Performance diagnosis for inefficient loops

Linhai Song, Shan Lu

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

21 Scopus citations

Abstract

Writing efficient software is difficult. Design and implementation defects cancause severe performance degradation. Unfortunately, existing performance diagnosis techniques like profilers are still preliminary. They can locate code regions that consume resources, but not the ones that waste resources. In this paper, we first design a root-causeand fix-strategy taxonomy for inefficient loops, one of the most common performance problems in the field. We then design a static-dynamic hybrid analysis tool, LDoctor, toprovide accurate performance diagnosis for loops. We further use sampling techniques to lower the run-Time overhead withoutdegrading the accuracy or latency of LDoctor diagnosis. Evaluation using real-world performanceproblems shows that LDoctor can provide better coverage and accuracy thanexisting techniques, with low overhead.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE/ACM 39th International Conference on Software Engineering, ICSE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages370-380
Number of pages11
ISBN (Electronic)9781538638682
DOIs
StatePublished - Jul 19 2017
Event39th IEEE/ACM International Conference on Software Engineering, ICSE 2017 - Buenos Aires, Argentina
Duration: May 20 2017May 28 2017

Publication series

NameProceedings - 2017 IEEE/ACM 39th International Conference on Software Engineering, ICSE 2017

Other

Other39th IEEE/ACM International Conference on Software Engineering, ICSE 2017
CountryArgentina
CityBuenos Aires
Period5/20/175/28/17

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Software

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