Assessing the quality of tabular state machines through metrics.

A.A.H. Osaiweran, J. Marincic, J.F. Groote

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

Software metrics are widely used to measure the quality of software and to give an early indication of the efficiency of the development process in industry. There are many well-established frameworks for measuring the quality of source code through metrics, but limited attention has been paid to the quality of software models. In this article, we evaluate the quality of state machine models specified using the Analytical Software Design (ASD) tooling. We discuss how we applied a number of metrics to ASD models in an industrial setting and report about results and lessons learned while collecting these metrics. Furthermore, we recommend some quality limits for each metric and validate them on models developed in a number of industrial projects.
Originele taal-2Engels
TitelProceedings - 2017 IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
Plaats van productie Piscataway
UitgeverijIEEE Press
Pagina's426-433
Aantal pagina's8
ISBN van elektronische versie978-1-5386-0592-9
ISBN van geprinte versie978-1-5386-0593-6
DOI's
StatusGepubliceerd - 11 aug 2017
Evenement2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) - Prague, Tsjechië
Duur: 25 jul 201729 jul 2017

Congres

Congres2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)
LandTsjechië
StadPrague
Periode25/07/1729/07/17

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  • Citeer dit

    Osaiweran, A. A. H., Marincic, J., & Groote, J. F. (2017). Assessing the quality of tabular state machines through metrics. In Proceedings - 2017 IEEE International Conference on Software Quality, Reliability and Security, QRS 2017 (blz. 426-433). [8009946] IEEE Press. https://doi.org/10.1109/QRS.2017.52