Author(s): Prof. Devendra Kumar, Ms. Ritu Sharma
Published in: International Journal of Engineering Research & Technology
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Volume/Issue: Volume. 4 - Issue. 05 , May - 2015
Bug Localization is the task of locating the area of source code that requires modification to correct that bug. By automating this task, effort of debugger can be considerably reduced. In past, automated bug localization has been done with the help of many IR(Information Retrieval) models that focused on the semantic information. In this paper, we have proposed LDACG approach for bug localization which focuses on both semantic and structural information. In LDACG approach, bugs are located using an IR model i.e. LDA (Latent Dirichlet Allocation) and Call graph. Then the combined score of both methods is calculated to locate bugs in efficient manner. We have compared LDACG based approach with LDA based approach and it has been found that LDACG approach performs better than LDA approach for bug localization. The performance of both approaches has been evaluated on the datasets downloaded from two open source projects i.e. Rhino and ModeShape.
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