Approaches to Semantic Mutation of Behavioral State Machines in Model-Driven Software Development

Anna Derezińska , Łukasz Zaremba

Abstract

Behavior of UML state machines can be a source of interpretation problems in model to code transformation. Different solutions to the semantic variants could be defined as a special kind of mutations, similarly as in the mutation testing. State machines together with class models can be a source of an Model-Driven Software Development process aimed at building an executable application. We have compared several approaches to creating applications based on models in which semantic mutation operators of state machine behavior are used. The most promising approach has been utilized to extend the Framework for eXecutable UML (FXU) with semantic mutation facilities. The framework supports code generation from UML classes and their state machines as well as developing C# applications according to selected mutations of state machine behavior. The tool has been used in evaluation of a case study.
Author Anna Derezińska (FEIT / IN)
Anna Derezińska,,
- The Institute of Computer Science
, Łukasz Zaremba
Łukasz Zaremba,,
-
Pages863-866
Publication size in sheets0.5
Book Ganzha Maria, Maciaszek Leszek A., Paprzycki Marcin (eds.): Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, Annals of Computer Science and Information Systems, vol. 15, 2018, Institute of Electrical and Electronics Engineers, IEEE, PTI, ISBN 978-83-949419-5-6, [978-83-949419-6-3, 978-83-949419-7-0], 1112 p., DOI:10.15439/978-83-949419-5-6
DOIDOI:10.15439/2018F313
URL https://annals-csis.org/proceedings/2018/drp/313.html
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Arabas Jarosław, , Phone: +48 22 234 7432, start date 01-06-2017, end date 31-10-2018, II/2017/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
File
ADerezFedCSIS2018_313.pdf 190.72 KB
Score (nominal)15
ScoreMinisterial score = 15.0, 10-07-2019, ChapterFromConference
Publication indicators Scopus Citations = 1; WoS Citations = 0
Citation count*1 (2019-08-19)
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