Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Cedric Richter"'
Autor:
Matthias Becker, Steffen Becker, Eyke Hüllermeier, Cedric Richter, Arnab Sharma, Heike Wehrheim
Book chapter of subproject B3 within the final book of the Collaborative Research Center 901 published within the series "Verlagsschriftenreihe des Heinz Nixdorf Instituts", volume 412, ISBN 978-3-947647-31-6, June 2023.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4ca753df7e45722285a90f1ab87ef75
Publikováno v:
Fundamental Approaches to Software Engineering ISBN: 9783031308253
Ranged symbolic execution has been proposed as a way of scaling symbolic execution by splitting the task of path exploration onto several workers running in parallel. The split is conducted along path ranges which – simply speaking – describe set
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1478849dfa7b72d17096e4dbea69185b
https://doi.org/10.1007/978-3-031-30826-0_11
https://doi.org/10.1007/978-3-031-30826-0_11
Autor:
Cedric Richter, Jan Haltermann, Marie-Christine Jakobs, Felix Pauck, Stefan Schott, Heike Wehrheim
Publikováno v:
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e21ec80b3b4c8fd98f1d6b7bb9c756b3
https://doi.org/10.1145/3551349.3561156
https://doi.org/10.1145/3551349.3561156
Autor:
Cedric Richter, Heike Wehrheim
Publikováno v:
2022 IEEE Conference on Software Testing, Verification and Validation (ICST).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c16bee6ea9052fa2f32707ebd73d9a2d
https://doi.org/10.1109/icst53961.2022.00027
https://doi.org/10.1109/icst53961.2022.00027
Publikováno v:
Automated Software Engineering. 27:153-186
Algorithm selection is the task of choosing an algorithm from a given set of candidate algorithms when faced with a particular problem instance. Algorithm selection via machine learning (ML) has recently been successfully applied for various problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7043b7daeb154faa72457e32d5b8884b
https://doi.org/10.1007/s10515-020-00270-x
https://doi.org/10.1007/s10515-020-00270-x
Publikováno v:
Fundamental Approaches to Software Engineering ISBN: 9783030994280
Software verifiers have different strengths and weaknesses, depending on properties of the verification task. It is well-known that combinations of verifiers via portfolio and selection approaches can help to combine the strengths. In this paper, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44c5b70c14be684108e6f900bb3869ff
https://doi.org/10.1007/978-3-030-99429-7_3
https://doi.org/10.1007/978-3-030-99429-7_3
Autor:
Marie-Christine Jakobs, Cedric Richter
Publikováno v:
Fundamental Approaches to Software Engineering ISBN: 9783030714994
FASE
FASE
CoVeriTest, which is integrated in the analysis framework CPAchecker, adopts verification technology for test-case generation. It encodes individual test goals as reachability queries, which are then processed by verifiers. To increase the effectiven
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12569cea73fb7b834dcc3521757add8d
https://doi.org/10.1007/978-3-030-71500-7_18
https://doi.org/10.1007/978-3-030-71500-7_18
Autor:
Cedric Richter, Heike Wehrheim
Publikováno v:
ASE
Today, a plethora of different software verification tools exist. When having a concrete verification task at hand, software developers thus face the problem of algorithm selection. Existing algorithm selectors for software verification typically use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a3f805d167b27536d5cc8fa55b9f57c
https://doi.org/10.1145/3324884.3416633
https://doi.org/10.1145/3324884.3416633
Autor:
Heike Wehrheim, Cedric Richter
Publikováno v:
Tools and Algorithms for the Construction and Analysis of Systems ISBN: 9783030175016
TACAS (3)
TACAS (3)
PeSCo is a tool for predicting a (likely best) sequential combination of verifiers on a given verification task and then running it. The approach is based on machine learning, more precisely on learning rankings of verifiers on verification tasks (wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb41baeae7427d912a3ea95efc5002f9
https://doi.org/10.1007/978-3-030-17502-3_19
https://doi.org/10.1007/978-3-030-17502-3_19