Print Email Facebook Twitter Guess What Title Guess What: Test Case Generation for Javascript with Unsupervised Probabilistic Type Inference Author Stallenberg, D.M. (TU Delft Software Engineering) Olsthoorn, Mitchell (TU Delft Software Engineering) Panichella, A. (TU Delft Software Engineering) Contributor Papadakis, Mike (editor) Vergilio, Silvia Regina (editor) Date 2022 Abstract Search-based test case generation approaches make use of static type information to determine which data types should be used for the creation of new test cases. Dynamically typed languages like JavaScript, however, do not have this type information. In this paper, we propose an unsupervised probabilistic type inference approach to infer data types within the test case generation process. We evaluated the proposed approach on a benchmark of 98~units under test (i.e., exported classes and functions) compared to random type sampling w.r.t. branch coverage. Our results show that our type inference approach achieves a statistically significant increase in 56% of the test files with up to 71% of branch coverage compared to the baseline. To reference this document use: http://resolver.tudelft.nl/uuid:4e3d1119-7815-4b0b-87eb-558c78aca94d DOI https://doi.org/10.1007/978-3-031-21251-2_5 Publisher Springer, Cham Embargo date 2023-05-15 ISBN 978-3-031-21250-5 Source Search-Based Software Engineering - 14th International Symposium, SSBSE 2022, Proceedings: 14th International Symposium, SSBSE 2022, Proceedings (1) Event 14th Symposium on Search-based Software Engineering, 2022-11-17 → 2022-11-18, Singapore, Singapore, Singapore Series Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 0302-9743, 13711 LNCS Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type conference paper Rights © 2022 D.M. Stallenberg, Mitchell Olsthoorn, A. Panichella Files PDF 978_3_031_21251_2_5.pdf 551.6 KB Close viewer /islandora/object/uuid:4e3d1119-7815-4b0b-87eb-558c78aca94d/datastream/OBJ/view