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Domain-specific tailoring of code smells: An empirical study

: Guo, Y.; Seaman, C.; Zazworka, N.; Shull, F.


Association for Computing Machinery -ACM-; IEEE Computer Society:
ACM/IEEE 32nd International Conference on Software Engineering, ICSE 2010. Vol.2 : Cape Town, South Africa, 2 - 8 May 2010
Piscataway/NJ: IEEE, 2010
ISBN: 978-1-60558-719-6
International Conference on Software Engineering (ICSE) <32, 2010, Cape Town>
Fraunhofer CESE ()

Code smells refer to commonly occurring patterns in source code that indicate poor programming practices or code decay. Detecting code smells helps developers find design problems that can cause trouble in future maintenance. Detection rules for code smells, based on software metrics, have been proposed, but they do not take domain-specific characteristics into consideration. In this study we investigate whether such generic heuristics can be tailored to include domain-specific factors. Input into these domain-specific heuristics comes from an iterative empirical field study in a software maintenance project. The results yield valuable insight into code smell detection.