基于测试的软件修改评估资源适配的故障定位

Arpit Christi, Alex Groce, Rahul Gopinath
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引用次数: 2

摘要

动态适应资源变化的能力对于在不断变化的资源环境中运行的现代关键任务系统至关重要。基于测试的软件修改(TBSM)是最近提出的一种构建资源自适应软件(RAS)的技术,它依赖于现有的测试基础结构、测试标签和程序修改。TBSM技术简单实用,但效率不高;效率低下的主要原因是搜索空间的大小。在本文中,我们提出了AdFL,一种故障定位(FL)的重新用途,它可以比以前提出的启发式方法更有效地缩小(并优先考虑)TBSM的搜索空间。我们提出了完整的案例研究和一组开源项目的实证分析,以证明AdFL可以显著减少TBSM中的搜索空间。我们展示了如何将AdFL与先前的TBSM启发式方法结合起来,并提出了一个增量的、尽力而为的TBSM变体,该变体使用AdFL来确定搜索的优先级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating Fault Localization for Resource Adaptation via Test-Based Software Modification
The ability to dynamically adapt to resource variations is critical for modern-day mission-critical systems that operate in ever-changing resource environments. Test-based Software Modification (TBSM) is a recently proposed technique to build Resource Adaptive Software (RAS) that relies on existing test infrastructure, test labeling, and program modifications. TBSM is simple and applicable, but an inefficient technique; the primary reason for inefficiency is the sheer size of the search space. In this paper, we propose AdFL, a repurposing of Fault Localization (FL) that can shrink (and prioritize) the search space for TBSM more effectively than previously proposed heuristics. We present complete case studies and an empirical analysis of a set of open source projects as evidence that AdFL can significantly reduce the search space in TBSM. We show how to combine AdFL with previous heuristics for TBSM, and propose an incremental, best-effort variant of TBSM that uses AdFL to prioritize the search.
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