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Bang measure – Defines a function metric based on twelve primitive (simple) counts that affect or show Bang, defined as "the measure of true function to be delivered as perceived by the user." Bang measure may be helpful in evaluating a software unit's value in terms of how much useful function it provides, although there is little evidence ...
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.
This is a method for analysis and measurement of information processing applications based on end user functional view of the system. The MK II Method (ISO/IEC 20968 Software engineering—Mk II Function Point Analysis—Counting Practices Manual [1]) is one of five currently recognized ISO standards for Functionally sizing software.
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.
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.
The original research detailing this correlation is in CrossTalk The Journal of Defense Software Engineering, as the paper “A New Software Metric to Complement Function Points The Software Non-functional Assessment Process (SNAP).” [5]
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 ...
One method of software measurement is metrics that are analyzed against the code itself. These are called software metrics and including simple metrics, such as counting the number of lines in a single file, the number of files in an application, the number of functions in a file, etc.