Paper Info
Title
quiho: Automated Performance Regression Testing Using Inferred Resource Utilization Profiles.
Abstract
We introduce quiho, a framework for profiling application performance that can be used in automated performance regression tests. quiho profiles an application by applying sensitivity analysis, in particular statistical regression analysis (SRA), using application-independent performance feature vectors that characterize the performance of machines. The result of the SRA, feature importance specifically, is used as a proxy to identify hardware and low-level system software behavior. The relative importance of these features serve as a performance profile of an application (termed inferred resource utilization profile or IRUP), which is used to automatically validate performance behavior across multiple revisions of an application»s code base without having to instrument code or obtain performance counters. We demonstrate that quiho can successfully discover performance regressions by showing its effectiveness in profiling application performance for synthetically introduced regressions as well as those found in real-world applications.
Year
Venue
Field
2018
ICPE
System software,Data mining,Feature vector,Performance engineering,Regression analysis,Profiling (computer programming),Control engineering,Regression testing,Engineering,Software testing
DocType
ISBN
Citations 
Conference
978-1-4503-5095-2
0
PageRank 
References 
Authors
0.34
21
5
Name
Order
Citations
PageRank
Ivo Jimenez1183.76
Noah Watkins21068.09
Michael Sevilla3111.63
Jay F. Lofstead438223.42
Carlos Maltzahn5120187.49