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The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.


Using bug report similarity to enhance bug localisation

Davies, Steven and Roper, Marc and Wood, Murray (2012) Using bug report similarity to enhance bug localisation. In: 19th Working Conference on Reverse Engineering, 2012-10-15 - 2012-10-18.

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Bug localisation techniques are proposed as a method to reduce the time developers spend on maintenance, allowing them to quickly and source code relevant to a bug. Some techniques are based on information retrieval methods, treating the source code as a corpus and the bug report as a query. While these have shown success, there remain a number of little-exploited additional sources of information which could enhance the techniques, including the textual similarity between bug reports themselves. Based on successful results in detecting duplicate bug reports, this work asks: if duplicate bugs reports, which by denition are xed in the same source location, can be detected through the use of similar language, can bugs which are in the same location but not duplicates be detected in the same way? A technique using this information is implemented and evaluated on 372 bugs across 4 projects, and is found to improve performance on all projects. In particular, the technique increases the number of bugs where the rst relevant method presented to developers is the rst result from 6 to 27, and those in the top-10 from 50 to 57, showing that it can be successfully used to enhance existing bug localisation techniques.