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Are Popular Classes More Defect Prone?

Are Popular Classes More Defect Prone?,10.1007/978-3-642-12029-9_5,Alberto Bacchelli,Marco D’Ambros,Michele Lanza

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Are Popular Classes More Defect Prone?   (Citations: 7)
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Traces of the evolution of software systems are left in a number of different repositories, such as configuration management systems, bug tracking systems, and mailing lists. Developers use e-mails to discuss issues ranging from low-level concerns (bug fixes, refactorings) to high-level resolutions (future planning, design decisions). Thus, e-mail archives constitute a valuable asset for understanding the evolutionary dynamics of a system. We introduce metrics that measure the “popularity” of source code artifacts, i.e. the amount of discussion they generate in e-mail archives, and investigate whether the information contained in e-mail archives is correlated to the defects found in the system. Our hypothesis is that developers discuss problematic entities more than unproblematic ones. We also study whether the precision of existing techniques for defect prediction can be improved using our popularity metrics.
Conference: Fundamental Approaches to Software Engineering - FASE , pp. 59-73, 2010
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    • ... we devised [4]; (3) manually interact with emails and, for example, label them to create benchmarks for assessing the accuracy of mining methods [3]; (4) automatically find the traceability links between email and code entities, using various linking techniques [3, 7]; (5) automatically recognize emails and lines containing source code [2]; (6) export manual benchmarks and code metrics computed from mailing lists, such as “popularity” [1]; ...
    • ...The Miler toolset o ers a Popularity metrics extractor, which—by combining link data, system model, and email model— extracts various metrics to seize the “popularity” of code artifacts in mailing lists discussions [1]...

    Alberto Bacchelli, et al. Miler: a toolset for exploring email data

    • ...Bacchelli et al.’s empirical study [1] reveals that the discussions of an artifact in email archives and the defects of the artifact are significantly correlated...

    Lin Shi, et al. An Empirical Study on Evolution of API Documentation

    • ...The most interesting result is that the union of metrics extracted from repositories with di erent form of data, i.e., emails and change history, improves the overall predictive power [1]...

    Alberto Bacchelli. Exploring, exposing, and exploiting emails to include human factors in...

    • ... considerations (e.g., design rationales), they can be written and read by both software system developers and beta-testers or endusers, they always come with additional information (e.g., time-stamp, thread, author) that can be taken into account, they can be linked to any source code entity they are related to, they can be used to study the evolution of a system, and they can be employed in the prediction of defect-prone entities [2]...

    Alberto Bacchelli, et al. Towards integrating e-mail communication in the IDE

    • ...Our future work is twofold: (1) since naming conventions greatly improve the linking, easing their usage when writing emails is critical, and (2) we will exploit these links; we have already shown their usefulness for bug prediction [2]...

    Alberto Bacchelli, et al. Linking e-mails and source code artifacts

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