Tue 27 Oct 2015 15:54 - 16:18 at Grand Station 3 - Session 4, Empirical Studies

Little is known about how software performance evolves across software revisions. The severity of this situation is high since (i) most performance variations seem to happen accidentally and (ii) addressing a performance regression is challenging, especially when functional code is stacked on it.

This paper reports an empirical study on the performance evolution of 19 applications, totaling over 19 MLOC. It took 52 days to run our 49 benchmarks. By relating performance variation with source code revisions, we found out that: (i) 1 out of every 3 application revisions introduces a performance variation, (ii) performance variations may be classified into 9 patterns, (iii) the most prominent cause of performance regression involves loops and collections. We carefully describe the patterns we identified, and detail how we addressed the numerous challenges we faced to complete our experiment.

Tue 27 Oct

Displayed time zone: Eastern Time (US & Canada) change

15:30 - 17:30
Session 4, Empirical StudiesDLS at Grand Station 3
15:30
24m
Talk
Measuring Polymorphism in Python Programs
DLS
Beatrice Åkerblom Stockholm University, Tobias Wrigstad Uppsala University
15:54
24m
Talk
Tracking Down Performance Variation Against Source Code Evolution
DLS
Juan Pablo Sandoval Alcocer Universidad Católica Boliviana San Pablo, Alexandre Bergel
16:18
24m
Talk
Server-Side Type Profiling for Optimizing Client-Side JavaScript Engines
DLS
Madhukar Kedlaya University of California, Santa Barbara, Behnam Robatmili Qualcomm Research, Ben Hardekopf UC Santa Barbara
16:42
24m
Talk
An Empirical Investigation of the Effects of Type Systems and Code Completion on API Usability using TypeScript and JavaScript in MS Visual Studio
DLS
Lars Fischer University of Duisburg-Essen, Essen, Germany, Stefan Hanenberg University of Duisburg-Essen
17:06
24m
Talk
Access Control to Reflection with Object Ownership
DLS
Camille Teruel INRIA, Stéphane Ducasse INRIA, France, Damien Cassou Lille 1 University, Marcus Denker INRIA Lille