Detail publikace

Application of Evolutionary Algorithms for Optimization of Regression Suites

Originální název

Application of Evolutionary Algorithms for Optimization of Regression Suites

Anglický název

Application of Evolutionary Algorithms for Optimization of Regression Suites

Jazyk

en

Originální abstrakt

Regression test suites are necessary to ensure that changes to the system made after bug fixes or reimplementation have not broken the intended functionality. However, because of the complexity of current hardware systems, it is desirable to have optimized regression suites that provide the highest verification coverage with minimal simulation time and resources. In this paper, we introduce a coverage-directed optimization algorithm for creating optimized regression suites from verification stimuli that were evaluated in simulation-based verification environment. The results of our experiments show that the quality and the size of the final regression suites are significantly improved in comparison to the original test suit. For our experimental system, we were able to eliminate 94.4% redundant stimuli from the original test suite while retaining the same level of functional coverage.

Anglický abstrakt

Regression test suites are necessary to ensure that changes to the system made after bug fixes or reimplementation have not broken the intended functionality. However, because of the complexity of current hardware systems, it is desirable to have optimized regression suites that provide the highest verification coverage with minimal simulation time and resources. In this paper, we introduce a coverage-directed optimization algorithm for creating optimized regression suites from verification stimuli that were evaluated in simulation-based verification environment. The results of our experiments show that the quality and the size of the final regression suites are significantly improved in comparison to the original test suit. For our experimental system, we were able to eliminate 94.4% redundant stimuli from the original test suite while retaining the same level of functional coverage.

BibTex


@inproceedings{BUT119863,
  author="Michaela {Belešová} and Marcela {Zachariášová} and Zdeněk {Kotásek} and Tomáš {Hruška}",
  title="Application of Evolutionary Algorithms for Optimization of Regression Suites",
  annote="Regression test suites are necessary to ensure that
changes to the system made after bug fixes or reimplementation
have not broken the intended functionality. However, because of
the complexity of current hardware systems, it is desirable to have optimized
regression suites that provide the highest verification coverage with minimal
simulation time and resources. In this paper, we introduce a coverage-directed
optimization algorithm for creating optimized regression suites from verification
stimuli that were evaluated in simulation-based verification environment. The
results of our experiments show that the quality and the size of the final
regression suites are significantly improved in comparison to the original test
suit. For our experimental system, we were able to eliminate 94.4% redundant
stimuli from the original test suite while retaining the same level of functional
coverage.",
  address="IEEE Computer Society",
  booktitle="IEEE 18th International Symposium on Design and Diagnostics of Electronic Circuits and Systems",
  chapter="119863",
  doi="10.1109/DDECS.2015.42",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Computer Society",
  year="2015",
  month="april",
  pages="91--94",
  publisher="IEEE Computer Society",
  type="conference paper"
}