In recent years much attention has been directed toward reducing software cost. To this end, researchers have attempted to find relationships between the characteristics of programs and the difficulty of performing programming tasks The objective has been to develop measures of software complexity t...
In recent years much attention has been directed toward reducing software cost. To this end, researchers have attempted to find relationships between the characteristics of programs and the difficulty of performing programming tasks The objective has been to develop measures of software complexity that can be used for cost projection, manpower allocation, and program and programmer evaluation. Despite the growing body of literature devoted to their development, analysis, and testing, software complexity measures have yet to gain wide acceptance Early claims for the validity of the metrics have not been supported, and considerable criticism has been directed at the methodology of the experiments that support the measures. Nonetheless, new complexity easures continue to appear, and new support for old measures is earnestly sought. Complexity measures offer great potential for containing the galloping cost of software development and maintenance. Successful software-complexity-measure development must be motivated by a theory of programming behavior. An integrated approach to metric development, testing, and use is essential as development should anticipate the demands of the measures usage Testing should be performed with specific applications in mind, and where possible the test environment should simulate the actual use. Complexity measures have been developed without any particular use in mind Lacking a theory of programming behavior, researchers have sought meaningful applications through experimentation The results of these explorations are difficult to interpret and provide only weak support for the use of complexity measures. Until more comprehensive evidence is available, software complexity measures should be used very cautiously. Software complexity measures are believed to provide the most objective and quantitative means of controlling software projects. In this paper, we discuss major properties and weakness of control complexity measures, investigate hybrid measures and structuredness which complement the demerits of single component measures, and analyzes properties of control flow complexity measures and investigate a new complexity metrics using regular expression and S to measures program structuredness. To show the complexity according to the structured of programs, COMl and COM2 are presented
In recent years much attention has been directed toward reducing software cost. To this end, researchers have attempted to find relationships between the characteristics of programs and the difficulty of performing programming tasks The objective has been to develop measures of software complexity that can be used for cost projection, manpower allocation, and program and programmer evaluation. Despite the growing body of literature devoted to their development, analysis, and testing, software complexity measures have yet to gain wide acceptance Early claims for the validity of the metrics have not been supported, and considerable criticism has been directed at the methodology of the experiments that support the measures. Nonetheless, new complexity easures continue to appear, and new support for old measures is earnestly sought. Complexity measures offer great potential for containing the galloping cost of software development and maintenance. Successful software-complexity-measure development must be motivated by a theory of programming behavior. An integrated approach to metric development, testing, and use is essential as development should anticipate the demands of the measures usage Testing should be performed with specific applications in mind, and where possible the test environment should simulate the actual use. Complexity measures have been developed without any particular use in mind Lacking a theory of programming behavior, researchers have sought meaningful applications through experimentation The results of these explorations are difficult to interpret and provide only weak support for the use of complexity measures. Until more comprehensive evidence is available, software complexity measures should be used very cautiously. Software complexity measures are believed to provide the most objective and quantitative means of controlling software projects. In this paper, we discuss major properties and weakness of control complexity measures, investigate hybrid measures and structuredness which complement the demerits of single component measures, and analyzes properties of control flow complexity measures and investigate a new complexity metrics using regular expression and S to measures program structuredness. To show the complexity according to the structured of programs, COMl and COM2 are presented
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