Today, it is well known that missing, incomplete or inconsistent requirements lead to faulty software designs, implementations and tests resulting in software of improper quality or safety risks. Thus, an improved Requirements Engineering contributes to safer and better-quality software, reduces the risk of overrun time and budgets and, most of all, decreases or even eliminates the risk for project failures.
One significant problem requirements engineers have to cope with, are inconsistencies in the Software Requirements Specification. Such inconsistencies result from the acquisition, specification, and evolution of goals and requirements from multiple stakeholders and sources. In order to regain consistency, requirements information are removed from the specification which often leads to incompleteness. Due to this causal relationship between consistency, completeness and correctness, we can formally improve the correctness of requirements knowledge by increasing its completeness and consistency. Furthermore, the poor quality of individual requirements is a primary reason why so many projects continue to fail and needs to be considered in order to improve the Software Requirements Specification.
These flaws in the Software Requirements Specification are hard to identify by current methods and thus, usually remain unrecognised. While the validation of requirements ensures that they are correct, complete, consistent and meet the customer and user intents, the requirements engineer is hardly supported by automated validation methods.
In this thesis, a novel approach to automated validation and measurement of requirements knowledge is presented, which automatically identifies incomplete or inconsistent requirements and quality flaws. Furthermore, the requirements engineer is guided by providing knowledge specific suggestions on how to resolve them. For this purpose, a requirements metamodel, the Requirements Ontology, has been developed that provides the basis for the validation and measurement support. This requirements ontology is suited for Goal-oriented Requirements Engineering and allows for the conceptualisation of requirements knowledge, facilitated by ontologies. It provides a huge set of predefined requirements metadata, requirements artefacts and various relations among them. Thus, the Requirements Ontology enables the documentation of structured, reusable, unambiguous, traceable, complete and consistent requirements as demanded by the IEEE specification for Software Requirement Specifications. We demonstrate our approach with a prototypic implementation called OntoReq. OntoReq allows for the specification of requirements knowledge while keeping the ontology invisible to the requirements engineer and enables the validation of the knowledge captured within.
The validation approach presented in this thesis is capable of being applied to any domain ontology. Therefore, we formulate various guidelines and use a continuous example to demonstrate the transfer to the domain of medical drugs. The Requirements Ontology as well as OntoReq have been evaluated by different methods. The Requirements Ontology has been shown to be capable for capturing requirements knowledge of a real Software Requirements Specification and OntoReq feasible to be used by a requirements engineering tool to highlight inconsistencies, incompleteness and quality flaws during real time requirements modelling.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:28576 |
| Date | 29 April 2014 |
| Creators | Siegemund, Katja |
| Contributors | Aßmann, Uwe, Wagner, Gerd, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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