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  4. Minecraft: Automated Mining of Software Bug Fixes with Precise Code Context
 
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Minecraft: Automated Mining of Software Bug Fixes with Precise Code Context

Source
Proceedings 2023 38th IEEE ACM International Conference on Automated Software Engineering Ase 2023
Date Issued
2023-01-01
Author(s)
Avula, Sai Krishna
Vobbilisetti, Venkatesh
Mondal, Shouvick  
DOI
10.1109/ASE56229.2023.00116
Abstract
Repository mining of bug fixes from version control systems like GitHub is a challenging problem as far as the precision of the bug context is concerned, i.e., source codes immediately preceding and succeeding the fix location. Coupled with this, identification of the type of the bug fix goes a long way towards creating high quality datasets that can be used for several downstream tasks. However, existing bug fix datasets suffer from the following limitations that dilute the data quality. Firstly, they do not focus on multilingual projects in their entirety given that most open-source projects are now multilingual. Secondly, the granularity of the bug fixes are considered only at the function/method level without specifying line/statement level information. Thirdly, bug fixes lying within the scope of a source file but outside any of its constituent functions have not been examined. In this paper, we propose a solution to overcome the aforementioned limitations by introducing a novel and extensive dataset named Minecraft. With a size of 28.8GB (considering 416 GitHub projects encompassing programming languages such as C, C++, Java, and Python, 2.2M commits, 3.29M bug-fix pairs), Minecraft surpasses the existing datasets by 4-fold enlargement in terms of data availability. We believe Minecraft would serve as a valuable resource for various stakeholders in the software development and research communities, empowering them to improve software quality, develop innovative bug detection and auto-fix techniques, and advance the field of software engineering.
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URI
https://d8.irins.org/handle/IITG2025/27004
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