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Softw. Eng. Methodol."],"published-print":{"date-parts":[[2024,3,31]]},"abstract":"<jats:p>The field of software verification has produced a wide array of algorithmic techniques that can prove a variety of properties of a given program. It has been demonstrated that the performance of these techniques can vary up to 4 orders of magnitude on the same verification problem. Even for verification experts, it is difficult to decide which tool will perform best on a given problem. For general users, deciding the best tool for their verification problem is effectively impossible.<\/jats:p>\n          <jats:p>\n            In this work, we present\n            <jats:sc>Graves<\/jats:sc>\n            , a selection strategy based on graph neural networks (GNNs).\n            <jats:sc>Graves<\/jats:sc>\n            generates a graph representation of a program from which a GNN predicts a score for a verifier that indicates its performance on the program.\n          <\/jats:p>\n          <jats:p>\n            We evaluate\n            <jats:sc>Graves<\/jats:sc>\n            on a set of 10 verification tools and over 8,000 verification problems and find that it improves the state-of-the-art in verification algorithm selection by 12%, or 8 percentage points. Further, it is able to verify 9% more problems than any existing verifier on our test set. Through a qualitative study on model interpretability, we find strong evidence that the\n            <jats:sc>Graves<\/jats:sc>\n            model learns to base its predictions on factors that relate to the unique features of the algorithmic techniques.\n          <\/jats:p>","DOI":"10.1145\/3637225","type":"journal-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T11:26:45Z","timestamp":1702294005000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Algorithm\u00a0Selection for Software Verification Using Graph Neural Networks"],"prefix":"10.1145","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2403-9295","authenticated-orcid":false,"given":"Will","family":"Leeson","sequence":"first","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1937-1544","authenticated-orcid":false,"given":"Matthew B.","family":"Dwyer","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, VA, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,3,14]]},"reference":[{"key":"e_1_3_4_2_2","unstructured":"2019. 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