🏗️Software Engineering: Extreme Programming (Just the Quotes)

"Given the choice between an extremely skilled loner and a competent-but-social programmer, XP teams consistently choose the more social candidate. The best interviewing technique is to have the candidate work with the team for a day. Pair programming provides an excellent test of technical and social skills." (Kent Beck, "Extreme Programming Explained: Embrace Change", 1999)

"The XP philosophy is to start where you are now and move towards the ideal. From where you are now, could you improve a little bit?" (Kent Beck, "Extreme Programming Explained: Embrace Change", 1999)

"The new concept of Extreme Programming (XP) is gaining more and more acceptance, partially because it is controversial, but primarily because it is particularly well-suited to help the small software development team succeed. [...] XP is controversial, many software development sacred cows don't make the cut in XP; it forces practitioners to take a fresh look at how software is developed." (Kent Beck, "Abstract Extreme Programming Explained", 2000)

"Don't produce voluminous design documents at the beginning. Don't even produce them in the middle: produce them at the end. Extreme Programming teaches you how to keep the design flexible, for highest flexibility and fastest implementation. The design documents you produce at the beginning will go out of date very quickly (they always do, even on non-Extreme projects), and you 'Il either waste time updating the docs or let them get out of date. Either is bad." (Ron Jeffries, "Extreme Programming Installed", 2001)

"Don't try to freeze requirements before you start implementing. Requirements changes show that the customer is learning! Sure, it would be nice if they knew just what they wanted before you started building things, but the fact is that when they see what you're building, they'll learn what they meant. XP lets you use a development and planning approach that allows for change, without big up-front investment in frameworks or flexibility." (Ron Jeffries, "Extreme Programming Installed", 2001)

"Extreme Programming is a discipline of software development with values of simplicity, communication, feedback and courage. We focus on the roles of customer, manager, and programmer and accord key rights and responsibilities to those in those roles." (Ron Jeffries, "Extreme Programming Installed", 2001)

"The values of XP are simplicity, communication, feedback, and courage. [...] Use simple design and programming practices, and simple methods of planning, tracking, and reporting. Test your program and your practices, using feedback to decide how to steer the project. Working together in this way gives the team courage."  (Ron Jeffries, "Extreme Programming Installed", 2001)

"We all strive for simple and clear design, don't we? Of course we do. But in XP, we take it to extremes. At every moment in time, we want  the system to be as simple as possible. That means that we want no  additional functions that aren't used, no structures or algorithms that  are more complex than the current need would dictate." (Ron Jeffries, "Extreme Programming Installed", 2001)

"XP isn't slash and burn programming, not code and fix, not at all. Extreme Programming is about careful and continuous design, rapid  feedback from extensive testing, and the maintenance of relentlessly clear and high-quality code." (Ron Jeffries, "Extreme Programming Installed, 2001)

"Extreme Programming is the most prominent new, light-weight (or agile) methods, defined to contrast the current heavy-weight and partially overloaded object-oriented methods. It focuses on the core issues of software technology. One of its principles is not to rely on diagrams to document a system." (Bernhard Rumpe, "Executable Modeling with UML. A vision or a Nightmare", Issues & Trends of Information Technology Management in Contemporary Associations, 2002)

"Extreme Programming recognizes the importance of design decisions, but it strongly resists upfront design. Instead, it puts an admirable effort into communication and improving the project’s ability to change course rapidly. With that ability to react, developers can use the “simplest thing that could work” at any stage of a project and then continuously refactor, making many small design improvements, ultimately arriving at a design that fits the customer’s true needs." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"In fact, XP works best for developers with a sharp design sense. The XP process assumes that you can improve a design by refactoring, and that you will do this often and rapidly. But past design choices make refactoring itself either easier or harder. The XP process attempts to increase team communication, but model and design choices clarify or confuse communication." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Extreme Programming is the first popular methodology to view software development as an exercise in coding rather than an exercise in management." (Ben Aveling, "XP lite considered harmful?", 2004)

"One of the central axioms of extreme programming is the disciplined use of regression testing during stepwise software development." (Thomas A Henzinger et al, "Extreme model checking", 2004)

🏗️Software Engineering: Simplicity vs Complexity (Just the Quotes)

"Simplicity of structure means organic unity, whether the organism be simple or complex; and hence in all times the emphasis which critics have laid upon Simplicity, though they have not unfrequently confounded it with narrowness of range." (George H Lewes, "The Principles of Success in Literature", 1865)

"The first obligation of Simplicity is that of using the simplest means to secure the fullest effect. But although the mind instinctlvely rejects all needless complexity, we shall greatly err if we fail to recognise the fact, that what the mind recoils from is not the complexity, but the needlessness." (George H Lewes, "The Principles of Success in Literature", 1865)

"Simplicity is the soul of efficiency." (Austin Freeman, "The Eye of Osiris", 1911)

"The complexity of a system is no guarantee of its accuracy." (John P Jordan, "Cost accounting; principles and practice", 1920)

"[Disorganized complexity] is a problem in which the number of variables is very large, and one in which each of the many variables has a behavior which is individually erratic, or perhaps totally unknown. However, in spite of this helter-skelter, or unknown, behavior of all the individual variables, the system as a whole possesses certain orderly and analyzable average properties. [...] [Organized complexity is] not problems of disorganized complexity, to which statistical methods hold the key. They are all problems which involve dealing simultaneously with a sizable number of factors which are interrelated into an organic whole. They are all, in the language here proposed, problems of organized complexity." (Warren Weaver, "Science and Complexity", American Scientist Vol. 36, 1948)

"A theory is the more impressive the greater the simplicity of its premises is, the more different kinds of things it relates, and the more extended its area of applicability." (Albert Einstein, "Autobiographical Notes", 1949)

"In products of the human mind, simplicity marks the end of a process of refining, while complexity marks a primitive stage." (Eric Hoffer, 1954)

"Nor does complexity deny the valid simplification which is part of the process of analysis, and even a method of achieving complex architecture itself." (Robert Venturi, "Complexity and Contradiction in Architecture Complexity and Contradiction in Architecture", 1966)

"The ideas need not be complex. Most ideas that are successful are ludicrously simple. Successful ideas generally have the appearance of simplicity because they seem inevitable." (Sol LeWitt, "Paragraphs on Conceptual Art", 1967) 

"Simplicity does not precede complexity, but follows it." (Alan Perlis, "Epigrams on Programming", 1982)

"The complexity of software is an essential property, not an accidental one. Hence, descriptions of a software entity that abstract away its complexity often abstracts away its essence." (Frederick P Brooks, "No Silver Bullet" , 1987)

"Organized simplicity occurs where a small number of significant factors and a large number of insignificant factors appear initially to be complex, but on investigation display hidden simplicity." (Robert L Flood & Ewart R Carson, "Dealing with Complexity: An introduction to the theory and application of systems", 1988)

"It is important to emphasize the value of simplicity and elegance, for complexity has a way of compounding difficulties and as we have seen, creating mistakes. My definition of elegance is the achievement of a given functionality with a minimum of mechanism and a maximum of clarity."  (Fernando J Corbató, "On Building Systems That Will Fail", 1991)

"Crude complexity is ‘the length of the shortest message that will describe a system, at a given level of coarse graining, to someone at a distance, employing language, knowledge, and understanding that both parties share (and know they share) beforehand." (Murray Gell-Mann, "What is Complexity?" Complexity Vol. 1 (1), 1995)

"A dictionary definition of the word ‘complex’ is: ‘consisting of interconnected or interwoven parts’ […] Loosely speaking, the complexity of a system is the amount of information needed in order to describe it. The complexity depends on the level of detail required in the description. A more formal definition can be understood in a simple way. If we have a system that could have many possible states, but we would like to specify which state it is actually in, then the number of binary digits (bits) we need to specify this particular state is related to the number of states that are possible." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"When the behavior of the system depends on the behavior of the parts, the complexity of the whole must involve a description of the parts, thus it is large. The smaller the parts that must be described to describe the behavior of the whole, the larger the complexity of the entire system. […] A complex system is a system formed out of many components whose behavior is emergent, that is, the behavior of the system cannot be simply inferred from the behavior of its components." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"Complexity is that property of a model which makes it difficult to formulate its overall behaviour in a given language, even when given reasonably complete information about its atomic components and their inter-relations." (Bruce Edmonds, "Syntactic Measures of Complexity", 1999)

"People who pride themselves on their 'complexity' and deride others for being 'simplistic' should realize that the truth is often not very complicated. What gets complex is evading the truth." (Thomas Sowell, "Barbarians inside the Gates and Other Controversial Essays", 1999)

"Complexity is the characteristic property of complicated systems we don’t understand immediately. It is the amount of difficulties we face while trying to understand it. In this sense, complexity resides largely in the eye of the beholder - someone who is familiar with s.th. often sees less complexity than someone who is less familiar with it. [...] A complex system is created by evolutionary processes. There are multiple pathways by which a system can evolve. Many complex systems are similar, but each instance of a system is unique." (Jochen Fromm, "The Emergence of Complexity", 2004)

"Simplicity is achieved in two general ways: minimizing the amount of essential complexity that anyone's brain has to deal with at any one time, and keeping accidental complexity from proliferating needlessly." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"Complexity carries with it a lack of predictability different to that of chaotic systems, i.e. sensitivity to initial conditions. In the case of complexity, the lack of predictability is due to relevant interactions and novel information created by them." (Carlos Gershenson, "Understanding Complex Systems", 2011)

"Complexity has shown that reductionism is limited, in the sense that emergent properties cannot be reduced. In other words, the properties at a given scale cannot be always described completely in terms of properties at a lower scale. This has led people to debate on the reality of phenomena at different scales." (Carlos Gershenson, "Complexity", 2011)

"I think there is a profound and enduring beauty in simplicity; in clarity, in efficiency. True simplicity is derived from so much more than just the absence of clutter and ornamentation. It's about bringing order to complexity." (Jonathan Ive, 2013)

"Simplicity in a system tends to increase that system’s efficiency. Because less can go wrong with fewer parts, less will. Complexity in a system tends to increase that system’s inefficiency; the greater the number of variables, the greater the probability of those variables clashing, and in turn, the greater the potential for conflict and disarray. Because more can go wrong, more will. That is why centralized systems are inclined to break down quickly and become enmeshed in greater unintended consequences." (Lawrence K Samuels,"Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

🏗️Software Engineering: Understanding (Just the Quotes)

"I consider computer science to be the art and science of exploiting automatic digital computers, and of creating the technology necessary to understand their use. It deals with such related problems as the design of better machines using known components:, the design and implementation of adequate software systems for communication between man and machine, and the design and analysis of methods of representing information by abstract symbols and of processes for manipulating these symbols." (George E Forsythe, "Stanford University's Program in Computer Science", 1965) 

"Most programs are too big to be comprehended as a single chunk. They must be divided into smaller pieces that can be conquered separately. That is the only way to write them reliably; it is the only way to read and understand them. [...] When a program is not broken up into small enough pieces, the larger modules often fail to deliver on these promises. They try to do too much, or too many different things, and hence are difficult to maintain and are too specialized for general use." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Recursion represents no saving of time or storage. Somewhere in the computer must be maintained a list of all the places a recursive routine is called, so the program can eventually find its way back. But the storage for that list is shared among many different uses. More important, it is managed automatically; many of the burdens of storage management and control flow are placed on the compiler, not on the programmer. And since bookkeeping details are hidden, the program can be much easier to understand. Learning to think recursively takes some effort, but it is repaid with smaller and simpler programs." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"The beginning of wisdom for a programmer is to recognize the difference between getting his program to work and getting it right. A program which does not work is undoubtedly wrong; but a program which does work is not necessarily right. It may still be wrong because it is hard to understand; or because it is hard to maintain as the problem requirements change; or because its structure is different from the structure of the problem; or because we cannot be sure that it does indeed work." (Michael A Jackson, "Principles of Program Design", 1975)

"The aim of the model is of course not to reproduce reality in all its complexity. It is rather to capture in a vivid, often formal, way what is essential to understanding some aspect of its structure or behavior." (Joseph Weizenbaum, "Computer power and human reason: From judgment to calculation" , 1976)

"Make no mistake about it: Computers process numbers - not symbols. We measure our understanding (and control) by the extent to which we can arithmetize an activity." (Alan J Perlis, "Epigrams on Programming", 1982)

"Wherever there is modularity there is the potential for misunderstanding: Hiding information implies a need to check communication." (Alan J Perlis, "Epigrams on Programming", 1982)

"Whether you call it a 'team' or an 'ensemble' or a 'harmonious work group' is not what matters; what matters is helping all parties understand that the success of the individual is tied irrevocably to the success of the whole." (Tom DeMarco & Timothy Lister, "Peopleware: Productive Projects and Teams", 1987)

"[Object-oriented analysis is] the challenge of understanding the problem domain and then the system's responsibilities in that light." (Edward Yourdon, "Object-Oriented Design", 1991) 

"An important symptom of an emerging understanding is the capacity to represent a problem in a number of different ways and to approach its solution from varied vantage points; a single, rigid representation is unlikely to suffice." (Howard Gardner, "The Unschooled Mind", 1991)

"The fundamentals of language are not understood to this day. [...] Until we understand languages of communication involving humans as they are then it is unlikely many of our software problems will vanish." (Richard W Hamming, "The Art of Probability for Scientists and Engineers", 1991)

"A problem with this 'waterfall' approach is that there will then be no user interface to test with real users until this last possible moment, since the 'intermediate work products' do not explicitly separate out the user interface in a prototype with which users can interact. Experience also shows that it is not possible to involve the users in the design process by showing them abstract specifications documents, since they will not understand them nearly as well as concrete prototypes." (Jakob Nielsen, "Usability Engineering", 1993)

"One should not start full-scale implementation efforts based on early user interface designs. Instead, early usability evaluation can be based on prototypes of the final systems that can be developed much faster and much more cheaply, and which can thus be changed many times until a better understanding of the user interface design has been achieved." (Jakob Nielsen, "Usability Engineering", 1993)

"Users are not designers, so it is not reasonable to expect them to come up with design ideas from scratch. However, they are very good at reacting to concrete designs they do not like or that will not work in practice. To get full benefits from user involvement, it is necessary to present these suggested system designs in a form the users can understand." (Jakob Nielsen, "Usability Engineering", 1993)

"Crude complexity is the length of the shortest message that will describe a system, at a given level of coarse graining, to someone at a distance, employing language, knowledge, and understanding that both parties share (and know they share) beforehand." (Murray Gell-Mann, "What is Complexity?" Complexity Vol. 1" (1), 1995)

"Good design protects you from the need for too many highly accurate components in the system. But such design principles are still, to this date, ill-understood and need to be researched extensively. Not that good designers do not understand this intuitively, merely it is not easily incorporated into the design methods you were taught in school. Good minds are still needed in spite of all the computing tools we have developed." (Richard Hamming, "The Art of Doing Science and Engineering: Learning to Learn", 1997)

"In an argument between a specialist and a generalist the expert usually wins by simply:" (1) using unintelligible jargon, and" (2) citing their specialist results which are often completely irrelevant to the discussion. The expert is, therefore, a potent factor to be reckoned with in our society. Since experts are both necessary, and also at times do great harm in blocking significant progress, they need to be examined closely. All too often the expert misunderstands the problem at hand, but the generalist cannot carry though their side to completion. The person who thinks they understand the problem and does not is usually more of a curse" (blockage) than the person who knows they do not understand the problem." (Richard Hamming, "The Art of Doing Science and Engineering: Learning to Learn", 1997)

"Any fool can write code that a computer can understand. Good programmers write code that humans can understand." (Martin Fowler, "Refactoring: Improving the Design of Existing Code", 1999)

"Computer programs are complex by nature. Even if you could invent a programming language that operated exactly at the level of the problem domain, programming would be complicated because you would still need to precisely define relationships between real-world entities, identify exception cases, anticipate all possible state transitions, and so on. Strip away the accidental work involved in representing these factors in a specific programming language and in a specific computing environment, and you still have the essential difficulty of defining the underlying real-world concepts and debugging your understanding of them." (Steve C McConnell," After the Gold Rush : Creating a True Profession of Software Engineering", 1999)

"We plan because: We need to ensure that we are always working on the most important thing we need to do. We need to coordinate with other people. When unexpected events occur we need to understand the consequences for the first two." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"Note that a project always begins as a concept, and a concept is usually a bit fuzzy. Our job as a team is to clarify the concept, to turn it into a shared understanding that the entire team will accept. It is failure to do this that causes many project failures." (James P Lewis, "Project Planning, Scheduling, and Control" 3rd Ed., 2001)

"As the least conscious layer of the user experience, the conceptual model has the paradoxical quality of also having the most impact on usability. If an appropriate conceptual model is faithfully represented throughout the interface, after users recognize and internalize the model, they will have a fundamental understanding of what the application does and how to operate it." (Bob Baxley, "Making the Web Work: Designing Effective Web Applications", 2002)

"We build models to increase productivity, under the justified assumption that it's cheaper to manipulate the model than the real thing. Models then enable cheaper exploration and reasoning about some universe of discourse. One important application of models is to understand a real, abstract, or hypothetical problem domain that a computer system will reflect. This is done by abstraction, classification, and generalization of subject-matter entities into an appropriate set of classes and their behavior." (Stephen J Mellor, "Executable UML: A Foundation for Model-Driven Architecture", 2002)

"If the design, or some central part of it, does not map to the domain model, that model is of little value, and the correctness of the software is suspect. At the same time, complex mappings between models and design functions are difficult to understand and, in practice, impossible to maintain as the design changes. A deadly divide opens between analysis and design so that insight gained in each of those activities does not feed into the other." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Many things can put a project off course: bureaucracy, unclear objectives, and lack of resources, to name a few. But it is the approach to design that largely determines how complex software can become. When complexity gets out of hand, developers can no longer understand the software well enough to change or extend it easily and safely. On the other hand, a good design can create opportunities to exploit those complex features." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Design patterns give names to practical knowledge; they define a high-level vocabulary for understanding and solving business statements graphically. Design patterns are presented in a standard format; they're like recipes in a cookbook or dress patterns in a catalog. Above all, they are practical, first as instructional materials and then as development tools." (Alan Chmura & J Mark Heumann, "Logical Data Modeling: What it is and How to do it", 2005)

"Abstractions matter to users too. Novice users want programs whose abstractions are simple and easy to understand; experts want abstractions that are robust and general enough to be combined in new ways. When good abstractions are missing from the design, or erode as the system evolves, the resulting program grows barnacles of complexity. The user is then forced to master a mass of spurious details, to develop workarounds, and to accept frequent, inexplicable failures." (Daniel Jackson, "Software Abstractions", 2006)

"Programming is the ability to talk to the computer in a language it can understand and using grammar and syntax that it can follow to get it to perform useful tasks for you." (Adrian Kingsley-Hughes & Kathie Kingsley-Hughes, "Beginning Programming", 2007)

"We tend to form mental models that are simpler than reality; so if we create represented models that are simpler than the actual implementation model, we help the user achieve a better understanding. [...] Understanding how software actually works always helps someone to use it, but this understanding usually comes at a significant cost. One of the most significant ways in which computers can assist human beings is by putting a simple face on complex processes and situations. As a result, user interfaces that are consistent with users' mental models are vastly superior to those that are merely reflections of the implementation model." (Alan Cooper et al,  "About Face 3: The Essentials of Interaction Design", 2007)

"I find OOP methodologically wrong. It starts with classes. It is as if mathematicians would start with axioms. You do not start with axioms - you start with proofs. Only when you have found a bunch of related proofs, can you come up with axioms. You end with axioms. The same thing is true in programming: you have to start with interesting algorithms. Only when you understand them well, can you come up with an interface that will let them work." (Alexander Stepanov, [Interview with A. Stepanov] 2008)

"The majority of the cost of a software project is in long-term maintenance. In order to minimize the potential for defects as we introduce change, it's critical for us to be able to understand what a system does. As systems become more complex, they take more and more time for a developer to understand, and there is an ever greater opportunity for a misunderstanding. Therefore, code should clearly express the intent of its author. The clearer the author can make the code, the less time others will have to spend understanding it. This will reduce defects and shrink the cost of maintenance." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"We see a lot of feature-driven product design in which the cost of features is not properly accounted. Features can have a negative value to customers because they make the products more difficult to understand and use. We are finding that people like products that just work. It turns out that designs that just work are much harder to produce that designs that assemble long lists of features." (Douglas Crockford, "JavaScript: The Good Parts", 2008)

"Design has the power to enrich our lives by engaging our emotions through image, form, texture, color, sound, and smell. The intrinsically human-centered nature of design thinking points to the next step: we can use our empathy and understanding of people to design experiences that create opportunities for active engagement and participation." (Tim Brown, "Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation", 2009)

"Prototypes should command only as much time, effort, and investment as is necessary to generate useful feedback and drive an idea forward. The greater the complexity and expense, the more 'finished' it is likely to seem and the less likely its creators will be to profit from constructive feedback - or even to listen to it. The goal of prototyping is not to create a working model. It is to give form to an idea to learn about its strengths and weaknesses and to identify new directions for the next generation of more detailed, more refined prototypes. A prototype's scope should be limited. The purpose of early prototypes might be to understand whether an idea has functional value." (Tim Brown, "Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation", 2009)

"We developers can easily develop blind spots. We necessarily have a different perspective from our users, and that can mean we miss important information that would be obvious to someone who understands things from their point of view. Furthermore, our focus tends to be on working out how to make the software work, not proving that it's broken." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)

"Although it is focused on the code, refactoring has a large impact on the design of a system. It is vital for senior designers and architects to understand the principles of refactoring and to use them in their projects." (Jay Fields et al, "Refactoring: Ruby Edition", 2010)

"Understanding the causes of system failures may help organizations avoid them, although there are no guarantees." (Phil Simon, "Why New Systems Fail: An Insider's Guide to Successful IT Projects", 2010)

"What can you do to actually make your code tell the truth as clearly as possible? Strive for good names. Structure your code with respect to cohesive functionality, which also eases naming. Decouple your code to achieve orthogonality. Write automated tests explaining the intended behavior and check the interfaces. Refactor mercilessly when you learn how to code a simpler, better solution. Make your code as simple as possible to read and understand." (Peter Sommerlad, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"Complexity carries with it a lack of predictability different to that of chaotic systems, i.e. sensitivity to initial conditions. In the case of complexity, the lack of predictability is due to relevant interactions and novel information created by them." (Carlos Gershenson, "Understanding Complex Systems", 2011)

"Few would deny the importance of writing quality code. High quality code contains less bugs, and is easier to understand and easier to maintain. However, the precise definitions of code quality can be more subjective, varying between organizations, teams, and even individuals within a team." (John F Smart, "Jenkins: The Definitive Guide", 2011)

"Programming is a personal activity and there is no general process that is usually followed. Some programmers start with components that they understand, develop these, and then move on to less-understood components. Others take the opposite approach, leaving familiar components till last because they know how to develop them. Some developers like to define data early in the process then use this to drive the program development; others leave data unspecified for as long as possible." (Ian Sommerville, "Software Engineering" 9th Ed., 2011)

"The conceptual model is not the users' mental model of the application. [...] users of an application form mental models of it to allow them to predict its behavior. A mental model is the user's high-level understanding of how the application works; it allows the user to predict what the application will do in response to various user-actions. Ideally, a user's mental model of an application should be similar to the designers' conceptual model, but in practice the two models may differ signicantly. Even if a user-s mental model is the same as the designer's conceptual model, they are distinct models." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)

"If the user can't understand it, the design and the designer have failed." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"Programming is a science dressed up as art, because most of us don't understand the physics of software and it's rarely, if ever, taught. The physics of software is not algorithms, data structures, languages, and abstractions. These are just tools we make, use, and throw away. The real physics of software is the physics of people. Specifically, it's about our limitations when it comes to complexity and our desire to work together to solve large problems in pieces. This is the science of programming: make building blocks that people can understand and use easily, and people will work together to solve the very largest problems." (Pieter Hintjens, "ZeroMQ: Messaging for Many Applications", 2012)

"Development is a design process. Design processes are generally evaluated by the value they deliver rather than a conformance to plan. Therefore, it makes sense to move away from plan-driven projects and toward value-driven projects. [...] The realization that the source code is part of the design, not the product, fundamentally rewires our understanding of software." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"Feature extraction is also the most creative part of data science and the one most closely tied to domain expertise. Typically, a really good feature will correspond to some real-world phenomenon. Data scientists should work closely with domain experts and understand what these phenomena mean and how to distill them into numbers." (Field Cady, "The Data Science Handbook", 2017)

"Once we understand our user's mental model, we can capture it in a conceptual model. The conceptual model is a representation of the mental model using elements, relationships, and conditions. Our design and final system will be the tangible result of this conceptual model." (Pau Giner & Pablo Perea, "UX Design for Mobile, 2017)

"There aren't enough programmers in the world to do the amount of programming involved in making computers do everything we want or need." (Brian W Kernighan, "Understanding the Digital World", 2017)

"A key contribution of DevOps was to raise awareness of the problems lingering in how teams interacted" (or not) across the delivery chain, causing delays, rework, failures, and a lack of understanding and empathy toward other teams. It also became clear that such issues were not only happening between application development and operations teams but in interactions with many other teams involved in software delivery, like QA, InfoSec, networking, and more." (Matthew Skelton & Manuel Pais, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

"Data-intensive projects generally involve at least one person who understands all the nuances of the application, process, and source and target data. These are the people who also know about all the abnormalities in the data and the workarounds to deal with them, and are the experts. This is especially true in the case of legacy systems that store and use data in a manner it should not be used. The knowledge is not documented anywhere and is usually inside the minds of the people. When the experts leave, with no one having a true understanding of the data, the data are not used properly and everything goes haywire." (Rupa Mahanti, "Data Quality: Dimensions, Measurement, Strategy, Management, and Governance", 2019)

"Teams are always works in progress, but they are also your best shot at delivering value continuously and sustainably by aligning them with the business. Ideally, teams should be long lived and autonomous, with engaged team members. However, teams don't live in isolation. They need to understand how and when to interact with each other. And these team interactions need to evolve over time to support the distinct phases of discovery and execution that products and technology go through during their lifetimes." (Matthew Skelton & Manuel Pais, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

"People are inherently imperfect - we like to say that humans are mostly a collection of intermittent bugs. But before you can understand the bugs in your coworkers, you need to understand the bugs in yourself. We're going to ask you to think about your own reactions, behaviors, and attitudes - and in return, we hope you gain some real insight into how to become a more efficient and successful software engineer who spends less energy dealing with people-related problems and more time writing great code." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"Great engineering managers find ways to give work meaning and make that meaning broadly understood. They align the realities of the engineering work they are tasked with to the aspirations and beliefs of their team members. [...] For your engineers, translating the why in a way they can understand and accept is a powerful tool for alignment and guiding decisions in the direction you want. [...] Translating outside of your team and upward to leadership" (managing up) is oftentimes the most impactful translation of all." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"The thing that makes software design difficult is that we must express thoughts about a problem and a solution we typically do not understand fully, using a language that does not contain many of our accustomed features of expression, to a system that is unforgiving of mistakes." (Alistair Cockburn)

"Documentation is not understanding, process is not discipline, formality is not skill." (Jim Highsmith)

"One measure of our understanding is the number of independent ways we are able to get to the same result." (Richard P Feynman) 

"The guy who knows about computers is the last person you want to have creating documentation for people who don't understand computers." (Adam Osborne)

🏗️Software Engineering: Data Structures (Just the Quotes)

"At the present time, choosing a programming language is equivalent to choosing a data structure, and if that data structure does not fit the data you want to manipulate then it is too bad. It would, in a sense, be more logical first to choose a data structure appropriate to the problem and then look around for, or construct with a kit of tools provided, a language suitable for manipulating that data structure." (Maurice V Wilkes, "Computers Then and Now", 1968)

"Choosing a better data structure is often an art, which we cannot teach. Often you must write a preliminary draft of the code before you can determine what changes in the data structure will help simplify control. [...] Choose a data representation that makes the program simple." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Let the data structure the program." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Use recursive procedures for recursively-defined data structures." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"The programmer's primary weapon in the never-ending battle against slow system is to change the intramodular structure. Our first response should be to reorganize the modules' data structures." (Fred Brooks, "The Mythical Man-Month: Essays on Software Engineering", 1975)

"The representation of knowledge in symbolic form is a matter that has pre-occupied the world of documentation since its origin. The problem is now relevant in many situations other than documents and indexes. The structure of records and files in databases: data structures in computer programming; the syntactic and semantic structure of natural language; knowledge representation in artificial intelligence; models of human memory: in all these fields it is necessary to decide how knowledge may be represented so that the representations may be manipulated." (Brian C Vickery, "Concepts of documentation", 1978)

"Rule 4. Fancy algorithms are buggier than simple ones, and they're much harder to implement. Use simple algorithms as well as simple data structures." (Rob Pike, "Notes on Programming in C" , 1989)

"Rule 5. Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming." (Rob Pike, "Notes on Programming in C", 1989)

"If a programmer designs a program, only half the job is done if they have only designed the data structures. They also have to design the procedures for operating on the structures. (Specifically, a programmer designs abstract data types.) Without the appropriate procedures for operating on data structures, a computer would literally get lost in the structures, even supposing it could start executing anything sensible." (Yin L Theng et al," 'Lost in hhyperspace': Psychological problem or bad design?", 1996)

"Often you'll see the same three or four data items together in lots of places: fields in a couple of classes, parameters in many method signatures. Bunches of data that hang around together really ought to be made into their own object." (Kent Beck, "Refactoring: Improving the Design of Existing Code", 1999)

"Smart data structures and dumb code works a lot better than the other way around." (Eric S Raymond, "The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary", 2001)

"In fact, I'm a huge proponent of designing your code around the data, rather than the other way around, and I think it's one of the reasons git has been fairly successful. […] I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships." (Linus Torvalds, [email] 2006)

"Computation at its root consists of a data structure (for input, output, and perhaps something being stored in between) and some process. One cannot talk about the process without describing the data structure. More importantly, different data structures enable certain computations to be done easily, whereas other data structures support other computations. Thus, the choice of data structure (representation) helps explain why a problem-solver does or does not successfully engage in a given process (cognition/behavior) or perhaps why a process takes as long or as short as it does." (Christian D Schunn et al, "Complex Visual Data Analysis, Uncertainty, and Representation", 2007)

"One of the essential parts of a formal training in programming is a long and demanding study of the large collection of algorithms that have already been discovered and analyzed, together with the Data Structures (carefully tailored, seemingly unnatural ways of organizing data for effective access) that go with them. As with any other engineering profession, it is impossible to do a good job without a thorough knowledge of what has been tried before. If a programmer starts the job fully armed with what is already known, they will have some chance of finding something new. Inventiveness is important: not all problems have been seen before. A programmer who does not already know the standard algorithms and data structures is doomed to nothing more than rediscovering the basics." (Robert Plant & Stephen Murrell, "An Executive’s Guide to Information Technology: Principles, Business Models, and Terminology", 2007)

"A modeling language is usually based on some kind of computational model, such as a state machine, data flow, or data structure. The choice of this model, or a combination of many, depends on the modeling target. Most of us make this choice implicitly without further thinking: some systems call for capturing dynamics and thus we apply for example state machines, whereas other systems may be better specified by focusing on their static structures using feature diagrams or component diagrams. For these reasons a variety of modeling languages are available." (Steven Kelly & Juha-Pekka Tolvanen, "Domain-specific Modeling", 2008)

"Clearly, the search for a dividing line between code and data is fruitless—and not particularly flattering to our egos. Let’s abandon any attempt to find a higher truth here, and settle for a pragmatic definition. If a piece of generated text simply instantiates and provides values for a data structure, it’s data; otherwise, it’s code." (Steven Kelly & Juha-Pekka Tolvanen, "Domain-specific Modeling", 2008)

"Generally, the craft of programming is the factoring of a set of requirements into a a set of functions and data structures." (Douglas Crockford, "JavaScript: The Good Parts", 2008)

"If the data structure can’t be explained on a beer coaster, it’s too complex." (Felix von Leitner, "Source Code Optimization", 2009)

🏗️Software Engineering: Intent (Just the Quotes)

"The most important property of a program is whether it accomplishes the intention of its user." (C Anthony R Hoare, Communications of the ACM, 1969)

"Design patterns make it easier to reuse successful designs and architectures. Expressing proven techniques as design patterns makes them more accessible to developers of new systems. Design patterns help you choose design alternatives that make a system reusable and avoid alternatives that compromise reusability. Design patterns can even improve the documentation and maintenance of existing systems by furnishing an explicit specification of class and object interactions and their underlying intent. Put simply, design patterns help a designer get a design 'right' faster." (Erich Gamma et al, "Design Patterns: Elements of Reusable Object-Oriented Software", 1994)

"But code as a design document does have its limits. It can overwhelm the reader with detail. Although its behavior is unambiguous, that doesn't mean it is obvious. And the meaning behind a behavior can be hard to convey. [...] A document shouldn't try to do what the code already does well. The code already supplies the detail. It is an exact specification of program behavior. Other documents need to illuminate meaning, to give insight into large-scale structures, and to focus attention on core elements. Documents can clarify design intent when the programming language does not support a straightforward implementation of a concept. Written documents should complement the code and the talking." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"The majority of the cost of a software project is in long-term maintenance. In order to minimize the potential for defects as we introduce change, it's critical for us to be able to understand what a system does. As systems become more complex, they take more and more time for a developer to understand, and there is an ever greater opportunity for a misunderstanding. Therefore, code should clearly express the intent of its author. The clearer the author can make the code, the less time others will have to spend understanding it. This will reduce defects and shrink the cost of maintenance." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"Treat your code like any other composition, such as a poem, an essay, a public blog, or an important email. Craft what you express carefully, so that it does what it should and communicates as directly as possible what it is doing; so that it still communicates your intention when you are no longer around. Remember that useful code is used much longer than ever intended." (Peter Sommerlad, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"When designers intentionally trick users into inviting friends or blasting a message to their social networks, they may see some initial growth, but it comes at the expense of users' goodwill and trust. When people discover they've been duped, they vent their frustration and stop using the product." (Nir Eyal, "Hooked: How to Build Habit-Forming Products", 2014)

"A lack of focus on a shared language and knowledge of the problem domain results in a codebase that works but does not reveal the intent of the business. This makes codebases difficult to read and maintain because translations between the analysis model and the code model can be costly and error prone." (Scott Millett, "Patterns Principles and Practices of Domain Driven Design", 2015)

"The primary intent behind the principle of encapsulation is to separate the interface and the implementation, which enables the two to change nearly independently. This separation of concerns allows the implementation details to be hidden from the clients who must depend only on the interface of the abstraction. If an abstraction exposes implementation details to the clients, it leads to undesirable coupling between the abstraction and its clients, which will impact the clients whenever the abstraction needs to change its implementation details. Providing more access than required can expose implementation details to the clients, thereby, violating the 'principle of hiding'." (Girish Suryanarayana et al, "Refactoring for Software Design Smells: Managing Technical Debt", 2015)

"The intention behind prototypes is to explore the visualization design space, as opposed to the data space. A typical project usually entails a series of prototypes; each is a tool to gather feedback from stakeholders and help explore different ways to most effectively support the higher-level questions that they have. The repeated feedback also helps validate the operationalization along the way." (Danyel Fisher & Miriah Meyer, "Making Data Visual", 2018)

"I believe that the backlash against statistics is due to four primary reasons. The first, and easiest for most people to relate to, is that even the most basic concepts of descriptive and inferential statistics can be difficult to grasp and even harder to explain. [...] The second cause for vitriol is that even well-intentioned experts misapply the tools and techniques of statistics far too often, myself included. Statistical pitfalls are numerous and tough to avoid. When we can't trust the experts to get it right, there's a temptation to throw the baby out with the bathwater. The third reason behind all the hate is that those with an agenda can easily craft statistics to lie when they communicate with us  [...] And finally, the fourth cause is that often statistics can be perceived as cold and detached, and they can fail to communicate the human element of an issue." (Ben Jones, "Avoiding Data Pitfalls: How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations", 2020)

🏗️Software Engineering: Programing Languages (Just the Quotes)

"The establishment of formal standards for proofs about programs [...] and the proposal that the semantics of a programming language may be defined independently of all processors for that language, by establishing standards of rigor for proofs about programs in the language, appears to be novel." (Robert Floyd, "Assigning Meanings to Programs", 1967)

"Computer languages of the future will be more concerned with goals and less with procedures specified by the programmer." (Marvin Minsky, "Form and Content in Computer Science", [Turing Award lecture] 1969)

"There is no programming language, no matter how structured, that will prevent programmers from making bad programs." (Larry Flon, "On research in structured programming", SIGPLAN 10(10), 1975)

"Most programming languages are decidedly inferior to mathematical notation and are little used as tools of thought in ways that would be considered significant by, say, an applied mathematician." (Kenneth E Iverson, "Notation as a Tool of Thought", 1979)

"The properties of executability and universality associated with programming languages can be combined, in a single language, with the well-known properties of mathematical notation which make it such an effective tool of thought." (Kenneth E Iverson, "Notation as a Tool of Thought", 1979)

"A language that doesn't affect the way you think about programming, is not worth knowing." (Alan Perlis, "Epigrams on Programming", 1982)

"A programming language is low level when its programs require attention to the irrelevant." (Alan J Perlis, "Epigrams on Programming", 1982)

"Some programming languages manage to absorb change, but withstand progress." (Alan J Perlis, "Epigrams on Programming", 1982)

"The only way to learn a new programming language is by writing programs in it." (Dennis Ritchie, "C Programming Language", 1988)

"A programming language is like a natural, human language in that it favors certain methaphors, images, and ways of thinking." (Seymour Papert, "Mindstorms: Children, Computers, And Powerful Ideas", 1993) 

"Although mathematical notation undoubtedly possesses parsing rules, they are rather loose, sometimes contradictory, and seldom clearly stated. [...] The proliferation of programming languages shows no more uniformity than mathematics. Nevertheless, programming languages do bring a different perspective. [...] Because of their application to a broad range of topics, their strict grammar, and their strict interpretation, programming languages can provide new insights into mathematical notation." (Kenneth E Iverson, "Math for the Layman", 1999) 

"Programming in an object-oriented language, however, does not ensure that the complexity of an application will be well encapsulated. Applying good programming techniques can improve encapsulation, but the full benefit of object-oriented programming can be realized only if encapsulation is a recognized goal of the design process." (Rebecca Wirfs-Brock, "Object-oriented Design: A responsibility-driven approach", 1989)

"Computer programs are complex by nature. Even if you could invent a programming language that operated exactly at the level of the problem domain, programming would be complicated because you would still need to precisely define relationships between real-world entities, identify exception cases, anticipate all possible state transitions, and so on. Strip away the accidental work involved in representing these factors in a specific programming language and in a specific computing environment, and you still have the essential difficulty of defining the underlying real-world concepts and debugging your understanding of them." (Steve C McConnell," After the Gold Rush : Creating a True Profession of Software Engineering", 1999)

“The precision provided (or enforced) by programming languages and their execution can identify lacunas, ambiguities, and other areas of potential confusion in conventional [mathematical] notation." (Kenneth E Iverson, "Math for the Layman", 1999)

"Programming languages on the whole are very much more complicated than they used to be: object orientation, inheritance, and other features are still not really being thought through from the point of view of a coherent and scientifically well-based discipline or a theory of correctness. My original postulate, which I have been pursuing as a scientist all my life, is that one uses the criteria of correctness as a means of converging on a decent programming language design - one which doesn’t set traps for its users, and ones in which the different components of the program correspond clearly to different components of its specification, so you can reason compositionally about it. [...] The tools, including the compiler, have to be based on some theory of what it means to write a correct program." (Charles A R Hoare, [interview] 2002)

"A programming language is for thinking of programs, not for expressing programs you've already thought of." (Paul Graham, "Hackers and Painters", 2003)

"All OO languages show some tendency to suck programmers into the trap of excessive layering. Object frameworks and object browsers are not a substitute for good design or documentation, but they often get treated as one. Too many layers destroy transparency: It becomes too difficult to see down through them and mentally model what the code is actually doing. The Rules of Simplicity, Clarity, and Transparency get violated wholesale, and the result is code full of obscure bugs and continuing maintenance problems." (Eric S Raymond, "The Art of Unix Programming", 2003)

"Few classical programmers found prototypal inheritance to be acceptable, and classically inspired syntax obscures the language’s true prototypal nature. It is the worst of both worlds." (Douglas Crockford, "JavaScript: The Good Parts", 2008)

"Most programming languages contain good parts and bad parts. I discovered that I could be better programmer by using only the good parts and avoiding the bad parts." (Douglas Crockford, "JavaScript: The Good Parts", 2008)

"Programmers need to be fluent in the language of the machine, whether real or virtual, and in the abstractions that can be related to that language via development tools. It is important to learn many different abstractions, otherwise some ideas become incredibly hard to express. Good programmers need to be able to stand outside their daily routine, to be aware of other languages that are expressive for other purposes. The time always comes when this pays off." (Klaus Marquardt, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

🏗️Software Engineering: Documentation (Just the Quotes)

"Amid a wash of paper, a small number of documents become the critical pivots around which every project's management revolves. These are the manager's chief personal tools." (William Bengough, "Scene in the old Congressional Library", 1897)

"Notice that even the data is commented. One of the most effective ways to document a program is simply to describe the data layout in detail. If you can specify for each important variable what values it can assume and how it gets changed, you have gone a long way to describing the program. [...] Document your data layouts." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"The best documentation for a computer program is a clean structure. It also helps if the code is well formatted, with good mnemonic identifiers and labels (if any are needed), and a smattering of enlightening comments. Flowcharts and program descriptions are of secondary importance; the only reliable documentation of a computer program is the code itself. The reason is simple -whenever there are multiple representations of a program, the chance for discrepancy exists. If the code is in error, artistic flowcharts and detailed comments are to no avail. Only by reading the code can the programmer know for sure what the program does." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Writing a computer program eventually boils down to writing a sequence of statements in the language at hand. How each of those statements is expressed determines in large measure the intelligibility of the whole; no amount of commenting, formatting, or supplementary documentation can entirely replace well expressed statements. After all, they determine what the program actually does." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"There is nothing in the programming field more despicable than an undocumented program." (Edward Yourdon, "Techniques of program structure and design", 1975)

"The representation of knowledge in symbolic form is a matter that has pre-occupied the world of documentation since its origin. The problem is now relevant in many situations other than documents and indexes. The structure of records and files in databases: data structures in computer programming; the syntactic and semantic structure of natural language; knowledge representation in artificial intelligence; models of human memory: in all these fields it is necessary to decide how knowledge may be represented so that the representations may be manipulated." (Brian C Vickery, "Concepts of Documentation", 1978)

"Even though it is better if the system can be used without documentation, it may be necessary to provide help and documentation. Any such information should be easy to search, focused on the user's task, list concrete steps to be carried out, and not be too large." (Jakob Nielsen, "Usability Engineering", 1994)

"The following two statements are usually both true: 

There's not enough documentation. 

There's too much documentation." (Larry Wall, [Usenet article], 1997)

"But code as a design document does have its limits. It can overwhelm the reader with detail. Although its behavior is unambiguous, that doesn’t mean it is obvious. And the meaning behind a behavior can be hard to convey. […] A document shouldn’t try to do what the code already does well. The code already supplies the detail. It is an exact specification of program behavior. Other documents need to illuminate meaning, to give insight into large-scale structures, and to focus attention on core elements. Documents can clarify design intent when the programming language does not support a straightforward implementation of a concept. Written documents should complement the code and the talking." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Good code is its own best documentation." (Steve McConnell, "Code Complete", 2004)

"Documentation is a love letter that you write to your future self." (Damian Conway, "Perl Best Practices", 2005)

"Developing fewer features allows you to conserve development resources and spend more time refining those features that users really need. Fewer features mean fewer things to confuse users, less risk of user errors, less description and documentation, and therefore simpler Help content. Removing any one feature automatically increases the usability of the remaining ones." (Jakob Nielsen, "Prioritizing Web Usability", 2006)

"Any comment that forces you to look in another module for the meaning of that comment has failed to communicate to you and is not worth the bits it consumes." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008) 

"Features have a specification cost, a design cost, and a development cost. There is a testing cost and a reliability cost. […] Features have a documentation cost. Every feature adds pages to the manual increasing training costs." (Douglas Crockford, "JavaScript: The Good Parts: The Good Parts", 2008)

Software is usually accompanied by documentation in the form of big fat scary manuals that nobody ever reads. (Dave Barry, "Dave Barry in Cyberspace", 2010)

"In addition to developing the proper culture, invest in your testing infrastructure by developing linters, documentation, or other assistance that makes it more difficult to write bad tests." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"Documentation is a practice concerned with all the processes involved in transferring documents from sources to users." (Brian C Vickery)

"Documentation is not understanding, process is not discipline, formality is not skill." (Jim Highsmith)

"The guy who knows about computers is the last person you want to have creating documentation for people who don't understand computers." (Adam Osborne)

"This is generally true: any sizeable piece of program, or even a complete program package, is only a useful tool that can be used in a reliable fashion, provided that the documentation pertinent for the user is much shorter than the program text. If any machine or system requires a very thick manual, its usefulness becomes for that very circumstance subject to doubt!" (Edsger W. Dijkstra, "On the reliability of programs")

🏗️Software Engineering: Object-Oriented Programming [OOP] (Just the Quotes)

"Object-oriented programming languages support encapsulation, thereby improving the ability of software to be reused, refined, tested, maintained, and extended. The full benefit of this support can only be realized if encapsulation is maximized during the design process. […] design practices which take a data-driven approach fail to maximize encapsulation because they focus too quickly on the implementation of objects." (Rebecca Wirfs-Brock, "Object-oriented Design: A. responsibility-driven approach", 1989)

"Perhaps the greatest strength of an object-oriented approach to development is that it offers a mechanism that captures a model of the real world." (Grady Booch, "Software Engineering with Ada", 1986)

"Object-oriented programming increases the value of these metrics by managing this complexity. The most effective tool available for dealing with complexity is abstraction. Many types of abstraction can be used, but encapsulation is the main form of abstraction by which complexity is managed in object-oriented programming. Programming in an object-oriented language, however, does not ensure that the complexity of an application will be well encapsulated. Applying good programming techniques can improve encapsulation, but the full benefit of object-oriented programming can be realized only if encapsulation is a recognized goal of the design process." (Rebecca Wirfs-Brock," Object-Oriented Design: A responsibility-driven approach", 1989)

"Programming in an object-oriented language, however, does not ensure that the complexity of an application will be well encapsulated. Applying good programming techniques can improve encapsulation, but the full benefit of object-oriented programming can be realized only if encapsulation is a recognized goal of the design process." (Rebecca Wirfs-Brock, "Object-oriented Design: A responsibility-driven approach", 1989)

"In object-oriented analysis, we seek to model the world by identifying the classes and objects that form the vocabulary of the problem domain, and in object-oriented design, we invent the abstractions and mechanisms that provide the behavior that this model requires." (Grady Booch, "Object-Oriented Design: With Applications", 1991) 

"Object-oriented analysis is a method of analysis that examines requirements from the perspective of the classes and objects found in the vocabulary of the problem domain."(Grady Booch, "Object-oriented design: With Applications", 1991)

"[Object-oriented analysis is] the challenge of understanding the problem domain and then the system's responsibilities in that light." (Edward Yourdon, "Object-Oriented Design", 1991) 

"Object-oriented programming is a method of implementation in which programs are organized as cooperative collections of objects, each of which represents an instance of some class, and whose classes are all members of a hierarchy of classes united via inheritance relationships." (Grady Booch, "Object-oriented design: With Applications", 1991)

"Structured design does not scale up well for extremely complex systems, and this method is largely inappropriate for use with object-based and object-oriented programming languages." (Grady Booch, "Object-oriented design: With Applications", 1991) 

"The object-oriented paradigm is useful when building software systems where there is a hierarchy defined as a ranking or ordering of abstractions. (Grady Booch, "Object-Oriented Design: With Applications", 1991)

"Whereas object-oriented analysis typically focuses upon one specific problem at a time, domain analysis seeks to identify the classes and objects that are common to all applications within a given domain, such as missile avionics systems, compilers, or accounting software." (Grady Booch, "Object-oriented design: With Applications", 1991)

"Object-oriented methods tend to focus on the lowest-level building block: the class and its objects." (Peter Coad, "Object-oriented patterns", 1992)

"Object-oriented domain analysis seeks to identify reusable items localized around objects e. g., classes, instances, systems of interacting objects, and kits." (Edward V Berard, "Essays on object-oriented software engineering", 1993)

"All OO languages show some tendency to suck programmers into the trap of excessive layering. Object frameworks and object browsers are not a substitute for good design or documentation, but they often get treated as one. Too many layers destroy transparency: It becomes too difficult to see down through them and mentally model what the code is actually doing. The Rules of Simplicity, Clarity, and Transparency get violated wholesale, and the result is code full of obscure bugs and continuing maintenance problems." (Eric S. Raymond, "The Art of Unix Programming", 2003)

"Objects are the real and conceptual things we find in the world around us. An object may be hardware, software, a concept (e. g., velocity), or even 'flesh and blood'. Objects are complete entities, i. e., they are not 'simply information' or 'simply information and actions'. Software objects strive to capture as completely as possible the characteristics of the 'real world' objects which they represent. Finally, objects are 'black boxes', i. e., their internal implementations are hidden from the outside world, and all interactions with an object take place via a well-defined interface." (Edward V Berard, "Essays onObject-Oriented Software Engineering", 1993) 

"The combination of threads, remote-procedure-call interfaces, and heavyweight object-oriented design is especially dangerous [...] if you are ever invited onto a project that is supposed to feature all three, fleeing in terror might well be an appropriate reaction." (Eric S Raymond, "The Art of UNIX Programming", 2003)

"Abstraction is the ability to engage with a concept while safely ignoring some of its details - handling different details at different levels. Any time you work with an aggregate, you're working with an abstraction. […] From a complexity point of view, the principal benefit of abstraction is that it allows you to ignore irrelevant details. Most real-world objects are already abstractions of some kind." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"Coupling describes how tightly a class or routine is related to other classes or routines. The goal is to create classes and routines with small, direct, visible, and flexible relations to other classes and routines, which is known as "loose coupling." The concept of coupling applies equally to classes and routines […] Good coupling between modules is loose enough that one module can easily be used by other modules." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"Encapsulation picks up where abstraction leaves off. Abstraction says, ‘You're allowed to look at an object at a high level of detail’. Encapsulation says, ‘Furthermore, you aren't allowed to look at an object at any other level of detail’." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"Object-oriented design is the roman numerals of computing." (Rob Pike, 2004)

"On a related topic, let me say that I'm not much of a fan of object-oriented design. I've seen some beautiful stuff done with OO, and I've even done some OO stuff myself, but it's just one way to approach a problem. For some problems, it's an ideal way; for others, it's not such a good fit. […] OO is great for problems where an interface applies naturally to a wide range of types, not so good for managing polymorphism (the machinations to get collections into OO languages are astounding to watch and can be hellish to work with), and remarkably ill-suited for network computing. That's why I reserve the right to match the language to the problem, and even - often - to coordinate software written in several languages towards solving a single problem. It's that last point - different languages for different subproblems - that sometimes seems lost to the OO crowd." (Rob Pike, [interview] 2004) 

"The steps in designing with objects are

- Identify the objects and their attributes (methods and data).

- Determine what can be done to each object.

- Determine what each object is allowed to do to other objects.

- Determine the parts of each object that will be visible to other objects—which parts will be public and which will be private.

- Define each object's public interface. 

These steps aren't necessarily performed in order, and they're often repeated. Iteration is important." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"Every system is built from a domain-specific language designed by the programmers to describe that system. Functions are the verbs of that language, and classes are the nouns."  (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"I find OOP methodologically wrong. It starts with classes. It is as if mathematicians would start with axioms. You do not start with axioms - you start with proofs. Only when you have found a bunch of related proofs, can you come up with axioms. You end with axioms. The same thing is true in programming: you have to start with interesting algorithms. Only when you understand them well, can you come up with an interface that will let them work." (Alexander Stepanov, [Interview with A. Stepanov] 2008)

"We do not want to expose the details of our data. Rather we want to express our data in abstract terms. This is not merely accomplished by using interfaces and/or getters and setters. Serious thought needs to be put into the best way to represent the data that an object contains. The worst option is to blithely add getters and setters." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"Polymorphism is one of the grand ideas that is fundamental to OO. The word, taken from Greek, means many (poly) forms (morph). In the context of programming, polymorphism refers to many forms of a particular class of objects or method. But polymorphism isn’t simply about alternate implementations. Used carefully, polymorphism creates tiny localized execution contexts that let us work without the need for verbose if-then-else blocks. Being in a context allows us to do the right thing directly, whereas being outside of that context forces us to reconstruct it so that we can then do the right thing. With careful use of alternate implementations, we can capture context that can help us produce less code that is more readable." (Kirk Pepperdine, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"More generally, each unit of code, from a block to a library, should have a narrow interface. Less communication reduces the reasoning required. This means that getters that return internal state are a liability - don’t ask an object for information to work with. Instead, ask the object to do the work with the information it already has. In other words, encapsulation is all - and only - about narrow interfaces." (Yechiel Kimchi [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"[Object-oriented analysis is] the challenge of understanding the problem domain and then the system's responsibilities in that light." (Ed Yourdon)

"Strive for class interfaces that are complete and minimal." (Scott Meyers) 

🏗️Software Engineering: Code (Just the Quotes)

"A clean design is more easily modified as requirements change or as more is learned about what parts of the code consume significant amounts of execution time. A 'clever' design that fails to work or to run fast enough can often be salvaged only at great cost. Efficiency does not have to be sacrificed in the interest of writing readable code - rather, writing readable code is often the only way to ensure efficient programs that are also easy to maintain and modify." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Choosing a better data structure is often an art, which we cannot teach. Often you must write a preliminary draft of the code before you can determine what changes in the data structure will help simplify control. [...] Choose a data representation that makes the program simple." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Don't comment bad code - rewrite it." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Don't just echo the code with comments make every comment count." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Jumping around unnecessarily in a computer program has proved to be a fruitful source of errors, and usually indicates that the programmer is not entirely in control of the code." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Make sure comments and code agree." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"The best documentation for a computer program is a clean structure. It also helps if the code is well formatted, with good mnemonic identifiers and labels" (if any are needed), and a smattering of enlightening comments. Flowcharts and program descriptions are of secondary importance; the only reliable documentation of a computer program is the code itself. The reason is simple -whenever there are multiple representations of a program, the chance for discrepancy exists. If the code is in error, artistic flowcharts and detailed comments are to no avail. Only by reading the code can the programmer know for sure what the program does." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"The fundamental problem with software maintenance is that fixing a defect has a substantial (20-50 percent) chance of introducing another. So the whole process is two steps forward and one step back. Why aren't defects fixed more cleanly? First, even a subtle defect shows itself as a local failure of some kind. In fact it often has system-wide ramifications, usually nonobvious. Any attempt to fix it with minimum effort will repair the local and obvious, but unless the structure is pure or the documentation very fine, the far-reaching effects of the repair will be overlooked. Second, the repairer is usually not the man who wrote the code, and often he is a junior programmer or trainee." (Frederick P. Brooks, The Mythical Man-Month" , 1975)

"Elements (lines of code) in a coincidentally-cohesive module have no relationship. Typically occurs as the result of modularizing existing code, to separate out redundant code." (Edward Yourdon & Larry L Constantine, "Structured Design: Fundamentals of a discipline of computer program and systems design", 1978)

"The major distinguishing feature of the spiral model is that it creates a risk-driven approach to the software process rather than a primarily document-driven or code-driven process. It incorporates many of the strengths of other models and resolves many of their difficulties." (Barry Boehm, "A spiral model of software development and enhancement", IEEE, 1988)

"Code migrates to data. Because of this law there is increasing awareness that bugs in code are only half the battle and that data problems should be given equal attention."" (Boris Beizer, "Software Testing Techniques", 1990)

"More than the act of testing, the act of designing tests is one of the best bug preventers known. The thinking that must be done to create a useful test can discover and eliminate bugs before they are coded - indeed, test-design thinking can discover and eliminate bugs at every stage in the creation of software, from conception to specification, to design, coding and the rest."" (Boris Beizer, "Software Testing Techniques", 1990)

"Third law: Code migrates to data. Because of this law there is increasing awareness that bugs in code are only half the battle and that data problems should be given equal attention."" (Boris Beizer, "Software Testing Techniques", 1990)

"Shipping first time code is like going into debt. A little debt speeds development so long as it is paid back promptly with a rewrite [...] The danger occurs when the debt is not repaid. Every minute spent on not-quite-right code counts as interest on that debt." (Ward Cunningham, "The WyCash Portfolio Management System", OOPSLA, 1992)

"From time to time, a complex algorithm will lead to a longer routine, and in those circumstances, the routine should be allowed to grow organically up to 100-200 lines." (A line is a noncomment, nonblank line of source code.) Decades of evidence say that routines of such length are no more error prone than shorter routines. Let issues such as the routine's cohesion, depth of nesting, number of variables, number of decision points, number of comments needed to explain the routine, and other complexity-related considerations dictate the length of the routine rather than imposing a length restriction per se." (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)

"Inheritance is the idea that one class is a specialization of another class. The purpose of inheritance is to create simpler code by defining a base class that specifies common elements of two or more derived classes. The common elements can be routine interfaces, implementations, data members, or data types. Inheritance helps avoid the need to repeat code and data in multiple locations by centralizing it within a base class. When you decide to use inheritance, you have to make several decisions: For each member routine, will the routine be visible to derived classes? Will it have a default implementation? Will the default implementation be overridable? For each data member" (including variables, named constants, enumerations, and so on), will the data member be visible to derived classes?" (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)

"Modularity's goal is to make each routine or class like a 'black box': You know what goes in, and you know what comes out, but you don't know what happens inside." (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)

"The source code is often the only accurate description of the software. On many projects, the only documentation available to programmers is the code itself. Requirements specifications and design documents can go out of date, but the source code is always up to date. Consequently, it's imperative that the code be of the highest possible quality." (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993) 

"The real value of tests is not that they detect bugs in the code, but that they detect inadequacies in the methods, concentration, and skills of those who design and produce the code." (Charles A R Hoare, "How Did Software Get So Reliable Without Proof?", Lecture Notes in Computer Science Vol. 1051, 1996)

"Any fool can write code that a computer can understand. Good programmers write code that humans can understand." (Martin Fowler, "Refactoring: Improving the Design of Existing Code", 1999)

"Bug tracking will allow you to uncover 'smells' in code" (to use a refactoring phrase). If there are a large number of problems in a particular segment of your project then you may want to really focus on that segment and stabilize it. How do you identify this clustering unless you keep track of the errors.(Ken Beck, 1999)

"Treating your users as co-developers is your least-hassle route to rapid code improvement and effective debugging." (Eric S Raymond, "The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary", 1999)

"When you feel the need to write a comment, first try to refactor the code so that any comment becomes superfluous." (Kent Beck, "Refactoring: Improving the Design of Existing Code", 1999)

"When you find you have to add a feature to a program, and the program's code is not structured in a convenient way to add the feature, first refactor the program to make it easy to add the feature, then add the feature."" (Kent Beck, "Refactoring: Improving the Design of Existing Code", 1999)

"Bugs are things that creep into your software against your will. Every defect in your code was put there by one of the programmers. Two of the programmers, with pair programming. With the customers we visit, when something goes wrong, they think it's a defect." (Ron Jeffries, "Extreme Programming Installed", 2001)

"Do build perfectly for today. Do the simple thing that solves today's problem, but do it well. Keep the code of high quality, just perfect for today's needs." (Ron Jeffries, "Extreme Programming Installed", 2001)

"Smart data structures and dumb code works a lot better than the other way around." (Eric S Raymond, "The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary", 2001)

"XP isn't slash and burn programming, not code and fix, not at all. Extreme Programming is about careful and continuous design, rapid  feedback from extensive testing, and the maintenance of relentlessly clear and high-quality code." (Ron Jeffries, "Extreme Programming Installed, 2001)

"Refactoring is the process of changing a software system in such a way that it does not alter the external behavior of the code yet improves its internal structure. It is a disciplined way to clean up code that minimizes the chances of introducing bugs. In essence when you refactor you are improving the design of the code after it has been written." (Martin Fowler et al, "Refactoring: Improving the Design of Existing Code", 2002)

"Without refactoring, the design of the program will decay. As people change code - changes to realize short-term goals or changes made without a full comprehension of the design of the code - the code loses its structure. It becomes harder to see the design by reading the code. Refactoring is rather like tidying up the code. Work is done to remove bits that aren't really in the right place. Loss of the structure of code has a cumulative effect. The harder it is to see the design in the code, the harder it is to preserve it, and the more rapidly it decays. Regular refactoring helps code retain its shape." (Martin Fowler et al, "Refactoring: Improving the Design of Existing Code", 2002)

"All OO languages show some tendency to suck programmers into the trap of excessive layering. Object frameworks and object browsers are not a substitute for good design or documentation, but they often get treated as one. Too many layers destroy transparency: It becomes too difficult to see down through them and mentally model what the code is actually doing. The Rules of Simplicity, Clarity, and Transparency get violated wholesale, and the result is code full of obscure bugs and continuing maintenance problems." (Eric S Raymond, "The Art of Unix Programming", 2003)

"But code as a design document does have its limits. It can overwhelm the reader with detail. Although its behavior is unambiguous, that doesn't mean it is obvious. And the meaning behind a behavior can be hard to convey. [...] A document shouldn't try to do what the code already does well. The code already supplies the detail. It is an exact specification of program behavior. Other documents need to illuminate meaning, to give insight into large-scale structures, and to focus attention on core elements. Documents can clarify design intent when the programming language does not support a straightforward implementation of a concept. Written documents should complement the code and the talking." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"If the architecture isolates the domain-related code in a way that allows a cohesive domain design loosely coupled to the rest of the system, then that architecture can probably support domain-driven DESIGN." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Models come in many varieties and serve many roles, even those restricted to the context of a software development project. Domain-driven design calls for a model that doesn't just aid early analysis but is the very foundation of the design [...]  Tightly relating the code to an underlying model gives the code meaning and makes the model relevant." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"The effectiveness of an overall design is very sensitive to the quality and consistency of fine-grained design and implementation decisions. With a MODEL-DRIVEN DESIGN, a portion of the code is an expression of the model; changing that code changes the model. Programmers are modelers, whether anyone likes it or not. So it is better to set up the project so that the programmers do good modeling work." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Good code is its own best documentation." (Steve McConnell, "Code Complete", 2004)

"On small, informal projects, a lot of design is done while the programmer sits at the keyboard. 'Design' might be just writing a class interface in pseudocode before writing the details. It might be drawing diagrams of a few class relationships before coding them. It might be asking another programmer which design pattern seems like a better choice. Regardless of how it's done, small projects benefit from careful design just as larger projects do, and recognizing design as an explicit activity maximizes the benefit you will receive from it." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)

"A commitment to simplicity of design means addressing the essence of design - the abstractions on which software is built - explicitly and up front. Abstractions are articulated, explained, reviewed and examined deeply, in isolation from the details of the implementation. This doesn't imply a waterfall process, in which all design and specification precedes all coding. But developers who have experienced the benefits of this separation of concerns are reluctant to rush to code, because they know that an hour spent on designing abstractions can save days of refactoring." (Daniel Jackson, "Software Abstractions", 2006)

"In fact, I'm a huge proponent of designing your code around the data, rather than the other way around, and I think it's one of the reasons git has been fairly successful. [...] I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships." (Linus Torvalds, [email] 2006)

"The picture of digital progress that so many ardent boosters paint ignores the painful record of actual programmers' epic struggles to bend brittle code into functional shape. That record is of one disaster after another, marking the field's historical time line like craters. Anyone contemplating the start of a big software development project today has to contend with this unfathomably discouraging burden of experience. It mocks any newcomer with ambitious plans, as if to say, What makes you think you're any different?" (Scott Rosenberg, "Dreaming in Code", 2007)

"There is almost always something you can pull off the shelf that will satisfy many of your needs. But usually the parts of what you need done that your off-the-shelf code won���t handle are the very parts that make your new project different, unique, innovative - and they're why you're building it in the first place." (Scott Rosenberg, "Dreaming in Code", 2007)

"To programmers, refactoring means rewriting a chunk of code to make it briefer, clearer, and easier to read without changing what it actually does. Refactoring is often compared to gardening; it is never finished." (Scott Rosenberg, "Dreaming in Code", 2007)

"Well-commented code is one hallmark of good programming practice; it shows that you care about what you're doing, and it is considerate to those who will come after you to fix your bugs. But comments also serve as a kind of back channel for programmer-to-programmer communication and even occasionally as a competitive arena or an outlet for silliness." (Scott Rosenberg, "Dreaming in Code", 2007)

"Clearly, the search for a dividing line between code and data is fruitlesand not particularly flattering to our egos. Let's abandon any attempt to find a higher truth here, and settle for a pragmatic definition. If a piece of generated text simply instantiates and provides values for a data structure, it's data; otherwise, it's code." (Steven Kelly & Juha-Pekka Tolvanen, "Domain-specific Modeling", 2008)

"Good software designs accommodate change without huge investments and rework. When we use code that is out of our control, special care must be taken to protect our investment and make sure future change is not too costly." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"If the discipline of requirements specification has taught us anything, it is that well-specified requirements are as formal as code and can act as executable tests of that code!"" (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"In an ideal system, we incorporate new features by extending the system, not by making modifications to existing code." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"It is a myth that we can get systems 'right the first time'. Instead, we should implement only today's stories, then refactor and expand the system to implement new stories tomorrow. This is the essence of iterative and incremental agility. Test-driven development, refactoring, and the clean code they produce make this work at the code level." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"It is not enough for code to work. Code that works is often badly broken. Programmers who satisfy themselves with merely working code are behaving unprofessionally. They may fear that they don't have time to improve the structure and design of their code, but I disagree. Nothing has a more profound and long-term degrading effect upon a development project than bad code." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"It is unit tests that keep our code flexible, maintainable, and reusable. The reason is simple. If you have tests, you do not fear making changes to the code! Without tests every change is a possible bug."" (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"Nothing has a more profound and long-term degrading effect upon a development project than bad code. Bad schedules can be redone, bad requirements can be redefined. Bad team dynamics can be repaired. But bad code rots and ferments, becoming an inexorable weight that drags the team down." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"The majority of the cost of a software project is in long-term maintenance. In order to minimize the potential for defects as we introduce change, it's critical for us to be able to understand what a system does. As systems become more complex, they take more and more time for a developer to understand, and there is an ever greater opportunity for a misunderstanding. Therefore, code should clearly express the intent of its author. The clearer the author can make the code, the less time others will have to spend understanding it. This will reduce defects and shrink the cost of maintenance." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"You should choose a set of simple rules that govern the format of your code, and then you should consistently apply those rules. If you are working on a team, then the team should agree to a single set of formatting rules and all members should comply." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"But remember that refactoring should never be combined with modifying the functionality of the code, and that very definitely includes fixing bugs." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)

"Every piece of code is built upon a platform of myriad assumptions - things that have to be true for it to behave as expected. More often than not, bugs arise because one or more of these assumptions are violated or turn out to be mistaken." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)

"Refactoring is the process of improving the design of existing code without changing its behavior. [...] Bug fixing often uncovers opportunities for refactoring. The very fact that you're working with code that contains a bug indicates that there is a chance that it could be clearer or better structured." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)

"Although it is focused on the code, refactoring has a large impact on the design of a system. It is vital for senior designers and architects to understand the principles of refactoring and to use them in their projects." (Jay Fields et al, "Refactoring: Ruby Edition", 2010)

"Treat your code like any other composition, such as a poem, an essay, a public blog, or an important email. Craft what you express carefully, so that it does what it should and communicates as directly as possible what it is doing; so that it still communicates your intention when you are no longer around. Remember that useful code is used much longer than ever intended." (Peter Sommerlad, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])

"Few would deny the importance of writing quality code. High quality code contains less bugs, and is easier to understand and easier to maintain. However, the precise definitions of code quality can be more subjective, varying between organizations, teams, and even individuals within a team." (John F Smart, "Jenkins: The Definitive Guide", 2011)

"One of the worst symptoms of a dysfunctional team is when each programmer builds a wall around his code and refuses to let other programmers touch it." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)

"Programming is an act of creation. When we write code we are creating something out of nothing. We are boldly imposing order upon chaos. We are confidently commanding, in precise detail, the behaviors of a machine that could otherwise do incalculable damage. And so, programming is an act of supreme arrogance." (Robert C Martin, "The Clean Coder: A code of conduct for professional programmers", 2011)

"The fact that bugs will certainly occur in your code does not mean you aren't responsible for them. The fact that the task to write perfect software is virtually impossible does not mean you aren't responsible for the imperfection." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)

"The true professional knows that delivering function at the expense of structure is a fool's errand. It is the structure of your code that allows it to be flexible. If you compromise the structure, you compromise the future." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)

"A lack of focus on a shared language and knowledge of the problem domain results in a codebase that works but does not reveal the intent of the business. This makes codebases difficult to read and maintain because translations between the analysis model and the code model can be costly and error prone." (Scott Millett, "Patterns Principles and Practices of Domain Driven Design", 2015)

"Areas of low complexity or that are unlikely to be invested in can be built without the need for perfect code quality; working software is good enough. Sometimes feedback and first-to-market are core to the success of a product; in this instance, it can make business sense to get working software up as soon as possible, whatever the architecture." (Scott Millett, "Patterns Principles and Practices of Domain Driven Design", 2015)

"But like many other aspects of code quality, building an abstraction for a problem comes with tradeoffs. Building a generalized solution takes more time than building one specific to a given problem. To break even, the time saved by the abstraction for future engineers needs to outweigh the time invested." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)

"Development is a design process. Design processes are generally evaluated by the value they deliver rather than a conformance to plan. Therefore, it makes sense to move away from plan-driven projects and toward value-driven projects. [...] The realization that the source code is part of the design, not the product, fundamentally rewires our understanding of software." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"It's wishful thinking to believe that all the code we write will be bug-free and work the first time. In actuality, much of our engineering time is spent either debugging issues or validating that what we're building behaves as expected. The sooner we internalize this reality, the sooner we will start to consciously invest in our iteration speed in debugging and validation loops." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)

"Sometimes, we build things in a way that makes sense in the short-term but that can be costly in the long-term. We work around design guidelines because it's faster and easier than following them. We punt on writing test cases for a new feature because there' too much work to finish before the deadline. We copy, paste, and tweak small chunks of existing code instead of refactoring it to support our use cases. Each of these tradeoffs, whether they're made from laziness or out of a conscious decision to ship sooner, can increase the amount of technical debt in our codebase." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)

"The fact that software engineering is not like other forms of engineering should really come as no surprise. Medicine is not like the law. Carpentry is not like baking. Software development is like one thing, and one thing only: software development. We need practices that make what we do more efficient, more verifiable, and easier to change. If we can do this, we can slash the short-term cost of building software, and all but eliminate the crippling long-term cost of maintaining it." (David S Bernstein, "Beyond Legacy Code", 2015)

"When we talk about software architecture, software is recursive and fractal in nature, etched and sketched in code. Everything is details. Interlocking levels of detail also contribute to a building's architecture, but it doesn't make sense to talk about physical scale in software. Software has structure - many structures and many kinds of structures-but its variety eclipses the range of physical structure found in buildings. You can even argue quite convincingly that there is more design activity and focus in software than in building architecture - in this sense, it's not unreasonable to consider software architecture more architectural than building architecture!" (Robert C Martin, "Clean Architecture: A Craftsman's Guide to Software Structure and Design", 2017)

"It is not loyalty or internal motivation that drives us programmers forward. We must write our code when the road to our personal success is absolutely clear for us and writing high quality code obviously helps us move forward on this road. To make this happen, the management has to define the rules of the game, also known as process", and make sure they are strictly enforced, which is much more difficult than 'being agile'."" (Yegor Bugayenko, "Code Ahead", 2018)

"Trying to determine the cognitive load of software using simple measures such as lines of code, number of modules, classes, or methods is misguided. [...] When measuring cognitive load, what we really care about is the domain complexity - how complex is the problem that we're trying to solve with software? A domain is a more largely applicable concept than software size." (Matthew Skelton, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

"A boat without a captain is nothing more than a floating waiting room: unless someone grabs the rudder and starts the engine, it's just going to drift along aimlessly with the current. A piece of software is just like that boat: if no one pilots it, you're left with a group of engineers burning up valuable time, just sitting around waiting for something to happen" (or worse, still writing code that you don't need)." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"Code coverage can provide some insight into untested code, but it is not a substitute for thinking critically about how well your system is tested." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"People are inherently imperfect - we like to say that humans are mostly a collection of intermittent bugs. But before you can understand the bugs in your coworkers, you need to understand the bugs in yourself. We're going to ask you to think about your own reactions, behaviors, and attitudes - and in return, we hope you gain some real insight into how to become a more efficient and successful software engineer who spends less energy dealing with people-related problems and more time writing great code." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"Programming is the immediate act of producing code. Software engineering is the set of policies, practices, and tools that are necessary to make that code useful for as long as it needs to be used and allowing collaboration across a team." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"When program developers are not territorial about their code and encourage others to look for bugs and potential improvements, progress speeds up dramatically." (Gerald Weinberg)