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The code that a programmer writes should be simple. Complicated logic for achieving a simple thing should be kept to a minimum since the code might be modified by another programmer in the future. The logic one programmer implemented may not make perfect sense to another. So, always keep the code as simple as possible. [21]
This category describes rules and aphorisms applicable to software engineering.They range from the highly formal to those open to interpretation, and from serious to humorous.
The Zen of Python is a collection of 19 "guiding principles" for writing computer programs that influence the design of the Python programming language. [1] Python code that aligns with these principles is often referred to as "Pythonic". [2] Software engineer Tim Peters wrote this set of principles and posted it on the Python mailing list in ...
In software programming, SOLID is a mnemonic acronym for five design principles intended to make object-oriented designs more understandable, flexible, and maintainable. Although the SOLID principles apply to any object-oriented design, they can also form a core philosophy for methodologies such as agile development or adaptive software ...
All loops must have fixed bounds. This prevents runaway code. Avoid heap memory allocation. Restrict functions to a single printed page. Use a minimum of two runtime assertions per function. Restrict the scope of data to the smallest possible. Check the return value of all non-void functions, or cast to void to indicate the return value is useless.
Code conventions improve the readability of the software, allowing engineers to understand new code more quickly and thoroughly. If you ship your source code as a product, you need to make sure it is as well packaged and clean as any other product you create.
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
Refactoring is usually motivated by noticing a code smell. [2] For example, the method at hand may be very long, or it may be a near duplicate of another nearby method. Once recognized, such problems can be addressed by refactoring the source code, or transforming it into a new form that behaves the same as before but that no longer "smells".