How to Effectively Reduce Failure Analysis Time?

Author:

Golagha Mojdeh

Abstract

AbstractDebugging is one of the most expensive and challenging phases in the software development life-cycle. One important cost factor in the debugging process is the time required to analyze failures and find underlying faults. Two types of techniques that can help developers to reduce this analysis time are Failure Clustering and Automated Fault Localization. Although there is a plethora of these techniques in the literature, there are still some gaps that prevent their operationalization in real-world contexts. Besides, the abundance of these techniques confuses the developers in selecting a suitable method for their specific domain. In order to help developers in reducing analysis time, we propose methodologies and techniques that can be used standalone or in a form of a tool-chain. Utilizing this tool-chain, developers (1) know which data they need for further analysis, (2) are able to group failures based on their root causes, and (3) are able to find more information about the root causes of each failing group. Our tool-chain was initially developed based on state-of-the-art failure diagnosis techniques. We implemented and evaluated existing techniques. We built on and improved them where the results were promising and proposed new solutions where needed. The overarching goal of this study has been the applicability of techniques in practice.

Funder

Gesellschaft für Informatik e.V.

Publisher

Springer International Publishing

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3