High-performance mutation testing
Journal of Systems and Software
Introduction to Java Programming Using Jbuilder 4/5/6
Introduction to Java Programming Using Jbuilder 4/5/6
Multi-environment software testing on the grid
Proceedings of the 2006 workshop on Parallel and distributed systems: testing and debugging
Software Testing Research: Achievements, Challenges, Dreams
FOSE '07 2007 Future of Software Engineering
Parallel test generation and execution with Korat
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Software engineering for multicore systems: an experience report
Proceedings of the 1st international workshop on Multicore software engineering
Building Parallel Programs: SMPs, Clusters & Java
Building Parallel Programs: SMPs, Clusters & Java
Jartege: a tool for random generation of unit tests for java classes
QoSA'05 Proceedings of the First international conference on Quality of Software Architectures and Software Quality, and Proceedings of the Second International conference on Software Quality
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The power of parallel computing needs to be exploited on software testing because of challenges that remain today, such improving test effectiveness and automating test input generation. There has been research on applying parallel computing to software testing, but there are still areas where the power of parallel computers can be exploited. Another challenge which has remained due to the lack of tool support is the oracle problem. We want to be relieved of tedious and manual processes in software testing. This paper proposes a framework for parallel unit testing. To alleviate the oracle problem, we will use the Java Modeling Language as the test oracle. We will take advantage of the power of parallel computing and apply it to random unit testing of Java classes to overcome some of today's challenges. We believe that random testing can be used to help us achieve this goal because it is effective and also cost-effective. We will show that we can overcome these challenges by generating and executing more test cases in the same amount of time, and by implementing data diversity. Our framework will be extensible to support additional programming languages and technique diversity.