Issue No. 08 - August (2000 vol. 26)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/32.879812
<p><b>Abstract</b>—The Object-Process Methodology (OPM) specifies both graphically and textually the system's static-structural and behavioral-procedural aspects through a single unifying model. This model singularity is contrasted with the multimodel approach applied by existing object-oriented system analysis methods. These methods usually employ at least three distinct models for specifying various system aspects—mainly structure, function, and behavior. Object Modeling Technique (OMT), the main ancestor of the Unified Modeling Language (UML), extended with Timed Statecharts, represents a family of such multimodel object-oriented methods. Two major open questions related to model multiplicity vs. model singularity have been 1) whether or not a single model, rather than a combination of several models, enables the synthesis of a better system specification and 2) which of the two alternative approaches yields a specification that is easier to comprehend. In this study, we address these questions through a double-blind controlled experiment. To obtain conclusive results, real-time systems, which exhibit a more complex dynamic behavior than nonreal-time systems were selected as the focus of the experiment. We establish empirically that a single model methodology—OPM—is more effective than a multimodel one—OMT—in terms of synthesis. We pinpoint specific issues in which significant differences between the two methodologies were found. The specification comprehension results show that there were significant differences between the two methods in specific issues.</p>
Analysis and design methodologies, real-time systems specification, object-oriented analysis, experimentation, quality of analysis, object-process methodology, software engineering, and empirical evaluation.
M. Peleg and D. Dori, "The Model Multiplicity Problem: Experimenting with Real-Time Specification Methods," in IEEE Transactions on Software Engineering, vol. 26, no. , pp. 742-759, 2000.