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An experimental study of methods for executing test suites in memory constrained environments

empirical study
test execution
Proceedings of the 4th International Workshop on the Automation of Software Test
Authors

Suvarshi Bhadra

Alexander P. Conrad

Charles P. Hurkes

Brian Kirklin

Gregory M. Kapfhammer

Published

2009

Abstract
Software for memory constrained mobile devices is often implemented in the Java programming language because the Java compiler and virtual machine (JVM) provide enhanced safety, portability, and the potential for run-time optimization. However, testing time may increase substantially when memory is limited and the JVM employs a compiler to create native code bodies. This paper furnishes an empirical study that identifies the fundamental trade-offs associated with a method that uses adaptive native code unloading to perform memory constrained testing. The experimental results demonstrate that code unloading can reduce testing time by 17% and the code size of the test suite and application under test by 68% while maintaining the overall size of the JVM. We also find that the goal of reducing the space overhead of an automated testing technique is often at odds with the objective of decreasing the time required to test. Additional experiments reveal that using a complete record of test suite behavior, in contrast to a sample-based profile, does not enable the code unloader to make decisions that markedly reduce testing time. Finally, we identify test suite and application behaviors that may limit the effectiveness of our method for memory constrained test execution and we suggest ways to mitigate these challenges.
Details

Paper
Presentation
Presentation

Reference
@inproceedings{Bhadra2009,
 author = {Suvarshi Bhadra and Alexander P. Conrad and Charles P. Hurkes and
Brian Kirklin and Gregory M. Kapfhammer},
 booktitle = {Proceedings of the 4th International Workshop on the Automation
of Software Test},
 title = {An experimental study of methods for executing test suites in memory
constrained environments},
 year = {2009}
}

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