Abstract
In software, source code changes are expected to occur. In order to meet the enormous requirements of the users, source codes are frequently modified. The maintenance task is highly complicated if the changes due to bug repair, enhancement, and addition of new features are not reported carefully. In this paper, concurrent versions system (CVS) repository (http://bugzilla.mozilla.org) is taken into consideration for recording bugs. These observed bugs are collected from some subcomponents of Mozilla open-source software. As entropy is helpful in studying the code change process, and various entropies, namely Shannon, Renyi, and Tsallis entropies, have been evaluated using these observed bugs. By applying simple linear regression (SLR) technique, the bugs which are yet to come in future are predicted based on current year entropy measures and the observed bugs. Performance has been measured using various R2 statistics. In addition to this, ANOVA and Tukey test have been applied to statistically validate various entropy measures.
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Kumar, V., Arora, H.D., Sahni, R. (2019). An Assessment of Some Entropy Measures in Predicting Bugs of Open-Source Software. In: Hoda, M., Chauhan, N., Quadri, S., Srivastava, P. (eds) Software Engineering. Advances in Intelligent Systems and Computing, vol 731. Springer, Singapore. https://doi.org/10.1007/978-981-10-8848-3_58
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DOI: https://doi.org/10.1007/978-981-10-8848-3_58
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