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Automatic Generation of Object Usage Specifications from Large Method Traces.

, and . ASE, page 371-382. IEEE Computer Society, (2009)

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Bita: Coverage-guided, automatic testing of actor programs., , , and . ASE, page 114-124. IEEE, (2013)Poster: Automatically Fixing Real-World JavaScript Performance Bugs., and . ICSE (2), page 811-812. IEEE Computer Society, (2015)ISBN 978-1-4799-1934-5 (Vol. I + II ???).Ballerina: Automatic generation and clustering of efficient random unit tests for multithreaded code., , , , and . ICSE, page 727-737. IEEE Computer Society, (2012)Neural Bug Finding: A Study of Opportunities and Challenges., and . CoRR, (2019)Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts., , and . CoRR, (2018)Systematic black-box analysis of collaborative web applications., , and . PLDI, page 171-184. ACM, (2017)Interactive metamorphic testing of debuggers., , and . ISSTA, page 273-283. ACM, (2019)NL2Type: inferring JavaScript function types from natural language information., , and . ICSE, page 304-315. IEEE / ACM, (2019)Performance Issues and Optimizations in JavaScript: An Empirical Study., and . Software Engineering, volume P-267 of LNI, page 63. GI, (2017)EventBreak: Analyzing the Responsiveness of User Interfaces through Performance-Guided Test Generation., , , and . Software Engineering & Management, volume P-239 of LNI, page 131. GI, (2015)