To What Extent Does Performance Awareness Support Developers in Fixing Performance Bugs?

Alexandru Danciu, Helmut Krcmar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Current research on performance awareness evaluates approaches primarily for their functional correctness but does not assess to what extent developers are supported in improving software implementations. This article presents the evaluation of an existing approach for supporting developers of Java Enterprise Edition (EE) applications with response time estimations based on a controlled human-oriented experiment. The main goal of the experiment is to quantify the effectiveness of employing the approach while optimizing the response time of an implementation. Subjects’ optimizations are quantified by the amount of fixed performance bugs. Having employed the approach, subjects fixed on average over three times more performance bugs. The results further indicate that in the absence of a performance awareness aid, the success of optimizing a previously unknown implementation is far less dependent of the behavior and skill level of the developer.

Original languageEnglish
Title of host publicationComputer Performance Engineering - 15th European Workshop, EPEW 2018, Proceedings
EditorsAnne Remke, Paolo Ballarini, Benoît Barbot, Rena Bakhshi, Hind Castel-Taleb
PublisherSpringer Verlag
Pages14-29
Number of pages16
ISBN (Print)9783030022266
DOIs
StatePublished - 2018
Event15th European Performance Engineering Workshop, EPEW 2018 - Paris, France
Duration: 29 Oct 201830 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11178 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th European Performance Engineering Workshop, EPEW 2018
Country/TerritoryFrance
CityParis
Period29/10/1830/10/18

Keywords

  • Controlled experiment
  • Java EE
  • Palladio Component Model
  • Performance awareness
  • Response time estimation

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