@inproceedings{50f6b085e11c488898119486c209db3f,
title = "Testing Against Non-deterministic FSMs: A Probabilistic Approach for Test Suite Minimization",
abstract = "The paper is devoted to model based testing against non-deterministic specifications. Such test derivation strategies are well developed, for example against non-deterministic Finite State Machines, however the length of the corresponding test suite can be exponential w.r.t. the number of specification states. We therefore discuss how a test suite can be minimized or reduced when certain level of guarantee concerning its fault coverage is still preserved. The main idea behind the approach is to augment the specification by assigning probabilities for the non-deterministic transitions and later on evaluate the probability of each test sequence to detect the relevant faulty implementation. Given a probability P which is user-defined, we propose an approach for minimizing a given exhaustive test suite TS such that, it stays exhaustive with the probability no less than P.",
keywords = "Guaranteed fault coverage, Model based testing, Non-deterministic finite state machines, Probabilistic approach",
author = "Natalia Kushik and Nina Yevtushenko and Jorge L{\'o}pez",
note = "Publisher Copyright: {\textcopyright} 2022, IFIP International Federation for Information Processing.; 33rd IFIP WG 6.1 International Conference on Testing Software Systems, ICTSS 2021 ; Conference date: 10-11-2021 Through 12-11-2021",
year = "2022",
month = jan,
day = "1",
doi = "10.1007/978-3-031-04673-5\_4",
language = "English",
isbn = "9783031046728",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "55--61",
editor = "David Clark and Hector Menendez and Cavalli, \{Ana Rosa\}",
booktitle = "Testing Software and Systems - 33rd IFIP WG 6.1 International Conference, ICTSS 2021, Proceedings",
}