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Automated Repair of Unrealisable LTL Specifications Guided by Model Counting., , , , and . CoRR, (2021)Learning To Predict Vulnerabilities From Vulnerability-Fixes: A Machine Translation Approach., , , , , and . CoRR, (2020)Test Selection for Deep Learning Systems., , , , and . ACM Trans. Softw. Eng. Methodol., 30 (2): 13:1-13:22 (2021)Test Data Generation Techniques for Mutation Testing: A Systematic Mapping., , , and . CIbSE, page 419-432. Curran Associates, (2014)An empirical study of async wait flakiness in front-end testing., , , , and . BENEVOL, volume 3245 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Confuzzion: A Java Virtual Machine Fuzzer for Type Confusion Vulnerabilities., , , , and . QRS, page 586-597. IEEE, (2021)Mart: a mutant generation tool for LLVM., , and . ESEC/SIGSOFT FSE, page 1080-1084. ACM, (2019)Validity fuzzing and parametric generators for effective random testing., , , , and . ICSE (Companion Volume), page 266-267. IEEE / ACM, (2019)MuDelta: Delta-Oriented Mutation Testing at Commit Time., , , and . ICSE, page 897-909. IEEE, (2021)Semantic fuzzing with zest., , , , and . ISSTA, page 329-340. ACM, (2019)