Document Type

Article

Department/Program

Computer Science

Journal Title

2016 Ieee/Acm 38th International Conference on Software Engineering Companion (Icse-C)

Pub Date

2016

First Page

593

Abstract

A goal of performance testing is to find situations when applications unexpectedly exhibit worsened characteristics for certain combinations of input values. A fundamental question of performance testing is how to select a manageable subset of the input data faster to find performance problems in applications automatically. We present a novel tool, FOREPOST, for finding performance problems in applications automatically using black-box software testing. In this paper, we demonstrate how FOREPOST extracts rules from execution traces of applications by using machine learning algorithms, and then uses these rules to select test input data automatically to steer applications towards computationally intensive paths and to find performance problems.

DOI

10.1145/2889160.2889164

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