DocumentCode :
1634878
Title :
Performance Analysis Using Subsuming Methods: An Industrial Case Study
Author :
Maplesden, David ; von Randow, Karl ; Tempero, Ewan ; Hosking, John ; Grundy, John
Author_Institution :
Univ. of Auckland, Auckland, New Zealand
Volume :
2
fYear :
2015
Firstpage :
149
Lastpage :
158
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 methods; optimisation; pattern recognition; social networking (online); software performance evaluation; CPU load reduction; application runtime behaviour; automatic pattern identification; average response time reduction; complex runtime behaviour; large-scale object-oriented application; large-scale object-oriented applications; optimisation opportunities; performance analysis; social network Website; subsuming method analysis; subsuming methods; Context; Databases; Optimization; Performance analysis; Runtime; Servers; Time factors; Object oriented software; Performance analysis; Runtime bloat; Subsuming methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (ICSE), 2015 IEEE/ACM 37th IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICSE.2015.143
Filename :
7202959
Link To Document :
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