Severity Assessment of a Reported Bug by Considering its Uncertainty and Irregular State

Q4 Computer Science

International Journal of Open Source Software and Processes Pub Date : 2018-10-01 DOI:10.4018/IJOSSP.2018100102

Madhu Kumari, Meera Sharma, V. B. Singh

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引用次数: 14

Abstract

An accurate bug severity assessment is an important factor in bug fixing. Bugs are reported on the bug tracking system by different users with a fast speed. The size of software repositories is also increasing at an enormous rate. This increased size often has much uncertainty and irregularities. The factors that cause uncertainty are biases, noise and abnormality in data. The authors consider that software bug report phenomena on the bug tracking system keeps an irregular state. Without proper handling of these uncertainties and irregularities, the performance of learning strategies can be significantly reduced. To incorporate and consider these two phenomena, they have used entropy as an attribute to assess bug severity. The authors have predicted the bug severity by using machine learning techniques, namely KNN, J48, RF, RNG, NB, CNN and MLR. They have validated the classifiers using PITS, Eclipse and Mozilla projects. The results show that the proposed entropy-based approaches improves the performance as compared to the state of the art approach considered in this article.

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考虑不确定性和不规则状态的Bug严重性评估

准确的错误严重性评估是修复错误的重要因素。不同的用户以较快的速度在bug跟踪系统上报告bug。软件存储库的规模也在以惊人的速度增长。这种增加的尺寸通常有很多不确定性和不规则性。造成不确定性的因素有偏差、噪声和数据异常。作者认为，在缺陷跟踪系统中，软件缺陷报告现象是一种不规则的状态。如果不正确处理这些不确定性和不规则性，学习策略的性能会大大降低。为了结合并考虑这两种现象，他们使用熵作为评估bug严重性的属性。作者通过使用机器学习技术预测了漏洞的严重性，即KNN, J48, RF, RNG, NB, CNN和MLR。他们已经使用PITS、Eclipse和Mozilla项目验证了分类器。结果表明，与本文中考虑的最先进的方法相比，所提出的基于熵的方法提高了性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Open Source Software and Processes Computer Science-Software

CiteScore

1.90

自引率

0.00%

发文量

期刊介绍： The International Journal of Open Source Software and Processes (IJOSSP) publishes high-quality peer-reviewed and original research articles on the large field of open source software and processes. This wide area entails many intriguing question and facets, including the special development process performed by a large number of geographically dispersed programmers, community issues like coordination and communication, motivations of the participants, and also economic and legal issues. Beyond this topic, open source software is an example of a highly distributed innovation process led by the users. Therefore, many aspects have relevance beyond the realm of software and its development. In this tradition, IJOSSP also publishes papers on these topics. IJOSSP is a multi-disciplinary outlet, and welcomes submissions from all relevant fields of research and applying a multitude of research approaches.