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Invalid bug reports complicate the software aging situation
Software Quality Journal ( IF 1.9 ) Pub Date : 2020-01-13 , DOI: 10.1007/s11219-019-09481-2
Xiaoxue Wu , Wei Zheng , Minchao Pu , Jie Chen , Dejun Mu

Symptoms of software aging include performance degradation and failure occurrence increasing when software systems run for a period of time. Therefore, software aging is closely related to system performance. Understanding and analyzing performance issues in the software system is critical to mastering software aging information. Instead of focusing on normal valid bug reports (VBRs), this paper advocates the usage of invalid bug reports (IBRs) to capture software aging signals. We use performance bugs that are highly related to software aging as an example to construct a binary classification model for bug report classification. We conduct a rigorous evaluation of the constructed models via different performance measures (i.e., recall, precision, F1-score, AUC). Then, the model is used to predict the performance bug reports (PBRs) in IBRs, and a manual analysis of the prediction results is conducted to identify aging-related bug reports (ABRs). The final results show that the ratio of PBRs in IBRs ranges from 4.9 to 42.18% for the two real open-source projects HDFS and HBase when considering five different classifiers. Among these five classifiers, Support Vector Machine (SVM) classifier can achieve the best performance. The ratios of PBRs in IBRs by using this classifier are 11.1% and 15.35% for these two datasets and the performances in terms of F1-score are 85% and 74%. Further analysis of the predicted PBRs of IBRs in the project HDFS is conducted through a manual user case study; some surprising findings revealing the relationship between IBRs, PBRs, and ABRs are presented: (1) Around 50% of the PBRs in IBRs are related to software aging; (2) components that undertake major tasks are more prone to aging problems; (3) more than 50% ARBs lead to timeout, 33% ARBs are caused by improper control of memory or threats, and 29% ARBs are caused by inappropriate management of file operation or disk usage; (4) hard to reproduce is the major reason that ARBs are usually closed as invalid because many aging-related bugs would temporarily disappear by restarting the system.

中文翻译:

无效的错误报告使软件老化情况复杂化

软件老化的症状包括软件系统运行一段时间后性能下降和故障发生率增加。因此,软件老化与系统性能密切相关。了解和分析软件系统中的性能问题对于掌握软件老化信息至关重要。本文不关注正常的有效错误报告 (VBR),而是提倡使用无效错误报告 (IBR) 来捕获软件老化信号。我们以与软件老化高度相关的性能 bug 为例,构建了一个用于 bug 报告分类的二元分类模型。我们通过不同的性能指标(即召回率、精度、F1 分数、AUC)对构建的模型进行严格评估。然后,该模型用于预测 IBR 中的性能错误报告 (PBR),并对预测结果进行手动分析,以识别与老化相关的错误报告 (ABR)。最终结果表明,当考虑五种不同的分类器时,对于两个真正的开源项目 HDFS 和 HBase,IBR 中 PBR 的比例范围为 4.9% 到 42.18%。在这五个分类器中,支持向量机(SVM)分类器的性能最好。对于这两个数据集,使用该分类器在 IBR 中 PBR 的比率分别为 11.1% 和 15.35%,F1 分数的性能分别为 85% 和 74%。通过手动用户案例研究,对项目 HDFS 中 IBR 的预测 PBR 进行了进一步分析;一些令人惊讶的发现揭示了 IBR、PBR 和 ABR 之间的关系: (1) IBR 中大约 50% 的 PBR 与软件老化有关;(2)承担重大任务的组件更容易出现老化问题;(3) 超过50%的ARB导致超时,33%的ARB是由于内存控制不当或威胁造成的,29%的ARB是由于文件操作或磁盘使用管理不当引起的;(4) 难以重现是ARBs通常被关闭为无效的主要原因,因为许多与老化相关的错误会通过重新启动系统暂时消失。
更新日期:2020-01-13
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