Combining Query Reduction and Expansion for Text-Retrieval-Based Bug Localization
Combining Query Reduction and Expansion for Text-Retrieval-Based Bug Localization
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DOI：
10.1109/saner50967.2021.00024
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Juan Manuel Florez;Oscar Chaparro;Christoph Treude;Andrian Marcus
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文献类型：
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作者：
Juan Manuel Florez;Oscar Chaparro;Christoph Treude;Andrian Marcus
基于自动的文本回归错误本地化（TRBL）技术通常使用错误报告的全文来制定查询并检索代码的部分错误。先前的研究表明，减少查询的大小会提高TRBL的有效性。另一方面，研究人员在扩展查询时还发现了改进（即添加更多术语）。在本文中，我们将这两种观点汇总在一起，以重新调整TRBL的疑问。具体来说，我们通过采用组合方法并使用错误报告中的任务短语来改善基于话语的查询策略，并将其与最先进的查询扩展技术相结合，从而产生970个查询重新重新制定策略。我们根据最有效的策略调查了这些策略本地化构成错误代码元素的好处，并定义了一种称为QREX的新方法。我们使用五个最先进的自动化的TRBL方法评估了来自不同软件系统的1,217个查询，以从不同的软件系统进行了1,217个查询，以从不同的软件系统中进行了1,217个查询，评估了包括QREX的重新制定策略。结果表明，与无改革基线相比，与应用查询减少和扩展相比，QREX将TRBL效率提高了4％-12.6％，而将查询减少和扩展增加了32.1％。
Automated text-retrieval-based bug localization (TRBL) techniques normally use the full text of a bug report to formulate a query and retrieve parts of the code that are buggy. Previous research has shown that reducing the size of the query increases the effectiveness of TRBL. On the other hand, researchers also found improvements when expanding the query (i.e., adding more terms). In this paper, we bring these two views together to reformulate queries for TRBL. Specifically, we improve discourse-based query reduction strategies, by adopting a combinatorial approach and using task phrases from bug reports, and combine them with a state-of-the-art query expansion technique, resulting in 970 query reformulation strategies. We investigate the benefits of these strategies for localizing buggy code elements and define a new approach, called Qrex, based on the most effective strategy. We evaluated the reformulation strategies, including Qrex, on 1,217 queries from different software systems to retrieve buggy code artifacts at three code granularities, using five state-of-the-art automated TRBL approaches. The results indicate that Qrex increases TRBL effectiveness by 4% - 12.6%, compared to applying query reduction and expansion in isolation, and by 32.1%, compared to the no-reformulation baseline.