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

1 Citation (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
CountryChina
CityXi'an
Period4/22/194/27/19

All Science Journal Classification (ASJC) codes

  • Software
  • Safety, Risk, Reliability and Quality

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