Work place: Department of Software Engineering, Hashemite University, Zarka 13315, Jordan
Research Interests: Software Creation and Management, Software Design, Software Development Process, Computer Architecture and Organization, Data Structures and Algorithms
Fadi I. Wedyan is an Associate Professor in the department of Software Engineering at the Hashemite University, Jordan. He completed his Ph.D. in computer science at Colorado State University (2011). He received his Master in computer science from Colorado State University (2008). He also holds a masters in Computer Science from Al-albayt University, Jordan (1999). He received his B.S. in computer science from Yarmouk University, Jordan (1995). His research interest is software testing, software design, aspect-oriented testing and development, static analysis, and mobile computing.
DOI: https://doi.org/10.5815/ijisa.2018.01.05, Pub. Date: 8 Jan. 2018
Mutation testing is a structural testing technique in which the effectiveness of a test suite is measured by the suite ability to detect seeded faults. One fault is seeded into a copy of the program, called mutant, leading to a large number of mutants with a high cost of compiling and running the test suite against the mutants. Moreover, many of the mutants produce the same output as the original program (called equivalent mutants), such mutants need to be minimized to produce accurate results. Higher order mutation testing aims at solving these problems by allowing more than one fault to be seeded in the mutant. Recent work in higher order mutation show promising result in reducing the cost of mutation testing and increasing the approach effectiveness. In this paper, we present an approach for generating higher order mutants using a genetic algorithm. The aim of the proposed approach is to produce subtle and harder to kill mutants, and reduce the percentage of produced equivalent mutants. A Java tool has been developed, called HOMJava (Higher Order Mutation for Java), which implements the proposed approach. An experimental study was performed to evaluate the effectiveness of the proposed approach. The results show that the approach was able to produce subtle higher order mutants, the fitness of mutants improved by almost 99% compared with the first order mutants used in the experiment. The percentage of produced equivalent mutants was about 4%.[...] Read more.
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