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Content Provider | IEEE Xplore Digital Library |
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Author | Couto, C. Silva, C. Valente, M.T. Bigonha, R. Anquetil, N. |
Copyright Year | 2012 |
Abstract | Bug prediction is an important challenge for software engineering research. It consist in looking for possible early indicators of the presence of bugs in a software. However, despite the relevance of the issue, most experiments designed to evaluate bug prediction only investigate whether there is a linear relation between the predictor and the presence of bugs. However, it is well known that standard regression models cannot filter out spurious relations. Therefore, in this paper we describe an experiment to discover more robust evidences towards causality between software metrics (as predictors) and the occurrence of bugs. For this purpose, we have relied on Granger Causality Test to evaluate whether past changes in a given time series are useful to forecast changes in another series. As its name suggests, Granger Test is a better indication of causality between two variables. We present and discuss the results of experiments on four real world systems evaluated over a time frame of almost four years. Particularly, we have been able to discover in the history of metrics the causes -- in the terms of the Granger Test -- for 64% to 93% of the defects reported for the systems considered in our experiment. |
Starting Page | 223 |
Ending Page | 232 |
File Size | 776481 |
Page Count | 10 |
File Format | |
ISBN | 9781467309844 |
ISSN | 15345351 |
e-ISBN | 9780769546667 |
DOI | 10.1109/CSMR.2012.31 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-03-27 |
Publisher Place | Hungary |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Time series analysis Computer bugs Mathematical model Software metrics Software Reliability Granger Test Bug Prediction Causality Software Metrics |
Content Type | Text |
Resource Type | Article |
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