{"department":[{"_id":"34"},{"_id":"355"},{"_id":"26"},{"_id":"63"},{"_id":"238"}],"publication":"Evolutionary Computation","citation":{"bibtex":"@article{Wever_van Rooijen_Hamann_2020, title={Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets}, volume={28}, DOI={<a href=\"https://doi.org/10.1162/evco_a_00266\">10.1162/evco_a_00266</a>}, number={2}, journal={Evolutionary Computation}, publisher={MIT Press Journals}, author={Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}, year={2020}, pages={165–193} }","ama":"Wever MD, van Rooijen L, Hamann H. Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. <i>Evolutionary Computation</i>. 2020;28(2):165–193. doi:<a href=\"https://doi.org/10.1162/evco_a_00266\">10.1162/evco_a_00266</a>","ieee":"M. D. Wever, L. van Rooijen, and H. Hamann, “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets,” <i>Evolutionary Computation</i>, vol. 28, no. 2, pp. 165–193, 2020, doi: <a href=\"https://doi.org/10.1162/evco_a_00266\">10.1162/evco_a_00266</a>.","chicago":"Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” <i>Evolutionary Computation</i> 28, no. 2 (2020): 165–193. <a href=\"https://doi.org/10.1162/evco_a_00266\">https://doi.org/10.1162/evco_a_00266</a>.","mla":"Wever, Marcel Dominik, et al. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” <i>Evolutionary Computation</i>, vol. 28, no. 2, MIT Press Journals, 2020, pp. 165–193, doi:<a href=\"https://doi.org/10.1162/evco_a_00266\">10.1162/evco_a_00266</a>.","short":"M.D. Wever, L. van Rooijen, H. Hamann, Evolutionary Computation 28 (2020) 165–193.","apa":"Wever, M. D., van Rooijen, L., &#38; Hamann, H. (2020). Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. <i>Evolutionary Computation</i>, <i>28</i>(2), 165–193. <a href=\"https://doi.org/10.1162/evco_a_00266\">https://doi.org/10.1162/evco_a_00266</a>"},"author":[{"id":"33176","orcid":" https://orcid.org/0000-0001-9782-6818","full_name":"Wever, Marcel Dominik","last_name":"Wever","first_name":"Marcel Dominik"},{"first_name":"Lorijn","id":"58843","full_name":"van Rooijen, Lorijn","last_name":"van Rooijen"},{"last_name":"Hamann","full_name":"Hamann, Heiko","first_name":"Heiko"}],"volume":28,"language":[{"iso":"eng"}],"date_created":"2019-11-18T14:19:19Z","user_id":"15415","project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B1","_id":"9"},{"name":"SFB 901 - Subproject B2","_id":"10"},{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"date_updated":"2022-01-06T06:52:15Z","abstract":[{"text":"In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available.","lang":"eng"}],"publication_status":"published","publisher":"MIT Press Journals","status":"public","title":"Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets","intvolume":"        28","_id":"15025","doi":"10.1162/evco_a_00266","issue":"2","related_material":{"link":[{"relation":"confirmation","url":"https://www.mitpressjournals.org/doi/pdf/10.1162/evco_a_00266"}]},"type":"journal_article","page":"165–193","year":"2020"}