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- W3048292777 abstract "Search-based test data generation approaches have come a long way over the past few years, but these approaches still have some limitations when it comes to exercising specific behavior for triggering particular kinds of faults (e.g., crashes or specific types of integration between classes/modules). In this thesis, we are investigating new fitness functions and evolutionary-based algorithms and techniques to tackle these limitations. We have defined multiple novel approaches for crash reproduction and class integration testing. Currently, we are still working on improving both crash reproduction and class integration testing." @default.
- W3048292777 created "2020-08-13" @default.
- W3048292777 creator A5034023299 @default.
- W3048292777 date "2020-10-01" @default.
- W3048292777 modified "2023-10-18" @default.
- W3048292777 title "Well-informed Test Case Generation and Crash Reproduction" @default.
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- W3048292777 doi "https://doi.org/10.1109/icst46399.2020.00054" @default.
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