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Cyclomatic complexity is a software metric used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. It was developed by Thomas J. McCabe, Sr. in 1976. Cyclomatic complexity is computed using the control-flow graph of the program.
In the theoretical analysis of algorithms, the normal practice is to estimate their complexity in the asymptotic sense. The most commonly used notation to describe resource consumption or "complexity" is Donald Knuth 's Big O notation , representing the complexity of an algorithm as a function of the size of the input n {\textstyle n} .
A profiler can be applied to an individual method or at the scale of a module or program, to identify performance bottlenecks by making long-running code obvious. [1] A profiler can be used to understand code from a timing point of view, with the objective of optimizing it to handle various runtime conditions [2] or various loads. [3]
Halstead complexity measures are software metrics introduced by Maurice Howard Halstead in 1977 [1] as part of his treatise on establishing an empirical science of software development. Halstead made the observation that metrics of the software should reflect the implementation or expression of algorithms in different languages, but be ...
Since basic languages such as C, C++, Java, etc. have operations like assignments of variables, function calls and test conditions only, the ABC score has these three components. [ 1 ] If the ABC vector is denoted as 5,11,9 for a subroutine , it means that the subroutine has 5 assignments, 11 branches and 9 conditionals.
Using lines of code to compare a 10,000-line project to a 100,000-line project is far more useful than when comparing a 20,000-line project with a 21,000-line project. While it is debatable exactly how to measure lines of code, discrepancies of an order of magnitude can be clear indicators of software complexity or man-hours.
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.
The Boolean satisfiability problem (SAT) is, given a formula, to check whether it is satisfiable. This decision problem is of central importance in many areas of computer science, including theoretical computer science, complexity theory, [3] [4] algorithmics, cryptography [5] [6] and artificial intelligence. [7] [additional citation(s) needed]