.png){kind=icon}
返回
Exoneration-based fault localization for SQL predicates
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jss.2018.10.037.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Spectrum-based fault localization (SFL) techniques automatically localize faults in program entities (statements, predicates, SQL clauses, etc.) by analyzing information collected from test executions. One application of SFL techniques is to find faulty SQL statements in database applications. However, prior techniques treated each SQL statement as one program entity, thus they could not find faulty elements inside SQL statements. Since SQL statements can be complex, identifying the faulty element within a faulty SQL statement is still time-consuming. In our previous paper, we developed a novel fault localization method based on row-based dynamic slicing and delta debugging techniques that can localize faults in individual clauses within SQL predicates. We call this technique exoneration-based fault localization because it can exonerate innocent elements and precisely identify the faulty element, whereas previous SFL techniques simply ranked all the elements in an SQL statement based on suspiciousness. This paper improves the exoneration-based fault localization technique with a new algorithm that considerably reduces the execution time. We also conducted an empirical study that compared nine existing SFL techniques with the exoneration-based technique in localizing faulty clauses in SQL predicates. Results indicate that the new exoneration-based technique surpasses the other techniques both in terms of effectiveness and efficiency. (C) 2018 Elsevier Inc. All rights reserved.
Keyword:
Fault localization
Spectrum-based fault localization
Exoneration-based fault localization
SQL
WHERE clause
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。