skip to main content
10.1145/3359061.3361076acmconferencesArticle/Chapter ViewAbstractPublication PagessplashConference Proceedingsconference-collections
short-paper

Improving performance and quality of database-backed software

Published: 20 October 2019 Publication History

Abstract

Modern web applications have stringent latency requirements while processing an ever-increasing amount of user data. To address these challenges and improve programmer productivity, Object Relational Mapping (ORM) frameworks have been developed to allow developers writing database processing code in an object-oriented manner. Despite such frameworks, prior work found that developers still struggle in developing ORM-based web applications. This paper presents a series of study and developed tools for optimizing web applications developed using the Ruby on Rails ORM. Using automated static analysis, we detect ORM related inefficiency problems and suggests fixes to developers. Our evaluation on 12 real-world applications shows that more than 1000 performance issues can be detected and fixed.

References

[1]
2018. Download PowerStation. https://bit.ly/2NYFRs3 .
[2]
2018. Hacker News. https://news.ycombinator.com/item?id=17414383 .
[3]
2018. The morning paper. https://bit.ly/2IxpkI4 .
[4]
2018. RubyWeekly. https://rubyweekly.com/issues/406 .
[5]
2019. RubyMine. https://www.jetbrains.com/ruby/ .
[6]
Tse-Hsun Chen, Weiyi Shang, Zhen Ming Jiang, Ahmed E Hassan, Mohamed Nasser, and Parminder Flora. 2016. Finding and evaluating the performance impact of redundant data access for applications that are developed using object-relational mapping frameworks. Transactions on Software Engineering (2016).
[7]
Cong Yan, Junwen Yang, Alvin Cheung, and Shan Lu. 2017. Understanding Database Performance Inefficiencies in Real-world Web Applications. In 26th Conference on Information and Knowledge Management (CIKM) .
[8]
Junwen Yang, Pranav Subramaniam, Shan Lu, Cong Yan, and Alvin Cheung. 2018. PowerStation: Automatically detecting and fixing inefficiencies of database-backed web applications in IDE. In 26th Foundations of Software Engineering (FSE’18 Demostration Track) .
[9]
Junwen Yang, Cong Yan, Pranav Subramaniam, Shan Lu, and Alvin Cheung. 2018. How not to structure your database-backed web applications: a study of performance bugs in the wild. In IEEE/ACM 40th International Conference on Software Engineering (ICSE) . IEEE, 800–810.
[10]
Junwen Yang, Cong Yan, Chengcheng Wan, Shan Lu, and Alvin Cheung. 2019. View-Centric Performance Optimization for DatabaseBacked Web Applications. In IEEE/ACM 41th International Conference on Software Engineering (ICSE) . IEEE.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
SPLASH Companion 2019: Proceedings Companion of the 2019 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity
October 2019
58 pages
ISBN:9781450369923
DOI:10.1145/3359061
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 October 2019

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Object-Relational Mapping frameworks
  2. RubyMine Plugin
  3. database-backed applications
  4. performance anti-patterns

Qualifiers

  • Short-paper

Conference

SPLASH '19
Sponsor:

Upcoming Conference

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 117
    Total Downloads
  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)1
Reflects downloads up to 05 Mar 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media