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Full-Text Articles in Physical Sciences and Mathematics
Predicting Effectiveness Of Ir-Based Bug Localization Techniques, Tien-Duy B. Le, Ferdian Thung, David Lo
Predicting Effectiveness Of Ir-Based Bug Localization Techniques, Tien-Duy B. Le, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Recently, many information retrieval (IR) based bug localization approaches have been proposed in the literature. These approaches use information retrieval techniques to process a textual bug report and a collection of source code files to find buggy files. They output a ranked list of files sorted by their likelihood to contain the bug. Recent approaches can achieve reasonable accuracy, however, even a state-of-the-art bug localization tool outputs many ranked lists where buggy files appear very low in the lists. This potentially causes developers to distrust bug localization tools. Parnin and Orso recently conduct a user study and highlight that developers …
Potential Biases In Bug Localization: Do They Matter?, Pavneet Singh Kochhar, Yuan Tian, David Lo
Potential Biases In Bug Localization: Do They Matter?, Pavneet Singh Kochhar, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Issue tracking systems are valuable resources during software maintenance activities and contain information about the issues faced during the development of a project as well as after its release. Many projects receive many reports of bugs and it is challenging for developers to manually debug and fix them. To mitigate this problem, past studies have proposed information retrieval (IR)-based bug localization techniques, which takes as input a textual description of a bug stored in an issue tracking system, and returns a list of potentially buggy source code files. These studies often evaluate their effectiveness on issue reports marked as bugs …
Version History, Similar Report, And Structure: Putting Them Together For Improved Bug Localization, Shaowei Wang, David Lo
Version History, Similar Report, And Structure: Putting Them Together For Improved Bug Localization, Shaowei Wang, David Lo
Research Collection School Of Computing and Information Systems
During the evolution of a software system, a large number of bug reports are submitted. Locating the source code files that need to be fixed to resolve the bugs is a challenging problem. Thus, there is a need for a technique that can automatically figure out these buggy files. A number of bug localization solutions that take in a bug report and output a ranked list of files sorted based on their likelihood to be buggy have been proposed in the literature. However, the accuracy of these tools still need to be improved. In this paper, to address this need, …
Cross-Language Bug Localization, Xin Xia, David Lo, Xingen Wang, Chenyi Zhang, Xinyu Wang
Cross-Language Bug Localization, Xin Xia, David Lo, Xingen Wang, Chenyi Zhang, Xinyu Wang
Research Collection School Of Computing and Information Systems
Bug localization refers to the process of identifying source code files that contain defects from textual descriptions in bug reports. Existing bug localization techniques work on the assumption that bug reports, and identifiers and comments in source code files, are written in the same language (i.e., English). However, software users from non-English speaking countries (e.g., China) often use their native languages (e.g., Chinese) to write bug reports. For this setting, existing studies on bug localization would not work as the terms that appear in the bug reports do not appear in the source code. We refer to this problem as …