Toward Harnessing High-Level Language Virtual Machines for Further Speeding Up Weak Mutation Testing

Abstract

Abstract-High-level language virtual machines (HLL VMs) are now widely used to implement high-level programming languages. To a certain extent, their widespread adoption is due to the software engineering benefits provided by these managed execution environments, for example, garbage collection (GC) and cross-platform portability. Although HLL VMs are widely used, most research has concentrated on high-end optimizations such as dynamic compilation and advanced GC techniques. Few efforts have focused on introducing features that automate or facilitate certain software engineering activities, including software testing. This paper suggests that HLL VMs provide a reasonable basis for building an integrated software testing environment. As a proof-of-concept, we have augmented a Java virtual machine (JVM) to support weak mutation analysis. Our mutation-aware HLL VM capitalizes on the relationship between a program execution and the underlying managed execution environment, thereby speeding up the execution of the program under test and its associated mutants. To provide some evidence of the performance of our implementation, we conducted an experiment to compare the efficiency of our VM-based implementation with a strong mutation testing tool (muJava). Experimental results show that the VM-based implementation achieves speedups of as much as 89% in some cases.

Mutation Testing Advances: An Analysis and Survey

“…Other approaches involve the use of interpreted systems, such as the ones used by symbolic evaluation engines [149]. A possible realisation of this attempt is to harness the Java virtual machines in order to control and introduce the mutants [150]. Finally, Devroey et al [151] suggested encoding all mutants as a product line.…”

“…Thus, instead of executing every mutant with every test, it is possible to execute all mutants at once, by monitoring the coverage of the infection conditions. Durelli et al [150] suggested harnessing the Java virtual machine instead of schematic functions in order to record the mutant infection conditions. Both these methods resulted in major speed-ups (up to 5 times).…”

Mutant Selecting According to the Nondominated Original Statements

“…To speed up weak mutation testing, Durelli et al constructed virtual machine-integrated environment for mutation testing [18]. By using the high speed of noninterpretive system, Kim et al developed a Java mutation system to save the cost in weak mutation testing [19].…”

Dynamic Radius Species Conserving Genetic Algorithm for Test Generation for Structural Testing

“…Ammann and Offutt argue in [20] that it is a good algorithm for software testing research because it is easy to understand, relatively small yet very complex in terms of paths. In 2012 it was used in [21] for research in mutation testing. It has been used in Master's Thesis [22] and Doctoral Dissertations [23].…”