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25 December 2007
🏗️Software Engineering: Documentation (Just the Quotes)
🏗️Software Engineering: Object-Oriented Programming [OOP] (Just the Quotes)
🏗️Software Engineering: Code (Just the Quotes)
"A clean design is more easily modified as requirements change or as more is learned about what parts of the code consume significant amounts of execution time. A 'clever' design that fails to work or to run fast enough can often be salvaged only at great cost. Efficiency does not have to be sacrificed in the interest of writing readable code - rather, writing readable code is often the only way to ensure efficient programs that are also easy to maintain and modify." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"Choosing a better data structure is often an art, which we cannot teach. Often you must write a preliminary draft of the code before you can determine what changes in the data structure will help simplify control. [...] Choose a data representation that makes the program simple." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"Don't comment bad code - rewrite it." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"Don't just echo the code with comments make every comment count." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"Jumping around unnecessarily in a computer program has proved to be a fruitful source of errors, and usually indicates that the programmer is not entirely in control of the code." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"Make sure comments and code agree." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"The best documentation for a computer program is a clean structure. It also helps if the code is well formatted, with good mnemonic identifiers and labels" (if any are needed), and a smattering of enlightening comments. Flowcharts and program descriptions are of secondary importance; the only reliable documentation of a computer program is the code itself. The reason is simple -whenever there are multiple representations of a program, the chance for discrepancy exists. If the code is in error, artistic flowcharts and detailed comments are to no avail. Only by reading the code can the programmer know for sure what the program does." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"The fundamental problem with software maintenance is that fixing a defect has a substantial (20-50 percent) chance of introducing another. So the whole process is two steps forward and one step back. Why aren't defects fixed more cleanly? First, even a subtle defect shows itself as a local failure of some kind. In fact it often has system-wide ramifications, usually nonobvious. Any attempt to fix it with minimum effort will repair the local and obvious, but unless the structure is pure or the documentation very fine, the far-reaching effects of the repair will be overlooked. Second, the repairer is usually not the man who wrote the code, and often he is a junior programmer or trainee." (Frederick P. Brooks, The Mythical Man-Month" , 1975)
"Elements (lines of code) in a coincidentally-cohesive module have no relationship. Typically occurs as the result of modularizing existing code, to separate out redundant code." (Edward Yourdon & Larry L Constantine, "Structured Design: Fundamentals of a discipline of computer program and systems design", 1978)
"The major distinguishing feature of the spiral model is that it creates a risk-driven approach to the software process rather than a primarily document-driven or code-driven process. It incorporates many of the strengths of other models and resolves many of their difficulties." (Barry Boehm, "A spiral model of software development and enhancement", IEEE, 1988)
"Code migrates to data. Because of this law there is increasing awareness that bugs in code are only half the battle and that data problems should be given equal attention."" (Boris Beizer, "Software Testing Techniques", 1990)
"More than the act of testing, the act of designing tests is one of the best bug preventers known. The thinking that must be done to create a useful test can discover and eliminate bugs before they are coded - indeed, test-design thinking can discover and eliminate bugs at every stage in the creation of software, from conception to specification, to design, coding and the rest."" (Boris Beizer, "Software Testing Techniques", 1990)
"Third law: Code migrates to data. Because of this law there is increasing awareness that bugs in code are only half the battle and that data problems should be given equal attention."" (Boris Beizer, "Software Testing Techniques", 1990)
"Shipping first time code is like going into debt. A little debt speeds development so long as it is paid back promptly with a rewrite [...] The danger occurs when the debt is not repaid. Every minute spent on not-quite-right code counts as interest on that debt." (Ward Cunningham, "The WyCash Portfolio Management System", OOPSLA, 1992)
"From time to time, a complex algorithm will lead to a longer routine, and in those circumstances, the routine should be allowed to grow organically up to 100-200 lines." (A line is a noncomment, nonblank line of source code.) Decades of evidence say that routines of such length are no more error prone than shorter routines. Let issues such as the routine's cohesion, depth of nesting, number of variables, number of decision points, number of comments needed to explain the routine, and other complexity-related considerations dictate the length of the routine rather than imposing a length restriction per se." (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)
"Inheritance is the idea that one class is a specialization of another class. The purpose of inheritance is to create simpler code by defining a base class that specifies common elements of two or more derived classes. The common elements can be routine interfaces, implementations, data members, or data types. Inheritance helps avoid the need to repeat code and data in multiple locations by centralizing it within a base class. When you decide to use inheritance, you have to make several decisions: For each member routine, will the routine be visible to derived classes? Will it have a default implementation? Will the default implementation be overridable? For each data member" (including variables, named constants, enumerations, and so on), will the data member be visible to derived classes?" (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)
"Modularity's goal is to make each routine or class like a 'black box': You know what goes in, and you know what comes out, but you don't know what happens inside." (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)
"The source code is often the only accurate description of the software. On many projects, the only documentation available to programmers is the code itself. Requirements specifications and design documents can go out of date, but the source code is always up to date. Consequently, it's imperative that the code be of the highest possible quality." (Steve C McConnell," Code Complete: A Practical Handbook of Software Construction", 1993)
"The real value of tests is not that they detect bugs in the code, but that they detect inadequacies in the methods, concentration, and skills of those who design and produce the code." (Charles A R Hoare, "How Did Software Get So Reliable Without Proof?", Lecture Notes in Computer Science Vol. 1051, 1996)
"Any fool can write code that a computer can understand. Good programmers write code that humans can understand." (Martin Fowler, "Refactoring: Improving the Design of Existing Code", 1999)
"Bug tracking will allow you to uncover 'smells' in code" (to use a refactoring phrase). If there are a large number of problems in a particular segment of your project then you may want to really focus on that segment and stabilize it. How do you identify this clustering unless you keep track of the errors.(Ken Beck, 1999)
"Treating your users as co-developers is your least-hassle route to rapid code improvement and effective debugging." (Eric S Raymond, "The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary", 1999)
"When you feel the need to write a comment, first try to refactor the code so that any comment becomes superfluous." (Kent Beck, "Refactoring: Improving the Design of Existing Code", 1999)
"When you find you have to add a feature to a program, and the program's code is not structured in a convenient way to add the feature, first refactor the program to make it easy to add the feature, then add the feature."" (Kent Beck, "Refactoring: Improving the Design of Existing Code", 1999)
"Bugs are things that creep into your software against your will. Every defect in your code was put there by one of the programmers. Two of the programmers, with pair programming. With the customers we visit, when something goes wrong, they think it's a defect." (Ron Jeffries, "Extreme Programming Installed", 2001)
"Do build perfectly for today. Do the simple thing that solves today's problem, but do it well. Keep the code of high quality, just perfect for today's needs." (Ron Jeffries, "Extreme Programming Installed", 2001)
"Smart data structures and dumb code works a lot better than the other way around." (Eric S Raymond, "The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary", 2001)
"XP isn't slash and burn programming, not code and fix, not at all. Extreme Programming is about careful and continuous design, rapid feedback from extensive testing, and the maintenance of relentlessly clear and high-quality code." (Ron Jeffries, "Extreme Programming Installed, 2001)
"Refactoring is the process of changing a software system in such a way that it does not alter the external behavior of the code yet improves its internal structure. It is a disciplined way to clean up code that minimizes the chances of introducing bugs. In essence when you refactor you are improving the design of the code after it has been written." (Martin Fowler et al, "Refactoring: Improving the Design of Existing Code", 2002)
"Without refactoring, the design of the program will decay. As people change code - changes to realize short-term goals or changes made without a full comprehension of the design of the code - the code loses its structure. It becomes harder to see the design by reading the code. Refactoring is rather like tidying up the code. Work is done to remove bits that aren't really in the right place. Loss of the structure of code has a cumulative effect. The harder it is to see the design in the code, the harder it is to preserve it, and the more rapidly it decays. Regular refactoring helps code retain its shape." (Martin Fowler et al, "Refactoring: Improving the Design of Existing Code", 2002)
"All OO languages show some tendency to suck programmers into the trap of excessive layering. Object frameworks and object browsers are not a substitute for good design or documentation, but they often get treated as one. Too many layers destroy transparency: It becomes too difficult to see down through them and mentally model what the code is actually doing. The Rules of Simplicity, Clarity, and Transparency get violated wholesale, and the result is code full of obscure bugs and continuing maintenance problems." (Eric S Raymond, "The Art of Unix Programming", 2003)
"But code as a design document does have its limits. It can overwhelm the reader with detail. Although its behavior is unambiguous, that doesn't mean it is obvious. And the meaning behind a behavior can be hard to convey. [...] A document shouldn't try to do what the code already does well. The code already supplies the detail. It is an exact specification of program behavior. Other documents need to illuminate meaning, to give insight into large-scale structures, and to focus attention on core elements. Documents can clarify design intent when the programming language does not support a straightforward implementation of a concept. Written documents should complement the code and the talking." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"If the architecture isolates the domain-related code in a way that allows a cohesive domain design loosely coupled to the rest of the system, then that architecture can probably support domain-driven DESIGN." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"Models come in many varieties and serve many roles, even those restricted to the context of a software development project. Domain-driven design calls for a model that doesn't just aid early analysis but is the very foundation of the design [...] Tightly relating the code to an underlying model gives the code meaning and makes the model relevant." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"The effectiveness of an overall design is very sensitive to the quality and consistency of fine-grained design and implementation decisions. With a MODEL-DRIVEN DESIGN, a portion of the code is an expression of the model; changing that code changes the model. Programmers are modelers, whether anyone likes it or not. So it is better to set up the project so that the programmers do good modeling work." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"Good code is its own best documentation." (Steve McConnell, "Code Complete", 2004)
"On small, informal projects, a lot of design is done while the programmer sits at the keyboard. 'Design' might be just writing a class interface in pseudocode before writing the details. It might be drawing diagrams of a few class relationships before coding them. It might be asking another programmer which design pattern seems like a better choice. Regardless of how it's done, small projects benefit from careful design just as larger projects do, and recognizing design as an explicit activity maximizes the benefit you will receive from it." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)
"A commitment to simplicity of design means addressing the essence of design - the abstractions on which software is built - explicitly and up front. Abstractions are articulated, explained, reviewed and examined deeply, in isolation from the details of the implementation. This doesn't imply a waterfall process, in which all design and specification precedes all coding. But developers who have experienced the benefits of this separation of concerns are reluctant to rush to code, because they know that an hour spent on designing abstractions can save days of refactoring." (Daniel Jackson, "Software Abstractions", 2006)
"In fact, I'm a huge proponent of designing your code around the data, rather than the other way around, and I think it's one of the reasons git has been fairly successful. [...] I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships." (Linus Torvalds, [email] 2006)
"The picture of digital progress that so many ardent boosters paint ignores the painful record of actual programmers' epic struggles to bend brittle code into functional shape. That record is of one disaster after another, marking the field's historical time line like craters. Anyone contemplating the start of a big software development project today has to contend with this unfathomably discouraging burden of experience. It mocks any newcomer with ambitious plans, as if to say, What makes you think you're any different?" (Scott Rosenberg, "Dreaming in Code", 2007)
"There is almost always something you can pull off the shelf that will satisfy many of your needs. But usually the parts of what you need done that your off-the-shelf code won���t handle are the very parts that make your new project different, unique, innovative - and they're why you're building it in the first place." (Scott Rosenberg, "Dreaming in Code", 2007)
"To programmers, refactoring means rewriting a chunk of code to make it briefer, clearer, and easier to read without changing what it actually does. Refactoring is often compared to gardening; it is never finished." (Scott Rosenberg, "Dreaming in Code", 2007)
"Well-commented code is one hallmark of good programming practice; it shows that you care about what you're doing, and it is considerate to those who will come after you to fix your bugs. But comments also serve as a kind of back channel for programmer-to-programmer communication and even occasionally as a competitive arena or an outlet for silliness." (Scott Rosenberg, "Dreaming in Code", 2007)
"Clearly, the search for a dividing line between code and data is fruitlesand not particularly flattering to our egos. Let's abandon any attempt to find a higher truth here, and settle for a pragmatic definition. If a piece of generated text simply instantiates and provides values for a data structure, it's data; otherwise, it's code." (Steven Kelly & Juha-Pekka Tolvanen, "Domain-specific Modeling", 2008)
"Good software designs accommodate change without huge investments and rework. When we use code that is out of our control, special care must be taken to protect our investment and make sure future change is not too costly." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"If the discipline of requirements specification has taught us anything, it is that well-specified requirements are as formal as code and can act as executable tests of that code!"" (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"In an ideal system, we incorporate new features by extending the system, not by making modifications to existing code." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"It is a myth that we can get systems 'right the first time'. Instead, we should implement only today's stories, then refactor and expand the system to implement new stories tomorrow. This is the essence of iterative and incremental agility. Test-driven development, refactoring, and the clean code they produce make this work at the code level." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"It is not enough for code to work. Code that works is often badly broken. Programmers who satisfy themselves with merely working code are behaving unprofessionally. They may fear that they don't have time to improve the structure and design of their code, but I disagree. Nothing has a more profound and long-term degrading effect upon a development project than bad code." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"It is unit tests that keep our code flexible, maintainable, and reusable. The reason is simple. If you have tests, you do not fear making changes to the code! Without tests every change is a possible bug."" (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"Nothing has a more profound and long-term degrading effect upon a development project than bad code. Bad schedules can be redone, bad requirements can be redefined. Bad team dynamics can be repaired. But bad code rots and ferments, becoming an inexorable weight that drags the team down." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"The majority of the cost of a software project is in long-term maintenance. In order to minimize the potential for defects as we introduce change, it's critical for us to be able to understand what a system does. As systems become more complex, they take more and more time for a developer to understand, and there is an ever greater opportunity for a misunderstanding. Therefore, code should clearly express the intent of its author. The clearer the author can make the code, the less time others will have to spend understanding it. This will reduce defects and shrink the cost of maintenance." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"You should choose a set of simple rules that govern the format of your code, and then you should consistently apply those rules. If you are working on a team, then the team should agree to a single set of formatting rules and all members should comply." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"But remember that refactoring should never be combined with modifying the functionality of the code, and that very definitely includes fixing bugs." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)
"Every piece of code is built upon a platform of myriad assumptions - things that have to be true for it to behave as expected. More often than not, bugs arise because one or more of these assumptions are violated or turn out to be mistaken." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)
"Refactoring is the process of improving the design of existing code without changing its behavior. [...] Bug fixing often uncovers opportunities for refactoring. The very fact that you're working with code that contains a bug indicates that there is a chance that it could be clearer or better structured." (Paul Butcher, "Debug It! Find, Repair, and Prevent Bugs in Your Code", 2009)
"Although it is focused on the code, refactoring has a large impact on the design of a system. It is vital for senior designers and architects to understand the principles of refactoring and to use them in their projects." (Jay Fields et al, "Refactoring: Ruby Edition", 2010)
"Treat your code like any other composition, such as a poem, an essay, a public blog, or an important email. Craft what you express carefully, so that it does what it should and communicates as directly as possible what it is doing; so that it still communicates your intention when you are no longer around. Remember that useful code is used much longer than ever intended." (Peter Sommerlad, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])
"Few would deny the importance of writing quality code. High quality code contains less bugs, and is easier to understand and easier to maintain. However, the precise definitions of code quality can be more subjective, varying between organizations, teams, and even individuals within a team." (John F Smart, "Jenkins: The Definitive Guide", 2011)
"One of the worst symptoms of a dysfunctional team is when each programmer builds a wall around his code and refuses to let other programmers touch it." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)
"Programming is an act of creation. When we write code we are creating something out of nothing. We are boldly imposing order upon chaos. We are confidently commanding, in precise detail, the behaviors of a machine that could otherwise do incalculable damage. And so, programming is an act of supreme arrogance." (Robert C Martin, "The Clean Coder: A code of conduct for professional programmers", 2011)
"The fact that bugs will certainly occur in your code does not mean you aren't responsible for them. The fact that the task to write perfect software is virtually impossible does not mean you aren't responsible for the imperfection." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)
"The true professional knows that delivering function at the expense of structure is a fool's errand. It is the structure of your code that allows it to be flexible. If you compromise the structure, you compromise the future." (Robert C Martin,"The Clean Coder: A code of conduct for professional programmers", 2011)
"A lack of focus on a shared language and knowledge of the problem domain results in a codebase that works but does not reveal the intent of the business. This makes codebases difficult to read and maintain because translations between the analysis model and the code model can be costly and error prone." (Scott Millett, "Patterns Principles and Practices of Domain Driven Design", 2015)
"Areas of low complexity or that are unlikely to be invested in can be built without the need for perfect code quality; working software is good enough. Sometimes feedback and first-to-market are core to the success of a product; in this instance, it can make business sense to get working software up as soon as possible, whatever the architecture." (Scott Millett, "Patterns Principles and Practices of Domain Driven Design", 2015)
"But like many other aspects of code quality, building an abstraction for a problem comes with tradeoffs. Building a generalized solution takes more time than building one specific to a given problem. To break even, the time saved by the abstraction for future engineers needs to outweigh the time invested." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)
"Development is a design process. Design processes are generally evaluated by the value they deliver rather than a conformance to plan. Therefore, it makes sense to move away from plan-driven projects and toward value-driven projects. [...] The realization that the source code is part of the design, not the product, fundamentally rewires our understanding of software." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)
"It's wishful thinking to believe that all the code we write will be bug-free and work the first time. In actuality, much of our engineering time is spent either debugging issues or validating that what we're building behaves as expected. The sooner we internalize this reality, the sooner we will start to consciously invest in our iteration speed in debugging and validation loops." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)
"Sometimes, we build things in a way that makes sense in the short-term but that can be costly in the long-term. We work around design guidelines because it's faster and easier than following them. We punt on writing test cases for a new feature because there' too much work to finish before the deadline. We copy, paste, and tweak small chunks of existing code instead of refactoring it to support our use cases. Each of these tradeoffs, whether they're made from laziness or out of a conscious decision to ship sooner, can increase the amount of technical debt in our codebase." (Edmond Lau, "The Effective Engineer: How to Leverage Your Efforts In Software Engineering to Make a Disproportionate and Meaningful Impact", 2015)
"The fact that software engineering is not like other forms of engineering should really come as no surprise. Medicine is not like the law. Carpentry is not like baking. Software development is like one thing, and one thing only: software development. We need practices that make what we do more efficient, more verifiable, and easier to change. If we can do this, we can slash the short-term cost of building software, and all but eliminate the crippling long-term cost of maintaining it." (David S Bernstein, "Beyond Legacy Code", 2015)
"When we talk about software architecture, software is recursive and fractal in nature, etched and sketched in code. Everything is details. Interlocking levels of detail also contribute to a building's architecture, but it doesn't make sense to talk about physical scale in software. Software has structure - many structures and many kinds of structures-but its variety eclipses the range of physical structure found in buildings. You can even argue quite convincingly that there is more design activity and focus in software than in building architecture - in this sense, it's not unreasonable to consider software architecture more architectural than building architecture!" (Robert C Martin, "Clean Architecture: A Craftsman's Guide to Software Structure and Design", 2017)
"It is not loyalty or internal motivation that drives us programmers forward. We must write our code when the road to our personal success is absolutely clear for us and writing high quality code obviously helps us move forward on this road. To make this happen, the management has to define the rules of the game, also known as process", and make sure they are strictly enforced, which is much more difficult than 'being agile'."" (Yegor Bugayenko, "Code Ahead", 2018)
"Trying to determine the cognitive load of software using simple measures such as lines of code, number of modules, classes, or methods is misguided. [...] When measuring cognitive load, what we really care about is the domain complexity - how complex is the problem that we're trying to solve with software? A domain is a more largely applicable concept than software size." (Matthew Skelton, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)
"A boat without a captain is nothing more than a floating waiting room: unless someone grabs the rudder and starts the engine, it's just going to drift along aimlessly with the current. A piece of software is just like that boat: if no one pilots it, you're left with a group of engineers burning up valuable time, just sitting around waiting for something to happen" (or worse, still writing code that you don't need)." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)
"Code coverage can provide some insight into untested code, but it is not a substitute for thinking critically about how well your system is tested." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)
"People are inherently imperfect - we like to say that humans are mostly a collection of intermittent bugs. But before you can understand the bugs in your coworkers, you need to understand the bugs in yourself. We're going to ask you to think about your own reactions, behaviors, and attitudes - and in return, we hope you gain some real insight into how to become a more efficient and successful software engineer who spends less energy dealing with people-related problems and more time writing great code." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)
"Programming is the immediate act of producing code. Software engineering is the set of policies, practices, and tools that are necessary to make that code useful for as long as it needs to be used and allowing collaboration across a team." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)
"When program developers are not territorial about their code and encourage others to look for bugs and potential improvements, progress speeds up dramatically." (Gerald Weinberg)
24 December 2007
🏗️Software Engineering: Design (Just the Quotes)
"If a project has not achieved a system architecture, including its rationale, the project should not proceed to full-scale system development. Specifying the architecture as a deliverable enables its use throughout the development and maintenance process." (Barry Boehm, 1995)
"If the architecture isolates the domain-related code in a way that allows a cohesive domain design loosely coupled to the rest of the system, then that architecture can probably support domain-driven DESIGN." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"If the design, or some central part of it, does not map to the domain model, that model is of little value, and the correctness of the software is suspect. At the same time, complex mappings between models and design functions are difficult to understand and, in practice, impossible to maintain as the design changes. A deadly divide opens between analysis and design so that insight gained in each of those activities does not feed into the other." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"Many things can put a project off course: bureaucracy, unclear objectives, and lack of resources, to name a few. But it is the approach to design that largely determines how complex software can become. When complexity gets out of hand, developers can no longer understand the software well enough to change or extend it easily and safely. On the other hand, a good design can create opportunities to exploit those complex features." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"Models come in many varieties and serve many roles, even those restricted to the context of a software development project. Domain-driven design calls for a model that doesn’t just aid early analysis but is the very foundation of the design […] Tightly relating the code to an underlying model gives the code meaning and makes the model relevant." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"Software design is a constant battle with complexity." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)
"Design patterns provide the cores of ready-made solutions that can be used to solve many of software’s most common problems. Some software problems require solutions that are derived from first principles. But most problems are similar to past problems, and those can be solved using similar solutions, or patterns." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)
"In addition to their complexity-management benefit, design patterns can accelerate design discussions by allowing designers to think and discuss at a larger level of granularity." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)
"On small, informal projects, a lot of design is done while the programmer sits at the keyboard. 'Design' might be just writing a class interface in pseudocode before writing the details. It might be drawing diagrams of a few class relationships before coding them. It might be asking another programmer which design pattern seems like a better choice. Regardless of how it’s done, small projects benefit from careful design just as larger projects do, and recognizing design as an explicit activity maximizes the benefit you will receive from it." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction" 2nd Ed., 2004)
"Software is built on abstractions. Pick the right ones, and programming will flow naturally from design; modules will have small and simple interfaces; and new functionality will more likely fit in without extensive reorganization […] Pick the wrong ones, and programming will be a series of nasty surprises: interfaces will become baroque and clumsy as they are forced to accommodate unanticipated interactions, and even the simplest of changes will be hard to make." (Daniel Jackson, "Software Abstractions", 2006)
"Whether you are designing systems or individual modules, never forget to use the simplest thing that can possibly work." (Robert C Martin, "Clean Code: A Handbook of Agile Software Craftsmanship", 2008)
"We see a lot of feature-driven product design in which the cost of features is not properly accounted. Features can have a negative value to customers because they make the products more difficult to understand and use. We are finding that people like products that just work. It turns out that designs that just work are much harder to produce that designs that assemble long lists of features." (Douglas Crockford, "JavaScript: The Good Parts", 2008)
"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)
"A systems approach is one that focuses on the system as a whole, specifically linking value judgments (what is desired) and design decisions (what is feasible). A true systems approach means that the design process includes the 'problem' as well as the solution. The architect seeks a joint problem–solution pair and understands that the problem statement is not fixed when the architectural process starts. At the most fundamental level, systems are collections of different things that together produce results unachievable by the elements alone." (Mark W Maier, "The Art Systems of Architecting" 3rd Ed., 2009)
"Design has the power to enrich our lives by engaging our emotions through image, form, texture, color, sound, and smell. The intrinsically human-centered nature of design thinking points to the next step: we can use our empathy and understanding of people to design experiences that create opportunities for active engagement and participation."
"How does a smell manifest in design? A smell occurs as a result of a combination of one or more design decisions. In other words, the design ecosystem itself is responsible for the creation of the smell. The presence of the smell in turn impacts the ecosystem in several ways. First, it is likely that the presence of the smell triggers new design decisions that are needed to address the smell! Second, the smell can potentially influence or constrain future design decisions as a result of which one or more new smells may manifest in the ecosystem. Third, smells also tend to have an effect on other smells. For instance, some smells amplify the effects of other smells, or co-occur with or act as precursors to other smells. Clearly, smells share a rich relationship with the ecosystem in which they occur." (Girish Suryanarayana et al, "Refactoring for Software Design Smells: Managing Technical Debt", 2015)
"Technical debt is the debt that accrues when you knowingly or unknowingly make wrong or non-optimal design decisions. [...] when a software developer opts for a quick fix rather than a proper well-designed solution, he introduces technical debt. It is okay if the developer pays back the debt on time. However, if the developer chooses not to pay or forgets about the debt created, the accrued interest on the technical debt piles up, just like financial debt, increasing the overall technical debt. The debt keeps increasing over time with each change to the software; thus, the later the developer pays off the debt, the more expensive it is to pay off. If the debt is not paid at all, then eventually the pile-up becomes so huge that it becomes immensely difficult to change the software. In extreme cases, the accumulated technical debt is so huge that it cannot be paid off anymore and the product has to be abandoned. Such a situation is called technical bankruptcy." (Girish Suryanarayana et al, "Refactoring for Software Design Smells: Managing Technical Debt", 2015)
🏗️Software Engineering: Errors (Just the Quotes)
"Mere deductive logic, whether you clothe it in mathematical symbols and phraseology or whether you enlarge its scope into a more general symbolic technique, can never take the place of clear relevant initial concepts of the meaning of your symbols, and among symbols I include words. If you are dealing with nature, your meanings must directly relate to the immediate facts of observation. We have to analyse first the most general characteristics of things observed, and then the more casual contingent occurrences. There can be no true physical science which looks first to mathematics for the provision of a conceptual model. Such a procedure is to repeat the errors of the logicians of the middle-ages." (Alfred N Whitehead, "Principle of Relativity", 1922)
"Jumping around unnecessarily in a computer program has proved to be a fruitful source of errors, and usually indicates that the programmer is not entirely in control of the code." (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"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)
"Watch out for off-by-one errors. A common cause of off-by-one errors is an incorrect test, for example using greater than" when "greater than or equal to" is actually needed. This program is a binary search routine, which looks for a particular element in a table by halving the interval in which the element might lie, until it ultimately either finds it, or deduces that it isn't present."" (Brian W Kernighan & Phillip J Plauger, "The Elements of Programming Style", 1974)
"A good information system both exposes interface errors and stimulates their correction" (Fred P Brooks, "The Mythical Man-Month: Essays", 1975)
"We try to solve the problem by rushing through the design process so that enough time is left at the end of the project to uncover the errors that were made because we rushed through the design process." (Glenford Myers, "Composite/structured design", 1978)
"The most common kind of coding bug, and often considered the least harmful, are documentation bugs (i.e., erroneous comments). Although many documentation bugs are simple spelling errors or the result of poor writing, many are actual errors - that is, misleading or erroneous comments. We can no longer afford to discount such bugs, because their consequences are as great as 'true' coding errors. Today programming labor is dominated by maintenance. This will increase as software becomes even longer-lived. Documentation bugs lead to incorrect maintenance actions and therefore cause the insertion of other bugs." (Boris Beizer, "Software Testing Techniques", 1990)
"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)
"Testing by itself does not improve software quality. Test results are an indicator of quality, but in and of themselves, they don't improve it. Trying to improve software quality by increasing the amount of testing is like trying to lose weight by weighing yourself more often. What you eat before you step onto the scale determines how much you will weigh, and the software development techniques you use determine how many errors testing will find. If you want to lose weight, don't buy a new scale; change your diet. If you want to improve your software, don't test more; develop better." (Steve C McConnell, "Code Complete: A Practical Handbook of Software Construction", 1993)
"Another curious phenomenon you may meet is in fitting data to a model there are errors in both the data and the model. For example, a normal distribution may be assumed, but the tails may in fact be larger or smaller than the model predicts, and possibly no negative values can occur although the normal distribution allows them. Thus there are two sources of error. As your ability to make more accurate measurements increases the error due to the model becomes an increasing part of the error." (Richard Hamming, "The Art of Doing Science and Engineering: Learning to Learn", 1997)
"Bug tracking will allow you to uncover 'smells' in code" (to use a refactoring phrase). If there are a large number of problems in a particular segment of your project then you may want to really focus on that segment and stabilize it. How do you identify this clustering unless you keep track of the errors." (Ken Beck, 1999)
"Developing fewer features allows you to conserve development resources and spend more time refining those features that users really need. Fewer features mean fewer things to confuse users, less risk of user errors, less description and documentation, and therefore simpler Help content. Removing any one feature automatically increases the usability of the remaining ones." (Jakob Nielsen, "Prioritizing Web Usability", 2006)
"It turns out that strong typing does not eliminate the need for careful testing. And I have found in my work that the sorts of errors that strong type checking finds are no the errors I worry about." (Douglas Crockford, "JavaScript: The Good Parts", 2008)
"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)
"Making interfaces hard to use incorrectly requires two things. First, you must anticipate errors users might make and find ways to prevent them. Second, you must observe how an interface is misused during early release and modify the interface - yes, modify the interface! - to prevent such errors. The best way to prevent incorrect use is to make such use impossible. If users keep wanting to undo an irrevocable action, try to make the action revocable. If they keep passing the wrong value to an API, do your best to modify the API to take the values that users want to pass." (Scott Meyers, [in Kevlin Henney’s "97 Things Every Programmer Should Know", 2010])
"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)
"The random element in most data analysis is assumed to be white noise - normal errors independent of each other. In a time series, the errors are often linked so that independence cannot be assumed" (the last examples). Modeling the nature of this dependence is the key to time series."" (DeWayne R Derryberry, "Basic data analysis for time series with R", 2014)
"Once a model has been fitted to the data, the deviations from the model are the residuals. If the model is appropriate, then the residuals mimic the true errors. Examination of the residuals often provides clues about departures from the modeling assumptions. Lack of fit - if there is curvature in the residuals, plotted versus the fitted values, this suggests there may be whole regions where the model overestimates the data and other whole regions where the model underestimates the data. This would suggest that the current model is too simple relative to some better model." (DeWayne R Derryberry, "Basic data analysis for time series with R", 2014)
"A lack of focus on a shared language and knowledge of the problem domain results in a codebase that works but does not reveal the intent of the business. This makes codebases difficult to read and maintain because translations between the analysis model and the code model can be costly and error prone." (Scott Millett, "Patterns Principles and Practices of Domain Driven Design", 2015)
"Programming in the real world tends to happen on a large scale. The strategy is similar to what one might use to write a book or undertake any other big project: figure out what to do, starting with a broad specification that is broken into smaller and smaller pieces, then work on the pieces separately while making sure that they hang together. In programming, pieces tend to be of a size such that one person can write the precise computational steps in some programming language. Ensuring that the pieces written by different programmers work together is challenging, and failing to get this right is a major source of errors." (Brian W Kernighan, "Understanding the Digital World", 2017)
"Sadly, no substantial program works the first time; life is too complicated and programs reflect that complexity. Programming requires perfect attention to detail, something that few people can achieve. Thus all programs of any size will have errors, that is, they will do the wrong thing or produce the wrong answer under some circumstances. Those flaws are called bugs [...]" (Brian W Kernighan, "Understanding the Digital World", 2017)
23 December 2007
🏗️Software Engineering: Conceptual Models (Just the Quotes)
"Mere deductive logic, whether you clothe it in mathematical symbols and phraseology or whether you enlarge its scope into a more general symbolic technique, can never take the place of clear relevant initial concepts of the meaning of your symbols, and among symbols I include words. If you are dealing with nature, your meanings must directly relate to the immediate facts of observation. We have to analyse first the most general characteristics of things observed, and then the more casual contingent occurrences. There can be no true physical science which looks first to mathematics for the provision of a conceptual model. Such a procedure is to repeat the errors of the logicians of the middle-ages." (Alfred N Whitehead, "Principle of Relativity", 1922)
"Scientists whose work has no clear, practical implications would want to make their decisions considering such things as: the relative worth of (1) more observations, (2) greater scope of his conceptual model, (3) simplicity, (4) precision of language, (5) accuracy of the probability assignment." (C West Churchman, "Costs, Utilities, and Values", 1956)
"Model-making, the imaginative and logical steps which precede the experiment, may be judged the most valuable part of scientific method because skill and insight in these matters are rare. Without them we do not know what experiment to do. But it is the experiment which provides the raw material for scientific theory. Scientific theory cannot be built directly from the conclusions of conceptual models." (Herbert G Andrewartha," Introduction to the Study of Animal Population", 1961)
"As the least conscious layer of the user experience, the conceptual model has the paradoxical quality of also having the most impact on usability. If an appropriate conceptual model is faithfully represented throughout the interface, after users recognize and internalize the model, they will have a fundamental understanding of what the application does and how to operate it." (Bob Baxley, "Making the Web Work: Designing Effective Web Applications", 2002)
"Sometimes, however, a conceptual model is only a first step, and the second step is a mathematical representation of the conceptual model." (Gregory N Derry, "What Science Is and How It Works", 2002)
"A conceptual model is one which reflects reality by placing words which are concepts into the model in the same way that the model aeroplane builder puts wings, a fuselage, and a cockpit together." (Lynn Basford & Oliver Slevin, "Theory and Practice of Nursing: An Integrated Approach to Caring Practice", 2003)
"Sometimes, however, a conceptual model is only a first step, and the second step is a mathematical representation of the conceptual model." (Gregory N Derry, "What Science Is and How It Works", 2002)
"The role of conceptual modelling in information systems development during all these decades is seen as an approach for capturing fuzzy, ill-defined, informal 'real-world' descriptions and user requirements, and then transforming them to formal, in some sense complete, and consistent conceptual specifications." (Janis A Burbenko jr., "From Information Algebra to Enterprise Modelling and Ontologies", Conceptual Modelling in Information Systems Engineering, 2007)
"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)
"The first function of a conceptual model is relating the research to the existing body of literature. With the help of a conceptual model a researcher can indicate in what way he is looking at the phenomenon of his research."(Jan Jonker & Bartjan Pennink, "The Essence of Research Methodology" , 2010)
"Conceptual models are best thought of as design-tools - a way for designers to straighten out and simplify the design and match it to the users’ task-domain, thereby making it clearer to users how they should think about the application. The designers’ responsibility is to devise a conceptual model that seems natural to users based on the users’ familiarity with the task domain. If designers do their job well, the conceptual model will be the basis for users’ mental models of the application." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)
"The conceptual model is not the users’ mental model of the application. […] users of an application form mental models of it to allow them to predict its behavior. A mental model is the user’s high-level understanding of how the application works; it allows the user to predict what the application will do in response to various user-actions. Ideally, a user’s mental model of an application should be similar to the designers’ conceptual model, but in practice the two models may differ significantly. Even if a user’s mental model is the same as the designer’s conceptual model, they are distinct models." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)
"Once we understand our user's mental model, we can capture it in a conceptual model. The conceptual model is a representation of the mental model using elements, relationships, and conditions. Our design and final system will be the tangible result of this conceptual model." (Pau Giner & Pablo Perea, "UX Design for Mobile, 2017)
"A model or conceptual model is a schematic or representation that describes how something works. We create and adapt models all the time without realizing it. Over time, as you gain more information about a problem domain, your model will improve to better match reality." (James Padolsey, "Clean Code in JavaScript", 2020)
About Me

- Adrian
- Koeln, NRW, Germany
- IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.