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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.
It counts the ears in an ear decomposition of the graph, forms the basis of parameterized complexity on almost-trees, and has been applied in software metrics as part of the definition of cyclomatic complexity of a piece of code. Under the name of cyclomatic number, the concept was introduced by Gustav Kirchhoff. [2] [3]
From the latter definition (of Jorgensen) we can conclude the following: Every node on a flow graph of a program belongs to one DD-path. If the first node on a DD-path is traversed, then all other nodes on that path will also be traversed. The DD path graph is used to find independent path for testing.
In algorithmic information theory, the Kolmogorov complexity (also called descriptive complexity, algorithmic complexity or algorithmic entropy) of a string is the length of the shortest binary program that outputs that string. Minimum message length is a practical application of this approach. Different kinds of Kolmogorov complexity are ...
Essential complexity is a numerical measure defined by Thomas J. McCabe, Sr., in his highly cited, 1976 paper better known for introducing cyclomatic complexity.McCabe defined essential complexity as the cyclomatic complexity of the reduced CFG (control-flow graph) after iteratively replacing (reducing) all structured programming control structures, i.e. those having a single entry point and a ...
In software engineering and development, a software metric is a standard of measure of a degree to which a software system or process possesses some property. [1] [2] Even if a metric is not a measurement (metrics are functions, while measurements are the numbers obtained by the application of metrics), often the two terms are used as synonyms.
Polyspace is a static code analysis tool for large-scale analysis by abstract interpretation to detect, or prove the absence of, certain run-time errors in source code for the C, C++, and Ada programming languages.
Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, M ( n ) {\displaystyle M(n)} below stands in for the complexity of the chosen multiplication algorithm.