Practical Extensions of a Randomized Testing Tool

—Many efficient random testing algorithms for object-oriented software have been proposed due to their simplicity and reasonable code coverage; however, even the stateof-the-art random test algorithms yield very low code coverage (around 22%) on large-scale software. We propose four testing techniques to improve test coverage. The proposed techniques are pluggable to any existing random testing techniques for object-oriented software. We incorporated our techniques to a state-of-the-art random testing tool and tested large-scale software, including Java Collections, Apache Ant, and ASM. Our experimental study shows that the proposed techniques increase at most 21% of branch coverage – a significant improvement.

• Type: Conference
• Year: 2009
• Where: COMPSAC
• Authors: Hojun Jaygarl, Carl K. Chang, Sunghun Kim
• Keywords: COMPSAC 2009, Random Testing, Random Testing Algorithms, Software Engineering, Testing Techniques