🏗️Software Engineering: Success (Just the Quotes)

"The engineer must be able not only to design, but to execute. A draftsman may be able to design, but unless he is able to execute his designs to successful operation he cannot be classed as an engineer. The production engineer must be able to execute his work as he has planned it. This requires two qualifications in addition to technical engineering ability: He must know men, and he must have creative ability in applying good statistical, accounting, and 'system' methods to any particular production work he may undertake." (Hugo Diemer, "Industrial Engineering", 1905)

"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)

"How do we convince people that in programming simplicity and clarity - in short: what mathematicians call 'elegance' - are not a dispensable luxury, but a crucial matter that decides between success and failure?" (Edsger W Dijkstra, "'Why is software so expensive?' An explanation to the hardware designer", 1982)

"No matter how vigorously a 'science' of design may be pushed, the successful design of real things in a contingent world will always be based more on art than on science. Unquantifiable judgments and choices are the elements that determine the way a design comes together. Engineering design is simply that kind of process. It always has been; it always will be. (Eugene S Ferguson , "Engineering and the Mind’s Eye", 1992)

"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)

"Our experience with designing and analyzing large and complex software-intensive systems has led us to recognize the role of business and organization in the design of the system and in its ultimate success or failure. Systems are built to satisfy an organization's requirements (or assumed requirements in the case of shrink-wrapped products). These requirements dictate the system's performance, availability, security, compatibility with other systems, and the ability to accommodate change over its lifetime. The desire to satisfy these goals with software that has the requisite properties influences the design choices made by a software architect." (Len Bass et al, "Software Architecture in Practice", 1998)

"Successful software development is a team effort - not just the development team, but the larger team consisting of customer, management and developers. [...] Every software project needs to deliver business value. To be successful, the team needs to build the right things, in the right order, and to be sure that what they build actually works." (Ron Jeffries, "Extreme Programming Installed", 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)

"A good system design is based on a sound conceptual model (architecture). A system design that has no conceptual structure and little logic to its organization is ultimately going to be unsuccessful. Good architecture will address all the requirements of the system at the right level of abstraction." (Vasudeva Varma, "Software Architecture: A Case Based Approach", 2009)

"Successful reproduction [of bugs] is all about control. If you control all the relevant variables, you will reproduce your problem. The trick, of course, is identifying which variables are relevant to the bug at hand, discovering what you need to set them to, and finding a way to do so." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)

"Design patterns are high-level abstractions that document successful design solutions. They are fundamental to design reuse in object-oriented development." (Ian Sommerville, "Software Engineering" 9th Ed., 2011)

"Software systems do not exist in isolation. They are used in a social and organizational context and software system requirements may be derived or constrained by that context. Satisfying these social and organizational requirements is often critical for the success of the system. One reason why many software systems are delivered but never used is that their requirements do not take proper account of how the social and organizational context affects the practical operation of the system." (Ian Sommerville, "Software Engineering" 9th Ed., 2011)

"No methodology can guarantee success. But a good methodology can provide a feedback loop for continual improvement and learning." (Ash Maurya, "Scaling Lean: Mastering the Key Metrics for Startup Growth", 2016)

IT: World Wide Web (Just the Quotes)

"The actual observed working structure of the organisation is a multiply connected 'web' whose interconnections evolve with time." (Tim Berners-Lee, "Information Management: A Proposal", 1989)

"This is why a 'web' of notes with links (like references) between them is far more useful than a fixed hierarchical system. When describing a complex system, many people resort to diagrams with circles and arrows. Circles and arrows leave one free to describe the interrelationships between things in a way that tables, for example, do not. The system we need is like a diagram of circles and arrows, where circles and arrows can stand for anything." (Tim Berners-Lee, "Information Management: A Proposal", 1989)

"Developments on the Internet over the next several years will set the course of our industry for a long time to come." (Bill Gates, "Internet Tidal Wave", [Microsoft internal memo], 1995)

"For me, the most exciting thing in the software area is the Internet, and part of the reason for that is no one owns it. It’s a free for all, it’s much like the early days of the personal computer." (Steve Jobs, Wall $treet Week, 1995)

"The Web is not going to change the world, certainly not in the next 10 years. It’s going to augment the world." (Steve Jobs, Wired, 1996)

"The internet model has many lessons for the new economy but perhaps the most important is its embrace of dumb swarm power. The aim of swarm power is superior performance in a turbulent environment. When things happen fast and furious, they tend to route around central control. By interlinking many simple parts into a loose confederation, control devolves from the center to the lowest or outermost points, which collectively keep things on course. A successful system, though, requires more than simply relinquishing control completely to the networked mob." (Kevin Kelly, "New Rules for the New Economy: 10 radical strategies for a connected world", 1998)

"I have a dream for the Web [...] and it has two parts. In the first part, the Web becomes a much more powerful means for collaboration between people. I have always imagine  the information space as something to which everyone has immediate and intuitive access, and not just to browse, but to create. Furthermore, the dream of people-to-people communication through shared knowledge must be possible for groups of all sizes, interacting electronically with as much ease as they do now in person." (Tim Berners-Lee, "Weaving the Web", 1999)

"It [the Internet] is inherently destructive of memory. You think you’re getting lots more [information] until you’ve found out you’ve made a bargain with the Devil. You’ve slowly mutated, and have become an extension of the machine." (James Billington, [interview] 1999)

"The first form of semantic data on the Web was metadata information about information. (There happens to be a company called Metadata, but I use the term here as a generic noun, as it has been used for many years.) Metadata consist of a set of properties of a document. By definition, metadata are data, as well as data about data. They describe catalogue information about who wrote Web pages and what they are about; information about how Web pages fit together and relate to each other as versions; translations, and reformattings; and social information such as distribution rights and privacy codes." (Tim Berners-Lee, "Weaving the Web", 1999)

"The web is more a social creation than a technical one. I designed it for a social effect - to help people work together - and not as a technical toy. The ultimate goal of the Web is to support and improve our web-like existence in the world. We clump into families, associations, and companies. We develop trust across the miles and distrust around the corner." (Tim Berners-Lee, "Weaving the Web", 1999)

"What we believe, endorse, agree with, and depend on is representable and, increasingly, represented on the Web. We all have to ensure that the society we build with the Web is the sort we intend." (Tim Berners-Lee, "Weaving the Web", 1999)

"The problem with the Internet startup craze isn’t that too many people are starting companies; it’s that too many people aren’t sticking with it. That’s somewhat understandable, because there are many moments that are filled with despair and agony, when you have to fire people and cancel things and deal with very difficult situations. That’s when you find out who you are and what your values are." (Steve Jobs, Fortune, 2000)

"The Web does not just connect machines, it connects people." (Tim Berners-Lee, [speech] 2008)

"Never before have we had so many tools to learn and to communicate. Yet the art of talking, listening, and ascertaining the truth seems more elusive than ever in this Internet and cable age, lost in a bitter stream of blather and misinformation." (Maureen Dowd, "Toilet-Paper Barricades", The New York Times, 2009)

"Big data is based on the feedback economy where the Internet of Things places sensors on more and more equipment. More and more data is being generated as medical records are digitized, more stores have loyalty cards to track consumer purchases, and people are wearing health-tracking devices. Generally, big data is more about looking at behavior, rather than monitoring transactions, which is the domain of traditional relational databases. As the cost of storage is dropping, companies track more and more data to look for patterns and build predictive models." (Neil Dunlop, "Big Data", 2015)

"If Web 2.0 for you is blogs and wikis, then that is people to people. But that was what the Web was supposed to be all along." (Tim Berners-Lee, [interview])

"One of the powerful things about networking technology like the Internet or the Web or the Semantic Web [...] is that the things we've just done with them far surpass the imagination of the people who invented them." (Tim Berners-Lee)

"The first step is putting data on the Web in a form that machines can naturally understand, or converting it to that form. This creates what I call a Semantic Web-a web of data that can be processed directly or indirectly by machines." (Tim Berners-Lee)

"The power of the Web is in its universality. Access by everyone regardless of disability is an essential aspect." (Tim Berners-Lee)

🏗️Software Engineering: Experts (Just the Quotes)

"Many people imagine that graphic charts cannot be understood except by expert mathematicians who have devoted years of study to the subject. This is a mistaken idea, and if instead of passing over charts as if they were something beyond their comprehension more people would make an effort to read them, much valuable time would be saved. It is true that some charts covering technical data are difficult even for an expert mathematician to understand, but this is more often the fault of the person preparing the charts than of the system." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Today's scientific investigations are so complicated that even experts in related fields may not understand them well. But there is a logic in the planning of experiments and in the analysis of their results that all intelligent people can grasp, and this logic is a great help in determining when to believe what we hear and read and when to be skeptical. This logic has a great deal to do with statistics, which is why statisticians have a unique interest in the scientific method, and why some knowledge of statistics can so often be brought to bear in distinguishing good arguments from bad ones." (Robert Hooke, "How to Tell the Liars from the Statisticians", 1983)

"All things which are proved to be impossible must obviously rest on some assumptions, and when one or more of these assumptions are not true then the impossibility proof fails - but the expert seldom remembers to carefully inspect the assumptions before making their 'impossible' statements." (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)

"Know the subject matter, learn it fast, or get a trustworthy expert. To identify the unknown, you must know the known. But don't be afraid to challenge experts on the basis of your logical reasoning. Sometimes a knowledge of the subject matter can blind the expert to the novel or unexpected." (Herbert F Spirer et al, "Misused Statistics" 2nd Ed, 1998)

"One reason we tend to accept statistics uncritically is that we assume that numbers come from experts who know what they're doing. [...] There is a natural tendency to treat these figures as straightforward facts that cannot be questioned." (Joel Best, "Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists", 2001)

"The fact that cognitive diversity matters does not mean that if you assemble a group of diverse but thoroughly uninformed people, their collective wisdom will be smarter than an expert's. But if you can assemble a diverse group of people who possess varying degrees of knowledge and insight, you're better off entrusting it with major decisions rather than leaving them in the hands of one or two people, no matter how smart those people are." (James Surowiecki, "The Wisdom of Crowds", 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)

"Much data in databases has a long history. It might have come from old 'legacy' systems or have been changed several times in the past. The usage of data fields and value codes changes over time. The same value in the same field will mean totally different thing in different records. Knowledge or these facts allows experts to use the data properly. Without this knowledge, the data may bc used literally and with sad consequences. The same is about data quality. Data users in the trenches usually know good data from bad and can still use it efficiently. They know where to look and what to check. Without these experts, incorrect data quality assumptions are often made and poor data quality becomes exposed." (Arkady Maydanchik, "Data Quality Assessment", 2007)

"Asking experts to do boring and repetitive, and yet technically demanding tasks is the most certain way of ensuring human error that we can think of, short of sleep deprivation, or inebriation." (David Farley & Jez Humble, "Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation", 2010)

"Experts in the 'Problem' area proceed to elaborate its complexity. They design complex Systems to attack it. This approach guarantees failure, at least for all but the most pedestrian tasks. The problem is a Problem precisely because it is incorrectly conceptualized in the first place, and a large System for studying and attacking the Problem merely locks in the erroneous conceptualization into the minds of everyone concerned. What is required is not a large System, but a different approach. Trying to design a System in the hope that the System will somehow solve the Problem, rather than simply solving the Problem in the first place, is to present oneself with two problems in place of one." (John Gall, "The Systems Bible: The Beginner's Guide to Systems Large and Small"[Systematics 3rd Ed.], 2011)

confusing, steeped in mystery and only truly understood by a few highly technical experts." (Alan Pennington, "The Customer Experience Book", 2016)

"Data from the customer interactions is the lifeblood for any organisation to view, understand and optimise the customer experience both remotely and on the front line! In the same way that customer experience experts understand that it’s the little things that count, it’s the small data that can make all the difference." (Alan Pennington, "The Customer Experience Book", 2016)

"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)

"The greatest leaders possess a combination of divergent traits: they are both experts and naïve, creative and efficient, serious and playful, social and reclusive - or at the very least, they surround themselves with this dynamic." (Beau Lotto, "Deviate: The Science of Seeing Differently", 2017)

"We, newbies and young programmers, don't like chaos because it makes us dependent on experts. We have to beg for information and feel bad." (Yegor Bugayenko, "Code Ahead", 2018)

"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)

"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)

"It is also important to note that data literacy is not about expecting to or becoming an expert; rather, it is a journey that must begin somewhere." (Angelika Klidas & Kevin Hanegan, "Data Literacy in Practice", 2022)

"Expert knowledge is a term covering various types of knowledge that can help define or disambiguate causal relations between two or more variables. Depending on the context, expert knowledge might refer to knowledge from randomized controlled trials, laws of physics, a broad scope of experiences in a given area, and more." (Aleksander Molak, "Causal Inference and Discovery in Python", 2023)

🎯Rukmani Gopalan - Collected Quotes

"A cloud data warehouse is an enterprise data warehouse offered as a managed service (PaaS) on public clouds with optimized integrations for data ingestion, analytics processing, and BI analytics." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"Churn refers to rapidly changing the activities and your plan when they are in flux - this is disruptive to your organization and slows your progress. Change refers to an inevitable movement in requirements and helps you plan for and execute this movement thoughtfully." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"Data mesh relies on a distributed architecture that consists of domains. Each domain is an independent unit of data and its associated storage and compute components. When an organization contains various product units, each with its own data needs, each product team owns a domain that is operated and governed independently by the product team. […] Data mesh has a unique value proposition, not just offering scale of infrastructure and scenarios but also helping shift the organization’s culture around data," (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022)

"If there is one thing I strongly recommend, it is to invest in a cloud data lake and start collecting and processing data that you believe is useful to your organization today." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"It’s true that data and data strategy are critical to the organization; however, it’s also true that data by itself is a means to the end of business or customer impact unless you’re a provider of data or data-related services." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"Plan for customer impact, and prepare to learn and fine-tune as you progress. Make choices based on the impact they offer to customers, and stay consistent in your implementation while keeping open-minded for learnings. Especially if you are an early adopter of a technology, you can help develop the technology with the provider and thus get ample support from the technology provider in return. Similarly, identify highly motivated early adopters within your customer base and offer to develop your solution with them." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"Real-time stream processing refers to the ingestion, processing, and consumption of data with a specific focus on speed, targeting near real time - that is, almost instantaneous results. […] Real-time stream processing pipelines involve data that is arriving from its source at very high velocity; in other words, it is data that is streaming into the system, just like rain or a waterfall." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"The lakehouse provides a key advantage over the modern data warehouse by eliminating the need to have two places to store the same data. [...] Data lakehouses offer the key benefit of being able to run performant BI/SQL-based scenarios directly on the data lake, right alongside the other exploratory data science and machine learning scenarios." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"The promise of a cloud data lake architecture lies in the boundless diversity of scenarios that it enables." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022) 

"The very simple definition of cloud data lake storage is a service available as a cloud offering that can serve as a central repository for all kinds of data (structured, unstructured, and semistructured) and can support data and transactions at a large scale." (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022)

"When it comes to data lakes, some things usually stay constant: the storage and processing patterns. Change could come in any of the following ways: Adding new components and processing or consumption patterns to respond to new requirements. […] Optimizing existing architecture for better cost or performance" (Rukmani Gopalan, "The Cloud Data Lake: A Guide to Building Robust Cloud Data Architecture", 2022)

🏗️Software Engineering: Implementation (Just the Quotes)

"The term architecture is used here to describe the attributes of a system as seen by the programmer, i.e., the conceptual structure and functional behavior, as distinct from the organization of the data flow and controls, the logical design, and the physical implementation." (Gene Amdahl et al, "Architecture of the IBM System", IBM Journal of Research and Development. Vol 8 (2), 1964)

"In computer design three levels can be distinguished: architecture, implementation and realisation; for the first of them, the following working definition is given: The architecture of a system can be defined as the functional appearance of the system to the user, its phenomenology. […] The inner structure of a system is not considered by the architecture: we do not need to know what makes the clock tick, to know what time it is. This inner structure, considered from a logical point of view, will be called the implementation, and its physical embodiment the realisation." (Gerrit A Blaauw, "Computer Architecture", 1972)

"Of course the technological base on which one builds is always advancing. As soon as one freezes a design, it becomes obsolete in terms of its concepts. But implementation of real products demands phasing and quantizing. The obsolescence of an implementation must be measured against other existing implementations, not against unrealized concepts. The challenge and the mission are to find real solutions to real problems on actual schedules with available resources." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"The separation of architectural effort from implementation is a very powerful way of getting conceptual integrity on very large projects." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"Systems with unknown behavioral properties require the implementation of iterations which are intrinsic to the design process but which are normally hidden from view. Certainly when a solution to a well-understood problem is synthesized, weak designs are mentally rejected by a competent designer in a matter of moments. On larger or more complicated efforts, alternative designs must be explicitly and iteratively implemented. The designers perhaps out of vanity, often are at pains to hide the many versions which were abandoned and if absolute failure occurs, of course one hears nothing. Thus the topic of design iteration is rarely discussed. Perhaps we should not be surprised to see this phenomenon with software, for it is a rare author indeed who publicizes the amount of editing or the number of drafts he took to produce a manuscript." (Fernando J Corbató, "A Managerial View of the Multics System Development", 1977)

"The design of a digital system starts with the specification of the architecture of the system and continues with its implementation and its subsequent realisation... the purpose of architecture is to provide a function. Once that function is established, the purpose of implementation is to give a proper cost-performance and the purpose of realisation is to build and maintain the appropriate logical organisation." (Gerrit A Blaauw, "Specification of Digital Systems", Proc. Seminar in Digital Systems Design, 1978)

"With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system." (John Zachman, "A Framework for Information Systems Architecture", 1987)

"Project failures are not always the result of poor methodology; the problem may be poor implementation. Unrealistic objectives or poorly defined executive expectations are two common causes of poor implementation. Good methodologies do not guarantee success, but they do imply that the project will be managed correctly." (Harold Kerzner, "Strategic Planning for Project Management using a Project Management Maturity Model", 2001)

"Most dashboards fail to communicate efficiently and effectively, not because of inadequate technology (at least not primarily), but because of poorly designed implementations. No matter how great the technology, a dashboard's success as a medium of communication is a product of design, a result of a display that speaks clearly and immediately. Dashboards can tap into the tremendous power of visual perception to communicate, but only if those who implement them understand visual perception and apply that understanding through design principles and practices that are aligned with the way people see and think." (Stephen Few, "Information Dashboard Design", 2006)

"Design is the bridging activity between gathering and implementation of software requirements that satisfies the required needs. […] The fundamental goal of design is to reduce the number of dependencies between modules, thus reducing the complexity of the system. This is also known as coupling; lesser the coupling the better is the design. On the other hand, higher the binding between elements within a module (known as cohesion) the better is the design." (Vasudeva Varma, "Software Architecture: A Case Based Approach", 2009)

"As a general rule, implementations do not just spontaneously combust. Failures tend to stem from the aggregation of many issues. Although some issues may have been known since the early stages of the project (for example, the sales cycle or system design), implementation teams discover the majority of problems during the middle of the implementation, typically during some form of testing." (Phil Simon, "Why New Systems Fail: An Insider’s Guide to Successful IT Projects", 2010)

"Implementation issues are not confined to the data and system realms. On the contrary, many of the problems encountered during a typical implementation stem from people, the roles they are required to play, political issues, and comfort zones." (Phil Simon, "Why New Systems Fail: An Insider’s Guide to Successful IT Projects", 2010)

"Implementing new systems is not like baking a cake. Organizations cannot follow a recipe with the following ingredients: three consultants, six weeks of testing, two training classes, and a healthy dose of project management. Nor do projects bake for six months until complete, after which time everyone enjoys a delicious piece of cake. For all sorts of reasons, a well-conceived and well-run project may fail, whereas a horribly managed project may come in under budget, ahead of schedule, and do everything that the vendor promised at the onset." (Phil Simon, "Why New Systems Fail: An Insider’s Guide to Successful IT Projects", 2010)

"Implementing new systems provides organizations with unique opportunities not only to improve their technologies, but to redefine and improve key business processes. Ultimately, for organizations to consider these new systems successes, the post-legacy environment must ensure that business processes, client end users, and systems work together." (Phil Simon, "Why New Systems Fail: An Insider’s Guide to Successful IT Projects", 2010)

"Pre-implementation, post-implementation, and ongoing data audits are invaluable tools for organizations. Used judiciously by knowledgeable and impartial resources, audits can detect, avoid, and minimize issues that can derail an implementation or cause a live system to fail. Rather than view them as superfluous expenses, organizations would be wise to conduct them at key points throughout the system’s life cycle." (Phil Simon, "Why New Systems Fail: An Insider’s Guide to Successful IT Projects", 2010)

"Agile approaches to software development consider design and implementation to be the central activities in the software process. They incorporate other activities, such as requirements elicitation and testing, into design and implementation. By contrast, a plan-driven approach to software engineering identifies separate stages in the software process with outputs associated with each stage." (Ian Sommerville, "Software Engineering" 9th Ed., 2011)

"Good architecture provides good interfaces that separate the shear layers of its implementation: a necessity for evolution and maintenance. Class-oriented programming puts both data evolution and method evolution in the same shear layer: the class. Data tend to remain fairly stable over time, while methods change regularly to support new services and system operations. The tension in these rates of change stresses the design." (James O Coplien & Trygve Reenskaug, "The DCI Paradigm: Taking Object Orientation into the Architecture World", 2014)

🏗️Software Engineering: Structure (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)

"Science aims at the discovery, verification, and organization of fact and information [...] engineering is fundamentally committed to the translation of scientific facts and information to concrete machines, structures, materials, processes, and the like that can be used by men." (Eric A Walker, "Engineers and/or Scientists", Journal of Engineering Education Vol. 51, 1961)

"The term architecture is used here to describe the attributes of a system as seen by the programmer, i.e., the conceptual structure and functional behavior, as distinct from the organization of the data flow and controls, the logical design, and the physical implementation." (Gene Amdahl et al, "Architecture of the IBM System", IBM Journal of Research and Development. Vol 8 (2), 1964)

"In computer design three levels can be distinguished: architecture, implementation and realisation; for the first of them, the following working definition is given: The architecture of a system can be defined as the functional appearance of the system to the user, its phenomenology. […] The inner structure of a system is not considered by the architecture: we do not need to know what makes the clock tick, to know what time it is. This inner structure, considered from a logical point of view, will be called the implementation, and its physical embodiment the realisation." (Gerrit A Blaauw, "Computer Architecture", 1972)

"There always is an architecture, whether it is defined in advance - as with modern computers - or found out after the fact - as with many older computers. For architecture is determined by behavior, not by words. Therefore, the term architecture, which rightly implies the notion of the arch, or prime structure, should not be understood as the vague overall idea. Rather, the product of the computer architecture, the principle of operations manual, should contain all detail which the user can know, and sooner or later is bound to know." (Gerrit A Blaauw, "Computer Architecture", 1972)

"A computer program is shaped by its data representation and the statements that determine its flow of control. These define the structure of a program. There is no sharp distinction between expression and organization; it is more a question of scope." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"Indent to show the logical structure of a program." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"It is a good rule of thumb that a program should read from top to bottom in the order that it will be executed; if this is not true, watch out for the bugs that often accompany poor structure. Make your programs read from top to bottom." (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)

"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 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 programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by exertion of the imagination. Few media of creation are so flexible, so easy to polish and rework, so readily capable of realizing grand conceptual structures. […] Yet the program construct, unlike the poet's words, is real in the sense that it moves and works, producing visible outputs separate from the construct itself. […] The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be." (Fred Brooks, The Mythical Man-Month: Essays, 1975) 

"As the size of software systems increases, the algorithms and data structures of the computation no longer constitute the major design problems. When systems are constructed from many components, the organization of the overall system - the software architecture - presents a new set of design problems. This level of design has been addressed in a number of ways including informal diagrams and descriptive terms, module interconnection languages, templates and frameworks for systems that serve the needs of specific domains, and formal models of component integration mechanisms." (David Garlan & Mary Shaw, "An introduction to software architecture", Advances in software engineering and knowledge engineering Vol 1, 1993)

"As a noun, design is the named (although sometimes unnamable) structure or behavior of a system whose presence resolves or contributes to the resolution of a force or forces on that system. A design thus represents one point in a potential decision space. A design may be singular (representing a leaf decision) or it may be collective (representing a set of other decisions). As a verb, design is the activity of making such decisions. Given a large set of forces, a relatively malleable set of materials, and a large landscape upon which to play, the resulting decision space may be large and complex. As such, there is a science associated with design (empirical analysis can point us to optimal regions or exact points in this design space) as well as an art (within the degrees of freedom that range beyond an empirical decision; there are opportunities for elegance, beauty, simplicity, novelty, and cleverness). All architecture is design but not all design is architecture. Architecture represents the significant design decisions that shape a system, where significant is measured by cost of change." (Grady Booch, "On design", 2006)

"An abstraction is not a module, or an interface, class, or method; it is a structure, pure and simple - an idea reduced to its essential form. Since the same idea can be reduced to different forms, abstractions are always, in a sense, inventions, even if the ideas they reduce existed before in the world outside the software. The best abstractions, however, capture their underlying ideas so naturally and convincingly that they seem more like discoveries." (Daniel Jackson, "Software Abstractions", 2006)

"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)

"A good system design is based on a sound conceptual model (architecture). A system design that has no conceptual structure and little logic to its organization is ultimately going to be unsuccessful. Good architecture will address all the requirements of the system at the right level of abstraction." (Vasudeva Varma, "Software Architecture: A Case Based Approach", 2009)

"The fundamental assumption underlying all software projects is that software is easy to change. If you violate this assumption by creating inflexible structures, then you undercut the economic model that the entire industry is based on." (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)

"Unfortunately, all too many projects become mired in a tar pit of poor structure. Tasks that used to take days begin to take weeks, and then months. Management, desperate to recapture lost momentum, hires more developers to speed things up. But these developers simply add to the morass, deepening the structural damage and raising the impediment." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)

"When you cannot concentrate and focus sufficiently, the code you write will be wrong. It will have bugs. It will have the wrong structure. It will be opaque and convoluted. It will not solve the customers’ real problems. In short, it will have to be reworked or redone. Working while distracted creates waste." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)

"Engineering is the art or science of utilizing, directing or instructing others in the utilization of the principles, forces, properties and substances of nature in the production, manufacture, construction, operation and use of things [...] or of means, methods, machines, devices and structures [...]" (Alfred W Kiddle)

🏗️Software Engineering: Debugging (Just the Quotes)

"As soon as we started programming, we found out to our surprise that it wasn't as easy to get programs right as we had thought. Debugging had to be discovered. I can remember the exact instant when I realized that a large part of my life from then on was going to be spent in finding mistakes in my own programs." (Maurice Wilkes, 1949)

"Everyone knows that debugging is twice as hard as writing a program in the first place. So if you're as clever as you can be when you write it, how will you ever debug it?" (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"When the operation to be done is more complex, write a separate subroutine or function. The ease of later comprehending, debugging, and changing the program will more than compensate for any overhead caused by adding the extra modules." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)

"The most effective debugging tool is still careful thought, coupled with judiciously placed print statements." (Brian Kernighan, "Unix for Beginners", 1979) 

"Testing proves a programmer’s failure. Debugging is the programmer’s vindication." (Boris Beizer, "Software Testing Techniques", 1990)

"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)

"People also underestimate the time they spend debugging. They underestimate how much time they can spend chasing a long bug. With testing, I know straight away when I added a bug. That lets me fix the bug immediately, before it can crawl off and hide. There are few things more frustrating or time wasting than debugging. Wouldn't it be a hell of a lot quicker if we just didn't create the bugs in the first place?" (Martin Fowler, 2002)

"For some reason software developers don’t think of debugging time as coding time. They think of debugging time as a call of nature, something that just has to be done. But debugging time is just as expensive to the business as coding time is, and therefore anything we can do to avoid or diminish it is good." (Robert C Martin, "The Clean Coder: A code of conduct for professional programmers", 2011)

"Continuous deployment is but one of many powerful tools at your disposal for increasing iteration speed. Other options include investing in time-saving tools, improving your debugging loops, mastering your programming workflows, and, more generally, removing any bottlenecks that you identify." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)

"Debugging is known as an open-ended sort of activity, and even seasoned programmers expect variable completion times when  faced with this type of task."  (Laurent Bossavit, "The Leprechauns of Software Engineering", 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)

🏗️Software Engineering: Teams (Just the Quotes)

"A baseball manager recognizes a nonphysical talent, hustle, as an essential gift of great players and great teams. It is the characteristic of running faster than necessary, moving sooner than necessary, trying harder than necessary. It is essential for great programming teams, too. Hustle provides the cushion, the reserve capacity, that enables a team to cope with routine mishaps, to anticipate and forfend minor calamities. The calculated response, the measured effort, are the wet blankets that dampen hustle. As we have seen, one must get excited about a one-day slip. Such are the elements of catastrophe." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"People who feel untrusted have little inclination to bond together into a cooperative team." (Tom DeMarco & Timothy Lister, "Peopleware: Productive Projects and Teams", 1987)

"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)

"The obsession with methodologies in the workplace is another instance of the high-tech illusion. It stems from the belief that what really matters is the technology. [...] Whatever the technological advantage may be, it may come only at the price of a significant worsening of the team's sociology." (Tom DeMarco & Timothy Lister, "Peopleware", 1987)

"Even when you have skilled, motivated, hard-working people, the wrong team structure can undercut their efforts instead of catapulting them to success. A poor team structure can increase development time, reduce quality, damage morale, increase turnover, and ultimately lead to project cancellation." (Steve McConnell, "Rapid Development", 1996)

"Software projects fail for one of two general reasons: the project team lacks the knowledge to conduct a software project successfully, or the project team lacks the resolve to conduct a project effectively." (Steve McConnell, "Software Project Survival Guide", 1997)

"No project can succeed when the team members have no commitment to the plan, so the first rule of project planning is that the people who must do the work should help plan that part of the project. You will not only gain their commitment to the plan, but also most likely cover all of the important issues that you may individually have forgotten."(James P Lewis, "Project Planning, Scheduling, and Control" 3rd Ed., 2001)

"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)

"Successful software development is a team effort - not just the development team, but the larger team consisting of customer, management and developers. [...] Every software project needs to deliver business value. To be successful, the team needs to build the right things, in the right order, and to be sure that what they build actually works." (Ron Jeffries, "Extreme Programming Installed", 2001)

"Failure usually results from a lack of a common approach to accomplish the work as a team. Inadequate leadership fails to create the environment in which teams can flourish. Furthermore, potential team members are seldom trained in how to share their efforts to accomplish team goals. The team may also assume they know more about teamwork than they actually do. So we need to be able to differentiate between superficial teamwork and the real thing." (Kevin Forsberg et al, "Visualizing Project Management: Models and frameworks for mastering complex systems" 3rd Ed., 2005)

"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)

"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)

"Teams should be able to act with the same unity of purpose and focus as a well-motivated individual." (Bill Gates, "Business @ the Speed of Thought: Succeeding in the Digital Economy", 2009)

"Coding standards are rules, sometimes relatively arbitrary, that define the coding styles and conventions that are considered acceptable within a team or organization. In many cases, agreeing on a set of standards, and applying them, is more important than the standards themselves." (John F Smart, "Jenkins: The Definitive Guide", 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)

"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)

"Automation is an essential backbone of DevOps. Automation is the use of solutions to reduce the need for human work. Automation can ensure that the software is built the same way each time, that the team sees every change made to the software, and that the software is tested and reviewed in the same way every day so that no defects slip through or are introduced through human error." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Conflicts between development and operations teams often originate from time pressures. Typically, a new software release must be deployed quickly. Another scenario that requires operations team to react quickly is when the system is down, and restoring it quickly becomes the highest priority. Th is situation often leads to a blame game where each side accuses the other of causing the problem." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Essential to improving collaboration is the alignment of incentives across teams as well as the application of shared processes and tools. The main attributes of aligned incentives include a shared definition of quality for the whole project or company and a commitment to it. Aligned with defined quality attributes, visibility and transparency can help to foster collaboration. Incentives must treat the development and operations groups as one team. That is, they should be rewarded for developing many changes that are stable and shipped."(Michael Hüttermann et al, "DevOps for Developers", 2013)

"The problem is that we cannot infer variations in individual productivity from data collected at the team level: we do not have an adequate theory of how a team’s productivity results from the aggregation of individual abilities, and in particular we cannot assume that a team’s output is a linear sum of individual 'productivities'." (Laurent Bossavit, "The Leprechauns of Software Engineering", 2015)

"There is common but flawed notion in enterprise IT circles that maintenance work requires less skill than full-scale development. As a result, project sponsors looking to reduce cost opt for a different team of lower-cost people for maintenance work. This is false economy. It hurts the larger business outcome and reduces IT agility." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"Any software project must have a technical leader, who is responsible for all technical decisions made by the team and have enough authority to make them. Responsibility and authority are two mandatory components that must be present in order to make it possible to call such a person an architect." (Yegor Bugayenko, "Code Ahead", 2018)

"Just by making the architect role explicit, a team can effectively resolve many technical conflicts." (Yegor Bugayenko, "Code Ahead", 2018)

"To make technical decisions, a result-oriented team needs a strong architect and a decision making process, not meetings." (Yegor Bugayenko, "Code Ahead", 2018)

"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)

"An obsession with 'feature delivery' ignores the human-related and team-related dynamics inherent in modern software, leading to a lack of engagement from staff, especially when the cognitive load is exceeded." (Matthew Skelton, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

"Organizations that rely too heavily on org charts and matrixes to split and control work often fail to create the necessary conditions to embrace innovation while still delivering at a fast pace. In order to succeed at that, organizations need stable teams and effective team patterns and interactions. They need to invest in empowered, skilled teams as the foundation for agility and adaptability. To stay alive in ever more competitive markets, organizations need teams and people who are able to sense when context changes and evolve accordingly." (Matthew Skelton & Manuel Pais, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 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)

"Teams take time to form and be effective. Typically, a team can take from two weeks to three months or more to become a cohesive unit. When (or if) a team reaches that special state, it can be many times more effective than individuals alone. If it takes three months for a team to become highly effective, we need to provide stability around and within the team to allow them to reach that level." (Matthew Skelton & Manuel Pais, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

"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)

"Engineering managers have a responsibility to optimize their teams. They improve engineering workflows and reduce dependencies and repetitive tasks. Self-sustaining teams minimize dependencies that hinder them in their efforts to achieve their objectives. Scalable teams minimize software delivery steps and eliminate bottlenecks. The mechanisms to achieve this may include the use of tools, conventions, documentation, processes, or abstract things such as values and principles. Any action that produces a tangible improvement in the speed, reliability, or robustness of your team’s work is worth your consideration." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"In a workplace setting, accountability is the willingness to take responsibility for one’s actions and their outcomes. Accountable team members take ownership of their work, admit their mistakes, and are willing to hold each other accountable as peers." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"Systems architecture is the portion of any project over which the engineering team has the most control. This design is usually less of a collaboration between different functions and more clearly in the domain of engineers. As such, engineering managers have a high responsibility to own this process and its decisions. To produce the best decisions possible, you must have the right decision-building blocks: complete information to work from and a structured methodology to guide you." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"One of the great enemies of design is when systems or objects become more complex than a person - or even a team of people - can keep in their heads. This is why software is generally beneath contempt." (Bran Ferren)

🏗️Software Engineering: Decision-Making (Just the Quotes)

"Engineering is a method and a philosophy for coping with that which is uncertain at the earliest possible moment and to the ultimate service to mankind. It is not a science struggling for a place in the sun. Engineering is extrapolation from existing knowledge rather than interpolation between known points. Because engineering is science in action - the practice of decision making at the earliest moment - it has been defined as the art of skillful approximation. No situation in engineering is simple enough to be solved precisely, and none worth evaluating is solved exactly. Never are there sufficient facts, sufficient time, or sufficient money for an exact solution, for if by chance there were, the answer would be of academic and not economic interest to society. These are the circumstances that make engineering so vital and so creative." (Ronald B Smith, "Engineering Is…", Mechanical Engineering Vol. 86 (5), 1964)

"Flow charts show the decision structure of a program, which is only one aspect of its structure. They show decision structure rather elegantly when the flow chart is on one page, but the overview breaks down badly when one has multiple pages, sewed together with numbered exits and connectors." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"By pulling together all of the decisions affecting the choice of modules and interrelationships in a system, we necessarily affect the way in which other decisions are organized and resolved. Thus, some issues which have traditionally been approached in a certain way during the earliest phase of a project may have to be dealt with in an entirely different manner at a much later stage once the designer graduates to a structured design approach." (Edward Yourdon & Larry L Constantine, "Structured Design: Fundamentals of a discipline of computer program and systems design", 1978)

"If we look at the discipline of software engineering, we see that the microeconomics branch of economics deals more with the types of decisions we need to make as software engineers or managers." (Barry Boehm, "Software Engineering Economics", 1981)

"Throughout the software life cycle, there are many decision situations involving limited resources in which software engineering economics techniques provide useful assistance."(Barry Boehm, "Software Engineering Economics", 1984)

"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)

"Executable UML is designed to produce a comprehensive and comprehensible model of a solution without making decisions about the organization of the software implementation. It is a highly abstract thinking tool to aid in the formalization of knowledge, a way of thinking about and describing the concepts that make up an abstract solution to a client problem." (Stephen J Mellor, "Executable UML: A Foundation for Model-Driven Architecture", 2002)

"The traditional view on software architecture suffers from a number of key problems that cannot be solved without changing our perspective on the notion of software architecture. These problems include the lack of first-class representation of design decisions, the fact that these design decisions are cross-cutting and intertwined, that these problems lead to high maintenance cost, because of which design rules and constraints are easily violated and obsolete design decisions are not removed." (Jan Bosch, "Software architecture: The next step", 2004)

"As a noun, design is the named (although sometimes unnamable) structure or behavior of a system whose presence resolves or contributes to the resolution of a force or forces on that system. A design thus represents one point in a potential decision space. A design may be singular (representing a leaf decision) or it may be collective (representing a set of other decisions). As a verb, design is the activity of making such decisions. Given a large set of forces, a relatively malleable set of materials, and a large landscape upon which to play, the resulting decision space may be large and complex. As such, there is a science associated with design (empirical analysis can point us to optimal regions or exact points in this design space) as well as an art (within the degrees of freedom that range beyond an empirical decision; there are opportunities for elegance, beauty, simplicity, novelty, and cleverness). All architecture is design but not all design is architecture. Architecture represents the significant design decisions that shape a system, where significant is measured by cost of change." (Grady Booch, "On design", 2006)

"Successful information design in movement systems gives the user the information he needs - and only the information he needs - at every decision point." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"A software architecture encompasses the significant decisions about the organization of the software system, the selection of structural elements and interfaces by which the system is composed, and determines their behavior through collaboration among these elements and their composition into progressively larger subsystems. Hence, the software architecture provides the skeleton of a system around which all other aspects of a system revolve." (Muhammad A Babar et al, "Agile Software Architecture Aligning Agile Processes and Software Architectures", 2014)

"As software professionals, we should be interested in knowing at least the basics of our own history, for just the same reasons that as citizens we are expected to know about our national history and about world history: so that we will be able to make informed decisions and know who to trust, who to listen to; so that we are not deceived by lies. Untrue histories generally have an agenda - 'someone trying to sell you something', as the saying goes." (Laurent Bossavit, "The Leprechauns of Software Engineering", 2015)

"DevOps recognizes the importance of culture. The acronym CAMS (culture, automation, measurement, and sharing) is used to encapsulate its key themes. Culture is acknowledged as all important in making development and IT operations work together effectively. But what is culture in this context? It is not so much about an informal dress code, flexible hours, or a free in-house cafeteria as it is about how decisions are taken, norms of behavior, protocols of communication, and the ways of navigating hierarchy and bureaucracy to get things done." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"Making good engineering decisions is all about weighing all of the available inputs and making informed decisions about the trade-offs. Sometimes, those decisions are based on instinct or accepted best practice, but only after we have exhausted approaches that try to measure or estimate the true underlying costs." (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)

"Systems architecture is the portion of any project over which the engineering team has the most control. This design is usually less of a collaboration between different functions and more clearly in the domain of engineers. As such, engineering managers have a high responsibility to own this process and its decisions. To produce the best decisions possible, you must have the right decision-building blocks: complete information to work from and a structured methodology to guide you." (Morgan Evans, "Engineering Manager's Handbook", 2023)

🏗️Software Engineering: Costs (Just the Quotes)

"Clearly, methods of designing programs so as to eliminate or at least illuminate side effects can have an immense payoff in maintenance costs. So can methods of implementing designs with fewer people, fewer interfaces, and hence fewer bugs." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"The second fallacious thought mode is expressed in the very unit of effort used in estimating and scheduling: the man-month. Cost does indeed vary as the product of the number of men and the number of months. Progress does not. Hence the man-month as a unit for measuring the size of a job is a dangerous and deceptive myth. It implies that men and months are interchangeable." (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)

"The design of a digital system starts with the specification of the architecture of the system and continues with its implementation and its subsequent realisation... the purpose of architecture is to provide a function. Once that function is established, the purpose of implementation is to give a proper cost-performance and the purpose of realisation is to build and maintain the appropriate logical organisation." (Gerrit A Blaauw, "Specification of Digital Systems", Proc. Seminar in Digital Systems Design, 1978)

"Economic principles underlie the overall structure of the software lifecycle, and its primary refinements of prototyping, incremental development, and advancemanship. The primary economic driver of the life-cycle structure is the significantly increasing cost of making a software change or fixing a software problem, as a function of the phase in which the change or fix is made." (Barry Boehm, "Software Engineering Economics", 1981)

"Poor management can increase software costs more rapidly than any other factor. Particularly on large projects, each of the following mismanagement actions has often been responsible for doubling software development costs." (Barry Boehm, "Software Engineering Economics", 1981)

"The entire idea behind prototyping is to save on the time and cost to develop something that can be tested with real users. These savings can only be achieved by somehow reducing the prototype compared with the full system: either cutting down on the number of features in the prototype or reducing the level of functionality of the features such that they seem to work but do not actually do anything." (Jakob Nielsen, "Usability Engineering", 1993)

"As a noun, design is the named (although sometimes unnamable) structure or behavior of a system whose presence resolves or contributes to the resolution of a force or forces on that system. A design thus represents one point in a potential decision space. A design may be singular (representing a leaf decision) or it may be collective (representing a set of other decisions). As a verb, design is the activity of making such decisions. Given a large set of forces, a relatively malleable set of materials, and a large landscape upon which to play, the resulting decision space may be large and complex. As such, there is a science associated with design (empirical analysis can point us to optimal regions or exact points in this design space) as well as an art (within the degrees of freedom that range beyond an empirical decision; there are opportunities for elegance, beauty, simplicity, novelty, and cleverness). All architecture is design but not all design is architecture. Architecture represents the significant design decisions that shape a system, where significant is measured by cost of change." (Grady Booch, "On design", 2006)

"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)

"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)

"Just as it can accelerate the pace of a project, prototyping allows the exploration of many ideas in parallel. Early prototypes should be fast, rough, and cheap. The greater the investment in an idea, the more committed one becomes to it. Overinvestment in a refined prototype has two undesirable consequences: First, a mediocre idea may go too far toward realization - or even, in the worst case, all the way. Second, the prototyping process itself creates the opportunity to discover new and better ideas at minimal cost." (Tim Brown, "Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation", 2009)

"Modeling is the creation of abstractions or representations of the system to predict and analyze performance, costs, schedules, and risks and to provide guidelines for systems research, development, design, manufacture, and management. Modeling is the centerpiece of systems architecting - a mechanism of communication to clients and builders, of design management with engineers and designers, of maintaining system integrity with project management, and of learning for the architect, personally."  (Mark W Maier, "The Art Systems of Architecting" 3rd Ed., 2009)

"But 'average cost to fix one defect' is a stupid metric […] It makes bad projects look good, and good projects look bad. How? By failing to divide the costs of fixing into two categories: fixed costs of detecting and fixing defects - costs which are the same no matter how buggy or how good the product is - and variable costs, those which you pay for each defect." (Laurent Bossavit, "The Leprechauns of Software Engineering", 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)

"Making good engineering decisions is all about weighing all of the available inputs and making informed decisions about the trade-offs. Sometimes, those decisions are based on instinct or accepted best practice, but only after we have exhausted approaches that try to measure or estimate the true underlying costs." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

"One of the broad truths we’ve seen to be true is the idea that finding problems earlier in the developer workflow usually reduces costs." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

🏗️Software Engineering: Integration (Just the Quotes)

"With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system." (John Zachman, "A Framework for Information Systems Architecture", 1987)

"The longer we wait between integrations and acceptance tests, the worse things get. Wait twice as long and we'll have four or more times the hassle. The reason is that one bug written just yesterday is pretty easy to find, while ten or a hundred written weeks ago can become almost impossible." (Ron Jeffries, "Extreme Programming Installed", 2001)

"The main activity of programming is not the origination of new independent programs, but in the integration, modification, and explanation of existing ones." (Terry Winograd, "Beyond Programming Languages", 1991)

"As the size of software systems increases, the algorithms and data structures of the computation no longer constitute the major design problems. When systems are constructed from many components, the organization of the overall system - the software architecture - presents a new set of design problems. This level of design has been addressed in a number of ways including informal diagrams and descriptive terms, module interconnection languages, templates and frameworks for systems that serve the needs of specific domains, and formal models of component integration mechanisms." (David Garlan & Mary Shaw, "An introduction to software architecture", Advances in software engineering and knowledge engineering Vol 1, 1993)

"Enterprise architecture is the organizing logic for business processes and IT infrastructure reflecting the integration and standardization requirements of a company's operation model. […] The key to effective enterprise architecture is to identify the processes, data, technology, and customer interfaces that take the operating model from vision to reality." (Jeanne W Ross et al, "Enterprise architecture as strategy: creating a foundation for business", 2006)

"Enterprise-architecture is the integration of everything the enterprise is and does. Even the term ‘architecture’ is perhaps a little misleading. It’s on a much larger scale, the scale of the whole rather than of single subsystems: more akin to city-planning than to the architecture of a single building. In something this large, there are no simple states of ‘as-is’ versus ‘to-be’, because its world is dynamic, not static. And it has to find some way to manage the messy confusion of what is, rather than the ideal that we might like it to be." (Tom Graves, "Real Enterprise-Architecture : Beyond IT to the whole enterprise", 2007)

"Acceptance testing relies on the ability to execute automated tests in a productionlike environment. However, a vital property of such a test environment is that it is able to successfully support automated testing. Automated acceptance testing is not the same as user acceptance testing. One of the differences is that automated acceptance tests should not run in an environment that includes integration to all external systems. Instead, your acceptance testing should be focused on providing a controllable environment in which the system under test can be run. 'Controllable' in this context means that you are able to create the correct initial state for our tests. Integrating with real external systems removes our ability to do this." (David Farley & Jez Humble, "Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation", 2010)

"In many applications, integration or functional tests are used by default as the standard way to test almost all aspects of the system. However integration and functional tests are not the best way to detect and identify bugs. Because of the large number of components involved in a typical end-to-end test, it can be very hard to know where something has gone wrong. In addition, with so many moving parts, it is extremely difficult, if not completely unfeasible, to cover all of the possible paths through the application." (John F Smart, "Jenkins: The Definitive Guide", 2011)

🏗️Software Engineering: Components (Just the Quotes)

"With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system." (John Zachman, "A Framework for Information Systems Architecture", 1987)

"Architecture is defined as a clear representation of a conceptual framework of components and their relationships at a point in time […] a discussion of architecture must take into account different levels of architecture. These levels can be illustrated by a pyramid, with the business unit at the top and the delivery system at the base. An enterprise is composed of one or more Business Units that are responsible for a specific business area. The five levels of architecture are Business Unit, Information, Information System, Data and Delivery System. The levels are separate yet interrelated. [...] The idea if an enterprise architecture reflects an awareness that the levels are logically connected and that a depiction at one level assumes or dictates that architectures at the higher level." (W Bradford Rigdon, "Architectures and Standards", 1989)

"Programmers are responsible for software quality - quality in their own work, quality in the products that incorporate their work, and quality at the interfaces between components. Quality has never been and will never be tested in. The responsibility is both moral and professional." (Boris Beizer, "Software Testing Techniques", 1990)

"As the size of software systems increases, the algorithms and data structures of the computation no longer constitute the major design problems. When systems are constructed from many components, the organization of the overall system - the software architecture - presents a new set of design problems. This level of design has been addressed in a number of ways including informal diagrams and descriptive terms, module interconnection languages, templates and frameworks for systems that serve the needs of specific domains, and formal models of component integration mechanisms." (David Garlan & Mary Shaw, "An introduction to software architecture", Advances in software engineering and knowledge engineering Vol 1, 1993)

"Although the concept of an enterprise architecture (EA) has not been well defined and agreed upon, EAs are being developed to support information system development and enterprise reengineering. Most EAs differ in content and nature, and most are incomplete because they represent only data and process aspects of the enterprise. […] An EA is a conceptual framework that describes how an enterprise is constructed by defining its primary components and the relationships among these components." (M A Roos, "Enterprise architecture: definition, content, and utility", Enabling Technologies: Infrastructure for Collaborative Enterprises, 1994)

"An enterprise architecture is an abstract summary of some organizational component's design. The organizational strategy is the basis for deciding where the organization wants to be in three to five years. When matched to the organizational strategy, the architectures provide the foundation for deciding priorities for implementing the strategy." (Sue A Conger, "The new software engineering", 1994)

"Software architecture involves the description of elements from which systems are built, interactions among those elements, patterns that guide their composition, and constraints on these patterns. In general, a particular system is defined in terms of a collection of components and interactions among those components. Such a system may in turn be used as a (composite) element in a larger system design." (Mary Shaw & David Garlan,"Characteristics of Higher-Level Languages for Software Architecture", 1994)

"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)

"Enterprise architecture is a family of related architecture components. This include information architecture, organization and business process architecture, and information technology architecture. Each consists of architectural representations, definitions of architecture entities, their relationships, and specification of function and purpose. Enterprise architecture guides the construction and development of business organizations and business processes, and the construction and development of supporting information systems." (Gordon B Davis, "The Blackwell encyclopedic dictionary of management information systems"‎, 1999)

"Enterprise architecture is a holistic representation of all the components of the enterprise and the use of graphics and schemes are used to emphasize all parts of the enterprise, and how they are interrelated. [...] Enterprise architectures are used to deal with intra-organizational processes, interorganizational cooperation and coordination, and their shared use of information and information technologies. Business developments, such as outsourcing, partnership, alliances and Electronic Data Interchange, extend the need for architecture across company boundaries." (Gordon B Davis," The Blackwell encyclopedic dictionary of management information systems"‎, 1999)

"Generically, an architecture is the description of the set of components and the relationships between them. […] A software architecture describes the layout of the software modules and the connections and relationships among them. A hardware architecture can describe how the hardware components are organized. However, both these definitions can apply to a single computer, a single information system, or a family of information systems. Thus 'architecture' can have a range of meanings, goals, and abstraction levels, depending on who’s speaking." (Frank J Armour et al, "A big-picture look at enterprise architectures", IT professional Vol 1 (1), 1999)

"Like a physical model, a conceptual model is an artificial system. It is however, made up of conceptual, and not physical components." (Ibrahim A Halloun, "Modeling Theory in Science Education", 2007) 

"Standards make it easier to reuse ideas and components, recruit people with relevant experience, encapsulate good ideas, and wire components together. However, the process of creating standards can sometimes take too long for industry to wait, and some standards lose touch with the real needs of the adopters they are intended to serve." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"Taking a systems approach means paying close attention to results, the reasons we build a system. Architecture must be grounded in the client’s/user’s/customer’s purpose. Architecture is not just about the structure of components. One of the essential distinguishing features of architectural design versus other sorts of engineering design is the degree to which architectural design embraces results from the perspective of the client/user/customer. The architect does not assume some particular problem formulation, as 'requirements' is fixed. The architect engages in joint exploration, ideally directly with the client/user/customer, of what system attributes will yield results worth paying for."  (Mark W Maier, "The Art Systems of Architecting" 3rd Ed., 2009)

"In many applications, integration or functional tests are used by default as the standard way to test almost all aspects of the system. However integration and functional tests are not the best way to detect and identify bugs. Because of the large number of components involved in a typical end-to-end test, it can be very hard to know where something has gone wrong. In addition, with so many moving parts, it is extremely difficult, if not completely unfeasible, to cover all of the possible paths through the application." (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)

🏗️Software Engineering: Standards (Just the Quotes)

"Autonomation [..] performs a dual role. It eliminates overproduction, an important waste in manufacturing, and prevents the production of defective products. To accomplish this, standard work procedures, corresponding to each player's ability, must be adhered to at all times." (Taiichi Ohno, "Toyota Production System: Beyond Large-Scale Production", 1978)

"Recognition of the idea that a programming language should have a precise mathematical meaning or semantics dates from the early 1960s. The mathematics provides a secure, unambiguous, precise and stable specification of the language to serve as an agreed interface between its users and its implementors. Furthermore, it gives the only reliable grounds for a claim that different implementations are implementations of the same language. So mathematical semantics are as essential to the objective of language standardisation as measurement and counting are to the standardisation of nuts and bolts." (C Anthony R Hoare, "Communicating Sequential Processes", 1985)

"The [software] builders’​​​​​​ view of quality, on the other hand, is very different. Since their self-esteem is strongly tied to the quality of the product, they tend to impose quality standards of their own. The minimum that will satisfy them is more or less the best quality they have achieved in the past. This is invariably a higher standard than what the market requires and is willing to pay for." (Tom DeMarco & Timothy Lister, "Peopleware: Productive Projects and Teams", 1987)

"A pattern is a fully realized form original, or model accepted or proposed for imitation. With patterns, small piecework is standardized into a larger chunk or unit. Patterns become the building blocks for design and construction. Finding and applying patterns indicates progress in a field of human endeavor." (Peter Coad, "Object-oriented patterns", 1992)

"The difference between standards and guidelines is that a standard specifies how the interface should appear to the user, whereas a set of guidelines provides advice about the usability characteristics of the interface." (Jakob Nielsen, "Usability Engineering", 1993)

"With each pattern, small piecework is standardized into a larger chunk or unit. Patterns become the building blocks for design and construction. Finding and applying patterns indicates progress in a field of human endeavor." (Peter Coad, "Object-oriented patterns", 1992)

"Standards make it easier to reuse ideas and components, recruit people with relevant experience, encapsulate good ideas, and wire components together. However, the process of creating standards can sometimes take too long for industry to wait, and some standards lose touch with the real needs of the adopters they are intended to serve." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)

"Coding standards are rules, sometimes relatively arbitrary, that define the coding styles and conventions that are considered acceptable within a team or organization. In many cases, agreeing on a set of standards, and applying them, is more important than the standards themselves." (John F Smart, "Jenkins: The Definitive Guide", 2011)

"In many applications, integration or functional tests are used by default as the standard way to test almost all aspects of the system. However integration and functional tests are not the best way to detect and identify bugs. Because of the large number of components involved in a typical end-to-end test, it can be very hard to know where something has gone wrong. In addition, with so many moving parts, it is extremely difficult, if not completely unfeasible, to cover all of the possible paths through the application." (John F Smart, "Jenkins: The Definitive Guide", 2011)