Learning performance optimization from code changes for android apps

Ruitao Feng, Guozhu Meng, Xiaofei Xie, Ting Su, Yang Liu, Shang Wei Lin

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

3 Citations (Scopus)

Abstract

Performance issues of Android apps can tangibly degrade user experience. However, it is challenging for Android developers, especially a novice to develop high-performance apps. It is primarily attributed to the lack of consolidated and abundant programmatic guides for performance optimization. To address this challenge, we propose a data-based approach to obtain performance optimization practices from historical code changes. We first elicit performance-aware Android APIs of which invocations could affect app performance to a large extent, identify historical code changes that produce impact on app performance, and further determine whether they are optimization practices. We have implemented this approach with a tool \tool and evaluated its effectiveness in 2 open source well-maintained projects. The experimental results found 83 changes relevant to performance optimization. Last, we summarize and explain 5 optimization rules to facilitate the development of high-performance apps.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages285-290
Number of pages6
ISBN (Electronic)9781728108889
DOIs
Publication statusPublished - Apr 2019
Externally publishedYes
Event12th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019 - Xi'an, China
Duration: Apr 22 2019Apr 27 2019

Publication series

NameProceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019

Conference

Conference12th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019
Country/TerritoryChina
CityXi'an
Period4/22/194/27/19

All Science Journal Classification (ASJC) codes

  • Software
  • Safety, Risk, Reliability and Quality

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