{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:03:09Z","timestamp":1760101389814,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031156281"},{"type":"electronic","value":"9783031156298"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-15629-8_20","type":"book-chapter","created":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T16:26:53Z","timestamp":1664036813000},"page":"371-381","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learning Language Intersections"],"prefix":"10.1007","author":[{"given":"Sebastian","family":"Junges","sequence":"first","affiliation":[]},{"given":"Jurriaan","family":"Rot","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"issue":"2","key":"20_CR1","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/0890-5401(87)90052-6","volume":"75","author":"D Angluin","year":"1987","unstructured":"Angluin, D.: Learning regular sets from queries and counterexamples. Inf. Comput. 75(2), 87\u2013106 (1987)","journal-title":"Inf. Comput."},{"key":"20_CR2","unstructured":"Caulfield, B., Seshia, S.A.: Modularity in query-based concept learning. CoRR, abs\/1911.02714 (2019)"},{"key":"20_CR3","unstructured":"Fiterau-Brostean, P.: Active Model Learning for the Analysis of Network Protocols. Ph.D thesis, Radboud University, April (2018)"},{"key":"20_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-3-319-96562-8_5","volume-title":"Machine Learning for Dynamic Software Analysis: Potentials and Limits","author":"F Howar","year":"2018","unstructured":"Howar, F., Steffen, B.: Active automata learning in practice. In: Bennaceur, A., H\u00e4hnle, R., Meinke, K. (eds.) Machine Learning for Dynamic Software Analysis: Potentials and Limits. LNCS, vol. 11026, pp. 123\u2013148. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-96562-8_5"},{"key":"20_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/978-3-319-11164-3_26","volume-title":"Runtime Verification","author":"M Isberner","year":"2014","unstructured":"Isberner, M., Howar, F., Steffen, B.: The TTT algorithm: a redundancy-free approach to active automata learning. In: Bonakdarpour, B., Smolka, S.A. (eds.) RV 2014. LNCS, vol. 8734, pp. 307\u2013322. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-11164-3_26"},{"key":"20_CR6","unstructured":"Lauffer, N., Yalcinkaya, B., Vazquez-Chanlatte, M., Shah, A., Seshia, S.A.: Learning deterministic finite automata decompositions from examples and demonstrations. CoRR, abs\/2205.13013 (2022)"},{"key":"20_CR7","unstructured":"Moerman, J.: Learning product automata. In: ICGI, volume 93 of Proceedings of Machine Learning Research, pp. 54\u201366. PMLR (2018)"},{"key":"20_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/978-3-030-88885-5_5","volume-title":"Automated Technology for Verification and Analysis","author":"E Mu\u0161kardin","year":"2021","unstructured":"Mu\u0161kardin, E., Aichernig, B.K., Pill, I., Pferscher, A., Tappler, M.: AALpy: an active automata learning library. In: Hou, Z., Ganesh, V. (eds.) ATVA 2021. LNCS, vol. 12971, pp. 67\u201373. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88885-5_5"},{"issue":"2","key":"20_CR9","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1145\/2967606","volume":"60","author":"F Vaandrager","year":"2017","unstructured":"Vaandrager, F.: Model learning. Commun. ACM 60(2), 86\u201395 (2017)","journal-title":"Commun. ACM"},{"key":"20_CR10","doi-asserted-by":"publisher","unstructured":"Vaandrager, F., Garhewal, B., Rot, J., Wi\u00dfmann, T.: A new approach for active automata learning based on apartness. In: TACAS, volume 13243 of LNCS, pp. 223\u2013243. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-030-99524-9_12","DOI":"10.1007\/978-3-030-99524-9_12"},{"key":"20_CR11","unstructured":"Marcell Vazquez-Chanlatte. dfa: A python library for deterministic finite automata. https:\/\/github.com\/mvcisback\/dfa"}],"container-title":["Lecture Notes in Computer Science","A Journey from Process Algebra via Timed Automata to Model Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-15629-8_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,24]],"date-time":"2022-09-24T16:31:58Z","timestamp":1664037118000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-15629-8_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031156281","9783031156298"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-15629-8_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"7 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}