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Evaluating and comparing software metrics in the software engineering laboratory

Published: 01 January 1981 Publication History

Abstract

There has appeared in the literature a great number of metrics that attempt to measure the effort or complexity in developing and understanding software(1). There have also been several attempts to independently validate these measures on data from different organizations gathered by different people(2). These metrics have many purposes. They can be used to evaluate the software development process or the software product. They can be used to estimate the cost and quality of the product. They can also be used during development and evolution of the software to monitor the stability and quality of the product.
Among the most popular metrics have been the software science metrics of Halstead, and the cyclomatic complexity metric of McCabe. One question is whether these metrics actually measure such things as effort and complexity. One measure of effort may be the time required to produce a product. One measure of complexity might be the number of errors made during the development of a product. A second question is how these metrics compare with standard size measures, such as the number of source lines or the number of executable statements, i.e., do they do a better job of predicting the effort or the number of errors? Lastly, how do these metrics relate to each other?

References

[1]
Halstead, M., Elements of Software Science, Elsevier North-Holland, New York, 1977.
[2]
McCabe, T.J., "A Complexity Measure," IEEE Transactions on Software Engineering, 1976, 2, 308-320.
[3]
Gaffney, John, "Program Control Complexity"; Proceedings of the "Workshop on Quantitative Software Models for Reliability, Complexity, and Cost, IEEE Computer Society, Oct. 1979.
[4]
Chen, E.T., "Program Complexity and Programmer Productivity," IEEE Transactions on Software Engineering, May 1978, Vol. SE-4, No. 3, pp. 187-194.
[5]
Curtis, Sheppard, & Milliman, "Third Time Charm: Stronger Prediction of Programmer Performance by Software Complexity Metrics," Proceedings of the Fourth International Conference on Software Engineering, 1979, pp. 356-360.
[6]
Feuer and Fowlkes, "Some Results from an Empirical Study of Computer Software," Proceedings of the Fourth International Conference on Software Engineering, 1979, pp. 351-355.
[7]
Basili, V., "Tutorial on Models and Metrics for Software Management and Engineering," IEEE Computer Society, IEEE Catalog No. EHO-167-7, 1980.
[8]
Basili and Zelkowitz, "Analyzing Medium Scale Software Developments," Third International Conference on Software Engineering, Atlanta, Georgia, May 1978.
[9]
O'Neil, E., "The Static Source Code Analyzer's Users Guide," CSC TM-78/ 6045, 1978.

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  • (2005)Complexity metrics for manufacturing control architectures based on software and information flowComputers and Industrial Engineering10.1016/j.cie.2005.01.00549:1(1-20)Online publication date: 1-Aug-2005
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Information

Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 10, Issue 1
Spring 1981
191 pages
ISSN:0163-5999
DOI:10.1145/1010627
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Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 1981
Published in SIGMETRICS Volume 10, Issue 1

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  • (2014)Climate modelsProceedings of the 2nd International workshop on Software Engineering for High Performance Computing in Computational Science and Engineering10.1109/SE-HPCCSE.2014.7(6-12)Online publication date: 16-Nov-2014
  • (2006)The evaluation of software systems' structure using quantitative software metricsSoftware: Practice and Experience10.1002/spe.438014060614:6(561-573)Online publication date: 30-Oct-2006
  • (2005)Complexity metrics for manufacturing control architectures based on software and information flowComputers and Industrial Engineering10.1016/j.cie.2005.01.00549:1(1-20)Online publication date: 1-Aug-2005
  • (2004)Software size prediction before codingACM SIGSOFT Software Engineering Notes10.1145/1022494.102251429:5(1-4)Online publication date: 1-Sep-2004
  • (1994)Measuring the complexity of rule-based expert systemsExpert Systems with Applications10.1016/0957-4174(94)90072-87:4(467-481)Online publication date: Oct-1994
  • (1994)A critique of three metricsJournal of Systems and Software10.1016/0164-1212(94)90011-626:3(197-210)Online publication date: Sep-1994
  • (1991)The use of software complexity metrics in software reliability modelingProceedings. 1991 International Symposium on Software Reliability Engineering10.1109/ISSRE.1991.145346(2-11)Online publication date: 1991
  • (1991)Rigor in software complexity measurement experimentationJournal of Systems and Software10.1016/0164-1212(91)90008-T16:2(141-149)Online publication date: 1-Sep-1991
  • (1990)A Predicitive Model for Programming Time: A Factor Analytic ApproachIFAC Proceedings Volumes10.1016/S1474-6670(17)52209-023:5(51-56)Online publication date: Oct-1990
  • (1990)Applications of a relative complexity metric for software project managementJournal of Systems and Software10.1016/0164-1212(90)90051-M12:3(283-291)Online publication date: 1-Jul-1990
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