Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

11-2015

Abstract

This paper presents a scenario-based approach for the evaluation of the quality attribute of performance, measured in terms of execution time (response time). The approach is implemented by a framework that uses dynamic analysis and repository mining techniques to provide an automated way for revealing potential sources of performance degradation of scenarios between releases of a software system. The approach defines four phases: (i) preparation – choosing the scenarios and preparing the target releases; (ii) dynamic analysis – determining the performance of scenarios and methods by calculating their execution time; (iii) degradation analysis – processing and comparing the results of the dynamic analysis for different releases; and (iv) repository mining – identifying development issues and commits associated with performance deviation. The paper also describes an evolutionary study of applying the approach to multiple releases of the Netty, Wicket and Jetty frameworks. The study analyzed seven releases of each system and addressed a total of 57 scenarios. Overall, we have found 14 scenarios with significant performance deviation for Netty, 13 for Wicket, and 9 for Jetty, almost all of which could be attributed to a source code change. We also discuss feedback obtained from eight developers of Netty, Wicket and Jetty as result of a questionnaire.

Keywords

dynamic analysis, execution time, Performance, repository mining, scenario

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 2015 IEEE 15th International Working Conference on Source Code Analysis and Manipulation (SCAM), Bremen, Germany, September 27-28

First Page

201

Last Page

210

ISBN

9781467375290

Identifier

10.1109/SCAM.2015.7335416

Publisher

Institute of Electrical and Electronics Engineers Inc.

City or Country

Bremen, Germany

Additional URL

https://doi.org/10.1109/SCAM.2015.7335416

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