Detail publikačního výsledku

Application of Evolutionary Algorithms for Optimization of Regression Suites

KEKELYOVÁ, M.; ZACHARIÁŠOVÁ, M.; KOTÁSEK, Z.; HRUŠKA, T.

Originální název

Application of Evolutionary Algorithms for Optimization of Regression Suites

Anglický název

Application of Evolutionary Algorithms for Optimization of Regression Suites

Druh

Stať ve sborníku v databázi WoS či Scopus

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.

Klíčová slova

genetic algorithm
optimization
regression tests

Klíčová slova v angličtině

genetic algorithm
optimization
regression tests

Autoři

KEKELYOVÁ, M.; ZACHARIÁŠOVÁ, M.; KOTÁSEK, Z.; HRUŠKA, T.

Rok RIV

2016

Vydáno

22.04.2015

Nakladatel

IEEE Computer Society

Místo

Belgrade

ISBN

978-1-4799-6779-7

Kniha

IEEE 18th International Symposium on Design and Diagnostics of Electronic Circuits and Systems

Strany od

91

Strany do

94

Strany počet

4

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",
  booktitle="IEEE 18th International Symposium on Design and Diagnostics of Electronic Circuits and Systems",
  year="2015",
  pages="91--94",
  publisher="IEEE Computer Society",
  address="Belgrade",
  doi="10.1109/DDECS.2015.42",
  isbn="978-1-4799-6779-7"
}