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Mon 9 Nov 2020 19:30 - 20:00 at Virtual room 3 - Session 1 Chair(s): Tien N. Nguyen, Alexander Serebrenik

Unit testing focused on Modified Condition/Decision Coverage (MC/DC) criterion is essential in development safety-critical systems. However, design of test data that meets the MC/DC criterion currently needs detailed manual analysis of branching conditions in units under test by test engineers. Multiple state-of-art approaches exist with proven usage even in industrial projects. However, these approaches have multiple shortcomings, one of them being the Path explosion problem which has not been fully solved yet. Machine learning methods as meta-heuristic approximations can model behaviour of programs that are hard to test using traditional approaches, where the Path explosion problem does occur and thus could solve the limitations of the current state-of-art approaches. I believe, motivated by an ongoing collaboration with an industrial partner, that the machine learning methods could be combined with existing approaches to produce an approach suitable for testing of safety-critical projects

Mon 9 Nov
Times are displayed in time zone: (UTC) Coordinated Universal Time change

19:00 - 20:30: Session 1Doctoral Symposium at Virtual room 3
Chair(s): Tien N. NguyenUniversity of Texas at Dallas, Alexander SerebrenikEindhoven University of Technology

The names under the talk are displayed in the following order: 1) presenter and 2) author.

19:00 - 19:30
Doctoral Symposium
S: Ján ČegiňFaculty of Informatics and Information Technologies Slovak Technical University, A: Orges CicoNorwegian University of Science and Technology
19:30 - 20:00
Doctoral Symposium
S: Orges CicoNorwegian University of Science and Technology, A: Ján ČegiňFaculty of Informatics and Information Technologies Slovak Technical University
20:00 - 20:30
Doctoral Symposium
S: Zhendong WangUniversity of California, Irvine, A: Mairieli WesselUniversity of São Paulo