Modeling of railway logics for reverse enginering, verification and refactoring
2011 (English) In: International Journal of Safety and Security Engineering, ISSN 2041-9031, E-ISSN 2041-904X, Vol. 1, no 1, p. 77-94Article in journal (Refereed) Published
Abstract [en]
Model-based approaches are widespread both in functional and non-functional verification activities of critical computer-based systems. Reverse engineering can also be used to support checks for correctness of system implementation against its requirements. In this paper, we show how a model-based technique, using the Unified Modeling Language (UML), suits the reverse engineering of complex control logics. UML is usually exploited to drive the development of software systems, using an object-oriented and bottom-up approach; however, it can be also used to model legacy non-object-oriented logic processes featuring a clear distinction between data structures and related operations. Our case-study consists in the most important component of the European Railway Traffic Management System/European Train Control System: the Radio Block Center (RBC). The model we obtained from the logic code of the RBC significantly facilitated both structural and behavioral analyses, giving a valuable contribution to the static verification and refactoring of the software under test. © 2011 WIT Press.
Place, publisher, year, edition, pages WITPress , 2011. Vol. 1, no 1, p. 77-94
Keywords [en]
Control Software, Modeling, Railways, Refactoring, Reverse Engineering, Verification, Data structures, Models, Railroad traffic control, Railroads, Software testing, Unified Modeling Language, Complex control logic, Computer-based system, Refactorings, System implementation, Train control systems, Verification activities, control system, logistics, railway, railway construction, software, traffic management, train
National Category
Embedded Systems
Identifiers URN: urn:nbn:se:mdh:diva-47804 DOI: 10.2495/SAFE-V1-N1-77-94 Scopus ID: 2-s2.0-85010915123 OAI: oai:DiVA.org:mdh-47804 DiVA, id: diva2:1427366
2018-06-052020-04-29 Bibliographically approved