Journal
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
Volume 27, Issue 1, Pages 1-12Publisher
IEEE COMPUTER SOC
DOI: 10.1109/32.895984
Keywords
software maintenance; metrics; statistical analysis; fault potential; span of changes; effort modeling
Ask authors/readers for more resources
A central feature of the evolution of large software systems is that change-which is necessary to add new functionality, accommodate new hardware, and repair faults-becomes increasingly difficult over time. In this paper, we approach this phenomenon, which we term code decay, scientifically and statistically. We define code decay and propose a number of measurements (code decay indices) on software and on the organizations that produce it, that serve as symptoms, risk factors, and predictors of decay. Using an unusually rich data set (the fifteen-plus year change history of the millions of lines of software for a telephone switching system), we find mixed, but on the whole persuasive, statistical evidence of code decay, which is corroborated by developers of the code. Suggestive indications that perfective maintenance can retard code decay are also discussed.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available