@inproceedings{399f24eaf27c4df49f8f437e41f38821,
title = "Performance Analysis Using Subsuming Methods: An Industrial Case Study",
abstract = "Large-scale object-oriented applications consist of tens of thousands of methods and exhibit highly complex runtime behaviour that is difficult to analyse for performance. Typical performance analysis approaches that aggregate performance measures in a method-centric manner result in thinly distributed costs and few easily identifiable optimisation opportunities. Subsuming methods analysis is a new approach that aggregates performance costs across repeated patterns of method calls that occur in the application's runtime behaviour. This allows automatic identification of patterns that are expensive and represent practical optimisation opportunities. To evaluate the practicality of this analysis with a real world large-scale object-oriented application we completed a case study with the developers of letterboxd.com - a social network website for movie goers. Using the results of the analysis we were able to rapidly implement changes resulting in a 54.8% reduction in CPU load and an 49.6% reduction in average response time.",
keywords = "Object oriented software, Performance analysis, Runtime bloat, Subsuming methods",
author = "David Maplesden and Randow, {Karl Von} and Ewan Tempero and John Hosking and John Grundy",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 37th IEEE/ACM International Conference on Software Engineering, ICSE 2015 ; Conference date: 16-05-2015 Through 24-05-2015",
year = "2015",
month = aug,
day = "12",
doi = "10.1109/ICSE.2015.143",
language = "English",
series = "Proceedings - International Conference on Software Engineering",
publisher = "IEEE Computer Society",
pages = "149--158",
booktitle = "Proceedings - 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, ICSE 2015",
address = "United States",
}