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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.
Robert E. Park (while at the Software Engineering Institute) and others developed a framework for defining SLOC values, to enable people to carefully explain and define the SLOC measure used in a project. For example, most software systems reuse code, and determining which (if any) reused code to include is important when reporting a measure.
Halstead's goal was to identify measurable properties of software, and the relations between them. This is similar to the identification of measurable properties of matter (like the volume, mass, and pressure of a gas) and the relationships between them (analogous to the gas equation). Thus his metrics are actually not just complexity metrics.
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 software engineering, coupling is the degree of interdependence between software modules, a measure of how closely connected two routines or modules are, [1] and the strength of the relationships between modules. [2] Coupling is not binary but multi-dimensional. [3] Coupling and cohesion. Coupling is usually contrasted with cohesion.
Some of the more commonly used metrics are McCabe's cyclomatic complexity metric; Halstead's software science metrics; Henry and Kafura introduced "Software Structure Metrics Based on Information Flow" in 1981, [3] which measures complexity as a function of "fan-in" and "fan-out". They define fan-in of a procedure as the number of local flows ...
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 ...
GQM defines a measurement model on three levels: [7]. 1. Conceptual level (Goal) A goal is defined for an object, for a variety of reasons, with respect to various models of quality, from various points of view and relative to a particular environment.