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[2] [3] It won a Jolt Award in 1993. [4] There are also negative reviews about the length and style of the book, [5] which runs to over 900 pages and goes into detail on many topics. The first edition has been superseded by Code Complete 2. [6] The first editions can be found used and are still relevant for programmers using C, Pascal and GW ...
Chapter 5 studies cyclic codes and Chapter 6 studies a special case of cyclic codes, the quadratic residue codes. Chapter 7 returns to BCH codes. [1] [6] After these discussions of specific codes, the next chapter concerns enumerator polynomials, including the MacWilliams identities, Pless's own power moment identities, and the Gleason ...
This prevents runaway code. Avoid heap memory allocation after initialization. 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.
While code integrity is usually achieved by unit testing the source code to reach high code coverage, it is definitely not the only way, or the best way, to achieve code integrity. In fact, code coverage, a popular metric to measure the thoroughness of unit tests, is known to have a limited correlation with the measure of real code integrity. [2]
Formally, a parity check matrix H of a linear code C is a generator matrix of the dual code, C ⊥. This means that a codeword c is in C if and only if the matrix-vector product Hc ⊤ = 0 (some authors [1] would write this in an equivalent form, cH ⊤ = 0.) The rows of a parity check matrix are the coefficients of the parity check equations. [2]
Code completion is an autocompletion feature in many integrated development environments (IDEs) that speeds up the process of coding applications by fixing common mistakes and suggesting lines of code. This usually happens through popups while typing, querying parameters of functions, and query hints related to syntax errors.
In software engineering, code coverage, also called test coverage, is a percentage measure of the degree to which the source code of a program is executed when a particular test suite is run. A program with high code coverage has more of its source code executed during testing, which suggests it has a lower chance of containing undetected ...
There are many variations of this basic process. A 2017 survey of 240 development teams found that 90% of teams using code review followed a change-based process, with 60% specifically using regular change-based review. [3] Major software corporations including such as Microsoft, [9] Google, [10] and Facebook follow a change-based code review ...