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Significance of Software Metrics to Quantify Design and Code Quality

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 9 - Article 7
Year of Publication: 2010
S.Arun Kumar
T.Arun Kumar

S.Arun Kumar, T.Arun Kumar and P.Swarnalatha. Article:Significance of Software Metrics to Quantify Design and Code Quality. International Journal of Computer Applications 11(9):36–42, December 2010. Published By Foundation of Computer Science. BibTeX

	author = {S.Arun Kumar and T.Arun Kumar and P.Swarnalatha},
	title = {Article:Significance of Software Metrics to Quantify Design and Code Quality},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {11},
	number = {9},
	pages = {36--42},
	month = {December},
	note = {Published By Foundation of Computer Science}


The vital role of software process improvement is ability to measure the current state of system process and establishing improvement priorities. In addition, the focus on process improvement has increased the demand for software measures, or metrics with which to manage the software process. The need for such metrics is particularly acute when an organization is adopting new technologies and establishing best practices for the organization. This paper mainly addresses the needs of development and implementation of a new suite of metrics for OO design. Metrics developed based on literature survey, while contributing the software development processes, having serious criticisms, which includes the lack of a theoretical base this suggests that software metrics need to be constructed with a stronger degree of theoretical and mathematical rigor. Given the extant software metrics literature, this paper has a three fold agenda: 1) To propose metrics that are constructed with a firm basis in theoretical concepts in measurement and the ontology of objects, and which incorporate the experiences of professional software developers; 2) Evaluate the proposed metrics against established criteria for validity 3) Present empirical data from commercial projects to illustrate the characteristics of these metrics on real applications, and suggest ways in which these metrics may be used.


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