DocumentCode :
1237703
Title :
Identifying Error-Prone Software—An Empirical Study
Author :
Shen, Vincent Y. ; Yu, Tze-jie ; Thebaut, Stephen M. ; Paulsen, Lorri R.
Author_Institution :
Department of Computer Sciences, Purdue University
Issue :
4
fYear :
1985
fDate :
4/1/1985 12:00:00 AM
Firstpage :
317
Lastpage :
324
Abstract :
A major portion of the effort expended in developing commercial software today is associated with program testing. Schedule and/ or resource constraints frequently require that testing be conducted so as to uncover the greatest number of errors possible in the time allowed. In this paper we describe a study undertaken to assess the potential usefulness of various product-and process-related measures in identifying error-prone software. Our goal was to establish an empirical basis for the efficient utilization of limited testing resources using objective, measurable criteria. Through a detailed analysis of three software products and their error discovery histories, we have found simple metrics related to the amount of data and the structural complexity of programs to be of value for this purpose.
Keywords :
Defect density; error-prone modules; probability of errors; program testing; software errors; software metrics; Costs; Error correction; History; Laboratories; Performance evaluation; Software measurement; Software metrics; Software systems; Software testing; System testing; Defect density; error-prone modules; probability of errors; program testing; software errors; software metrics;
fLanguage :
English
Journal_Title :
Software Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-5589
Type :
jour
DOI :
10.1109/TSE.1985.232222
Filename :
1702015
Link To Document :
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