Proactive Support for Conceptual Interoperability Analysis of Software Units.
(Sprache: Englisch)
Conceptual interoperability analysis refers to the process of identifying the conceptual interoperability constraints of two software units in order to detect existing conceptual mismatches between them. The thesis provides framework for supporting...
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Conceptual interoperability analysis refers to the process of identifying the conceptual interoperability constraints of two software units in order to detect existing conceptual mismatches between them. The thesis provides framework for supporting effective and efficient conceptual interoperability analysis. This includes a model for the conceptual constraints and mismatches, analysis methods, tools, guidelines, and empirical evaluation studies.
Klappentext zu „Proactive Support for Conceptual Interoperability Analysis of Software Units. “
Meaningful exchange of data or services with a software unit requires identifying and satisfying its conceptual constraints. Otherwise, unexpected conceptual mismatches lead to late projects and costly rework. However, for blackbox software providers, it is unguided and time-consuming task to share the conceptual constraints explicitly with third-party clients who also lack the guidance on detecting the conceptual mismatches. To cope with these challenges, we built a Conceptual Interoperability Constraints (COINs) model, which is the base for our Conceptual Interoperability Analysis (COINA) framework. COINA helps architects and analysts to identify the conceptual constraints and mismatches of software units effectively and efficiently. It comprises: (1) Proactive, semi-automatic, in-house preparation for interoperable units that helps providers to share the conceptual constraints with the least effort. (2) A systematic, algorithm-based method for mapping conceptual constraints of systems to detect their mismatches. A multi-run controlled experiment confirmed our hypotheses that our approach significantly increases the effectiveness and efficiency in detecting conceptual mismatches.
Bibliographische Angaben
- Autor: Hadil Abukwaik
- 2018, 282 Seiten, Maße: 17 x 24 cm, Kartoniert (TB), Englisch
- Herausgegeben: Frank Bomarius, Peter Liggesmeyer, Dieter Rombach, Kaiserslautern Fraunhofer IESE
- Verlag: Fraunhofer Verlag
- ISBN-10: 3839613388
- ISBN-13: 9783839613382
Sprache:
Englisch
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