Evaluating Software Product Metrics with Synthetic Defect Data

Stuckman, Jeffrey; Wills, Kent; Purtilo, James M.

doi:10.1109/esem.2013.38

Cited by 2 publications

(1 citation statement)

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“…It is not surprising then that several studies have attempted to compare software metrics to better understand their similarities and differences. Work by Stuckman et al (2013) for example, used synthetic defect datasets to assess the performance of metrics, complemented by a formal mathematical model. One of the results of the study was that a relatively small set of source code metrics conveyed the same information as a larger set.…”

Section: Analysis Of Software Metricsmentioning

confidence: 99%

An experimental search-based approach to cohesion metric evaluation

et al. 2016

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In spite of several decades of software metrics research and practice, there is little understanding of how software metrics relate to one another, nor is there any established methodology for comparing them. We propose a novel experimental technique, based on search-based refactoring, to 'animate' metrics and observe their behaviour in a practical setting. Our aim is to promote metrics to the level of active, opinionated objects that can be compared experimentally to uncover where they conflict, and to understand better the underlying cause of the conflict. Our experimental approaches include semi-random refactoring, refactoring for increased metric agreement/disagreement, refactoring to increase/decrease the gap between a pair of metrics, and targeted hypothesis testing. We apply our approach to

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Section: Analysis Of Software Metricsmentioning

confidence: 99%