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dc.contributor.authorPourali, Parsa
dc.contributor.authorAtlee, Joanne M.
dc.date.accessioned2019-12-23 15:33:04 (GMT)
dc.date.available2019-12-23 15:33:04 (GMT)
dc.date.issued2018-10
dc.identifier.urihttps:/doi.org/10.1145/3239372.3239400
dc.identifier.urihttp://hdl.handle.net/10012/15370
dc.description.abstractSoftware modelling is a challenging and error-prone task. Existing Model-Driven Engineering (MDE) tools provide modellers with little aid, partly because tool providers have not investigated users' difficulties through empirical investigations such as field studies. This paper presents the results of a two-phase user study to identify the most prominent difficulties that users might face when developing UML Class and State-Machine diagrams using UML modelling tools. In the first phase, we identified the preliminary modelling challenges by analysing 30 Class and State-Machine models that were previously developed by students as a course assignment. The result of the first phase helped us design the second phase of our user study where we empirically investigated different aspects of using modelling tools: the tools' effectiveness, users' efficiency, users' satisfaction, the gap between users' expectation and experience, and users' cognitive difficulties. Our results suggest that users' greatest difficulties are in (1) remembering contextual information and (2) identifying and fixing errors and inconsistencies.en
dc.description.sponsorshipNSERC CREATE, 465463-2015 || NSERC Discovery Grant, 155243-12en
dc.language.isoenen
dc.publisherACMen
dc.titleAn Empirical Investigation to Understand the Difficulties and Challenges of Software Modellers When Using Modelling Toolsen
dc.typeConference Paperen
dcterms.bibliographicCitationParsa Pourali and Joanne M. Atlee. 2018. An Empirical Investigation to Understand the Difficulties and Challenges of Software Modellers When Using Modelling Tools. In Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS '18). ACM, New York, NY, USA, 224-234.en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2David R. Cheriton School of Computer Scienceen
uws.contributor.affiliation2Electrical and Computer Engineeringen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.scholarLevelGraduateen


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