Print Email Facebook Twitter An Experience Report on Applying Passive Learning in a Large-Scale Payment Company Title An Experience Report on Applying Passive Learning in a Large-Scale Payment Company Author Wieman, Rick (External organisation) Aniche, Maurício (TU Delft Software Engineering) Lobbezoo, Willem (Adyen B.V.) Verwer, S.E. (TU Delft Cyber Security) van Deursen, A. (TU Delft Software Technology) Department Software Technology Date 2017 Abstract Passive learning techniques infer graph models on the behavior of a system from large trace logs. The research community has been dedicating great effort in making passive learning techniques more scalable and ready to use by industry. However, there is still a lack of empirical knowledge on the usefulness and applicability of such techniques in large scale real systems. To that aim, we conducted action research over nine months in a large payment company. Throughout this period, we iteratively applied passive learning techniques with the goal of revealing useful information to the development team. In each iteration, we discussed the findings and challenges to the expert developer of the company, and we improved our tools accordingly. In this paper, we present evidence that passive learning can indeed support development teams, a set of lessons we learned during our experience, a proposed guide to facilitate its adoption, and current research challenges. Subject passive learningexperience reportdfasat To reference this document use: http://resolver.tudelft.nl/uuid:b463c54a-d69f-4db4-9fcc-cbeb6e2ddf09 DOI https://doi.org/10.1109/ICSME.2017.71 Publisher IEEE, Los Alamitos, CA ISBN 78-1-5386-0992-7 Source Proceedings - 2017 IEEE International Conference on Software Maintenance and Evolution, ICSME 2017 Event ICSME 2017, 2017-09-17 → 2017-09-24, Shanghai, China Part of collection Institutional Repository Document type conference paper Rights © 2017 Rick Wieman, Maurício Aniche, Willem Lobbezoo, S.E. Verwer, A. van Deursen Files PDF icsme2017.pdf 563.93 KB Close viewer /islandora/object/uuid:b463c54a-d69f-4db4-9fcc-cbeb6e2ddf09/datastream/OBJ/view