Interactive Production Performance Feedback in the IDE
Name
icse19-performancehat.pdf
Description
Accepted version
Size
1.64 MB
Format
Adobe PDF
Checksum (MD5)
ce548347b138ee27be505e8b2fe9104e
Author(s)
Cito, Jurgen
Leitner, Philipp
Rinard, Martin C
Gall, Harald C.
Date Issued
August 2019
Journal
Proceedings - International Conference on Software Engineering
Publisher
IEEE
Citation
Cito, Jurgen, Leitner, Philipp, Rinard, Martin C and Gall, Harald C. 2019. "Interactive Production Performance Feedback in the IDE." Proceedings - International Conference on Software Engineering, 2019-May.
Version
Author's final manuscript
Abstract
© 2019 IEEE. Because of differences between development and production environments, many software performance problems are detected only after software enters production. We present PerformanceHat, a new system that uses profiling information from production executions to develop a global performance model suitable for integration into interactive development environments. PerformanceHat's ability to incrementally update this global model as the software is changed in the development environment enables it to deliver near real-time predictions of performance consequences reflecting the impact on the production environment. We implement PerformanceHat as an Eclipse plugin and evaluate it in a controlled experiment with 20 professional software developers implementing several software maintenance tasks using our approach and a representative baseline (Kibana). Our results indicate that developers using PerformanceHat were significantly faster in (1) detecting the performance problem, and (2) finding the root-cause of the problem. These results provide encouraging evidence that our approach helps developers detect, prevent, and debug production performance problems during development before the problem manifests in production.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICSE.2019.00102
