ADISSA: architectural design of information systems based on structures analysis
Information Systems
Object-oriented modeling and design
Object-oriented modeling and design
Comparing data modeling formalisms
Communications of the ACM
Effects of data model and task characteristics on designer performance: a laboratory study
International Journal of Human-Computer Studies
Entity-relationship and object-oriented data modeling—an experimental comparison of design quality
Data & Knowledge Engineering
IEEE Transactions on Software Engineering
Object-Process Methodology: A Holistic Systems Paradigm
Object-Process Methodology: A Holistic Systems Paradigm
The Model Multiplicity Problem: Experimenting with Real-Time Specification Methods
IEEE Transactions on Software Engineering
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
The application of FOOM methodology to IFIP conference case study
Practicing software engineering in the 21st century
Basics of Software Engineering Experimentation
Basics of Software Engineering Experimentation
Information Sciences: an International Journal
Quality and comprehension of UML interaction diagrams-an experimental comparison
Information and Software Technology
A method for development of adequate requirement specification in the plant control software domain
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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FOOM-Functional and Object Oriented Methodology-combines two essential software-engineering paradigms: the functional (or process-oriented) approach and the object-oriented (OO) approach. The two main products of the analysis phase of FOOM are an initial class diagram and OO-DFDs (dataflow diagrams including data classes rather than traditional data-stores). We evaluated these analysis products by comparing them with the analysis products of OPM-Object-Process Methodology-which also combines the functional and object-oriented approaches, using a unified diagrammatic notation. FOOM and OPM were compared in two controlled experiments from two main points of view: users and analysts. From the point of view of users we compared mainly comprehension of analysis specifications in each methodology. From the point of view of analysts we compared mainly quality, namely correctness of specifications created by analysts who utilized the two methodologies. The main results of the experiments are that FOOM specifications are more comprehensible and preferred by users, and that analysts create more correct specifications when using FOOM methodology.