- author = "Valerio Terragni and Gunel Jahangirova and Mauro Pezze and Paolo Tonella",
- title = "Improving Assertion Oracles with Evolutionary Computation",
- booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference Companion",
- series = "GECCO '21",
- year = "2021",
- editor = "Carola Doerr",
- month = "10-14 " # jul,
- pages = "45--46",
- organisation = "SIGEVO",
- address = "Internet",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE, Evolutionary Computation, Program Assertions, Test Generation, Mutation Analysis, Co-evolutionary Algorithms, Daikon, coevolution, Randoop",
- isbn13 = "978-1-4503-8351-6",
-
DOI = "
doi:10.1145/3449726.3462722",
- size = "2 pages",
- abstract = "Assertion oracles are executable Boolean expressions placed inside a software program that verify the correctness of test executions. A perfect assertion oracle passes (returns true) for all correct executions and fails (returns false) for all incorrect executions. Because designing perfect assertion oracles is difficult, assertions often fail to distinguish between correct and incorrect executions. In other words, they are prone to false positives and false negatives. GAssert is the first technique to automatically improve assertion oracles by reducing false positives and false negatives. Given an assertion oracle and a set of correct and incorrect program states, GAssert employs a novel co-evolutionary algorithm that explores the space of possible assertions to identify one with fewer false positives and false negatives. Our evaluation on 34 Java methods shows that GAssert effectively improves assertion oracles.",
-
notes = "Short version of \cite{terragni-fse-2020}
University of Auckland",
