Title :
Measuring the Accuracy of Information Retrieval Based Bug Localization Techniques
Author :
Beard, Matthew ; Kraft, Nicholas ; Etzkorn, Letha ; Lukins, Stacy
Author_Institution :
Comput. Sci. Dept., Univ. of Alabama in Huntsville, Huntsville, AL, USA
Abstract :
Bug localization involves using information about a bug to locate affected code sections. Several automated bug localization techniques based on information retrieval (IR) models have been constructed recently. The "gold standard" of measuring an IR technique\´s accuracy considers the technique\´s ability to locate a "first relevant method." However, the question remains -- does finding this single method enable the location of a complete set of affected methods? Previous arguments assume this to be true, however, few analyses of this assumption have been performed. In this paper, we perform a case study to test the reliability of this "gold standard" assumption. To further measure IR accuracy in the context of bug localization, we analyze the relevance of the IR model\´s "first method returned." We use various structural analysis techniques to extend relevant methods located by IR techniques and determine accuracy and reliability of these assumptions.
Keywords :
information retrieval; program debugging; software maintenance; automated bug localization techniques; first method returned; gold standard assumption; information retrieval models; Accuracy; Computer bugs; Gold; Large scale integration; Magnetic resonance; Reliability; Semantics; concept location; feature identification; information retrieval; latent Dirichlet allocation; latent semantic indexing; program comprehension; static analysis;
Conference_Titel :
Reverse Engineering (WCRE), 2011 18th Working Conference on
Conference_Location :
Limerick
Print_ISBN :
978-1-4577-1948-6
DOI :
10.1109/WCRE.2011.23