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KŘENA, B. ŠIMKOVÁ, H. UR, S. VOJNAR, T.
Original Title
Prediction of Coverage of Expensive Concurrency Metrics Using Cheaper Metrics
Type
conference paper
Language
English
Original Abstract
Testing of concurrent programs is difficult since the scheduling non-determinism requires one to test a huge number of different thread interleavings. Moreover, a simple repetition of test executions will typically examine similar interleavings only. One popular way how to deal with this problem is to use the noise injection approach, which is, however, parametrized with many parameters whose suitable values are difficult to find. To find such values, one needs to run many experiments and use some metric to evaluate them. Measuring the achieved coverage can, however, slow down the experiments. To minimize this problem, we show that there are correlations between metrics of different cost and that one can find a suitable test and noise setting to maximize coverage under a costly metrics by experiments with a cheaper metrics.
Keywords
parallel programs, noise-based testing, concurrency metrics, lasso algorithm, prediction
Authors
KŘENA, B.; ŠIMKOVÁ, H.; UR, S.; VOJNAR, T.
Released
19. 2. 2018
Publisher
Springer International Publishing
Location
Las Palmas
ISBN
978-3-319-74726-2
Book
Computer Aided Systems Theory - EUROCAST 2017
Edition
16th International Conference, Las Palmas de Gran Canaria, Spain, February 19-24, 2017, Revised Selected Papers, Part II
Pages from
99
Pages to
108
Pages count
10
URL
https://www.fit.vut.cz/research/publication/11650/
BibTex
@inproceedings{BUT146280, author="Bohuslav {Křena} and Hana {Šimková} and Shmuel {Ur} and Tomáš {Vojnar}", title="Prediction of Coverage of Expensive Concurrency Metrics Using Cheaper Metrics", booktitle="Computer Aided Systems Theory - EUROCAST 2017", year="2018", series="16th International Conference, Las Palmas de Gran Canaria, Spain, February 19-24, 2017, Revised Selected Papers, Part II", volume="10672", pages="99--108", publisher="Springer International Publishing", address="Las Palmas", doi="10.1007/978-3-319-74727-9\{_}12", isbn="978-3-319-74726-2", url="https://www.fit.vut.cz/research/publication/11650/" }