Resource Adaptation via Test-Based Software Minimization

Arpit Christi, Alex Groce, Rahul Gopinath

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Building software systems that adapt to changing resource environments is challenging: developers cannot anticipate all future situations that a software system may face, and even if they could, the effort required to handle such situations would often be too onerous for practical purposes. We propose a novel approach to allow a system to generate resource usage adaptations: use delta-debugging to generate versions of software systems that are 1-minimal with respect to satisfying various (labeled) subsets of a system's test suite. Many such variations will, while retaining core system functionality, use fewer resources. We describe an efficient tool for computing such variants and show how it reduces with respect to randomly selected subsets of Java class test suites, and propose an infrastructure in which this approach leads to a method for resource adaptation in the field. Using the NetBeans IDE, we demonstrate that even without additional infrastructure or heuristics, our approach is capable of quickly and cleanly removing a program's undo functionality, significantly reducing its resource usage, with no more effort than simply labeling three test cases asundo-related.

Original languageEnglish (US)
Title of host publicationProceedings - 11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages61-70
Number of pages10
ISBN (Electronic)9781509065554
DOIs
StatePublished - Oct 9 2017
Event11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2017 - Tucson, United States
Duration: Sep 18 2017Sep 22 2017

Publication series

NameProceedings - 11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2017

Conference

Conference11th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2017
Country/TerritoryUnited States
CityTucson
Period9/18/179/22/17

Keywords

  • delta-debugging
  • program mutation
  • resource adaptation
  • tests as specifications

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization

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