An Ontological Model of an Information System
IEEE Transactions on Software Engineering
Journal of Management Information Systems
Anchoring data quality dimensions in ontological foundations
Communications of the ACM
Applied software measurement (2nd ed.): assuring productivity and quality
Applied software measurement (2nd ed.): assuring productivity and quality
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Software development cost estimation approaches – A survey
Annals of Software Engineering
Commonality and Variability in Software Engineering
IEEE Software
Function Point Analysis: Difficulties and Improvements
IEEE Transactions on Software Engineering
Software Development Cost Estimation Using Function Points
IEEE Transactions on Software Engineering
Should Optional Properties Be Used in Conceptual Modelling? A Theory and Three Empirical Tests
Information Systems Research
Research Commentary: Information Systems and Conceptual Modeling--A Research Agenda
Information Systems Research
Using ontology to validate conceptual models
Communications of the ACM - Service-oriented computing
Agile Estimating and Planning
Ontology based object-oriented domain modelling: fundamental concepts
Requirements Engineering
IEEE Transactions on Software Engineering
Software Product Line Engineering: Foundations, Principles and Techniques
Software Product Line Engineering: Foundations, Principles and Techniques
Complexity and clarity in conceptual modeling: comparison of mandatory and optional properties
Data & Knowledge Engineering - Special issue: Quality in conceptual modeling
Kumbang: A domain ontology for modelling variability in software product families
Advanced Engineering Informatics
Information Systems Research
Software Estimation Best Practices, Tools & Techniques: A Complete Guide for Software Project Estimators
A theoretical foundation of variability in component-based development
Information and Software Technology
External variability of software: classification and ontological foundations
ER'11 Proceedings of the 30th international conference on Conceptual modeling
The IFPUG Guide to IT and Software Measurement
The IFPUG Guide to IT and Software Measurement
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Organizations can reduce the costs and enhance the quality of required software by adapting existing software systems. Software adaptation decisions often involve comparing alternatives on two criteria: (1) how well a system meets users' requirements and (2) the effort required for adapting the system. These criteria reflect two points of view - of users and of developers. Common to both views is the notion of functionality, which software developers have traditionally used for effort estimation utilizing concepts such as function points. However, users involved in selecting systems are not necessarily familiar with such concepts. We propose an approach for comparing software functionality from users' point of view. The approach employs ontological concepts to define functionality in terms of system behaviors. To evaluate whether or not the approach is also usable by software developers, we conducted an exploratory experiment. In the experiment, software engineering students ranked descriptions of software systems on the amount of changes needed to adapt the systems to given requirements. The results demonstrated that the ontological approach was usable after a short training and provided results comparable to ranking done by expert software developers. We also compared the ontological approach to a method which employed function point concepts. The results showed no statistically significant differences in performance, but there seemed to be an advantage to the ontological approach for cases that were difficult to analyze. Moreover, it took less time to apply the ontological approach than the function point-based approach, and the difference was statistically significant.