Many projects often receive more bug reports than what they can handle. To help debug and close bug reports, a number of bug localization techniques have been proposed. These techniques analyze a bug report and return a ranked list of potentially buggy source code files. Recent development on bug localization has resulted in the construction of effective supervised approaches that use historical data of manually localized bugs to boost performance. Unfortunately, as highlighted by Zimmermann et al., sufficient bug data is often unavailable for many projects and companies. This raises the need for cross-project bug localization – the use of data from a project to help locate bugs in another project. To fill this need, we propose a deep transfer learning approach for cross-project bug localization. Our proposed approach named TRANP-CNN extracts transferable semantic features from source project and fully exploits labeled data from target project for effective cross-project bug localization. We have evaluated TRANP-CNN on curated high-quality bug datasets and our experimental results show that TRANP-CNN can locate buggy files correctly at top 1, top 5, and top 10 positions for 29.9%, 51.7%, 61.3% of the bugs respectively, which significantly outperform state-of-the-art bug localization solution based on deep learning and several other advanced alternative solutions considering various standard evaluation metrics.
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15:00 - 16:00: A21-Testing and Debugging 3Paper Presentations / Journal First / Technical Papers at Silla Chair(s): Tingting YuUniversity of Kentucky | |||
15:00 - 15:12 Talk | Schrödinger's Security: Opening the Box on App Developers' Security RationaleTechnical Technical Papers Dirk van der LindenUniversity of Bristol, Pauline AnthonysamyGoogle Inc., Bashar NuseibehThe Open University (UK) & Lero (Ireland), Thein Tun, Marian PetreThe Open University, Mark LevineLancaster University, John TowseLancaster University, Awais RashidUniversity of Bristol, UK | ||
15:12 - 15:20 Talk | Smart Greybox FuzzingJ1 Journal First Van-Thuan PhamMonash University, Marcel BöhmeMonash University, Andrew SantosaNational University of Singapore, Alexandru Răzvan CăciulescuUiPath, Abhik RoychoudhuryNational University of Singapore, Singapore | ||
15:20 - 15:28 Talk | Deep Transfer Bug LocalizationJ1 Journal First Xuan HuoNanjing University, Ferdian ThungSingapore Management University, Ming LiNanjing University, David LoSingapore Management University, Shu-Ting ShiNanjing University | ||
15:28 - 15:36 Talk | A Benchmark-Based Evaluation of Search-Based Crash ReproductionJ1 Journal First Mozhan SoltaniLeiden University, Pouria DerakhshanfarDelft University of Technology, Xavier DevroeyDelft University of Technology, Arie van DeursenDelft University of Technology Link to publication DOI Pre-print Media Attached | ||
15:36 - 15:48 Talk | An Investigation of Cross-Project Learning in Online Just-In-Time Software Defect PredictionTechnical Technical Papers Sadia TabassumUniversity of Birmingham, UK, Leandro MinkuUniversity of Birmingham, UK, Danyi FengXiLiu Tech, George CabralUniversidade Federal Rural de Pernambuco, Liyan SongUniversity of Birmingham | ||
15:48 - 15:56 Talk | An Empirical Study of the Long Duration of Continuous Integration BuildsJ1 Journal First Taher Ahmed GhalebQueen's University, Daniel Alencar Da CostaUniversity of Otago, Ying ZouQueen's University, Kingston, Ontario Link to publication DOI Pre-print |