An ontology for software requirements modelling

Innab, Nisreen; Kayed, Ahmad; Sajeev, A. S. M.

doi:10.1109/icist.2012.6221694

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…Again, this is a requirements ontology and not a domain ontology. The same is true for Innab et al's work [15]. Thus, these methods are of limited use to the working requirement engineer.…”

Section: B Use Of Ontologies In Requirementsmentioning

confidence: 62%

The DODT tool applied to sub-sea software

Stålhane

Wien

2014

2014 IEEE 22nd International Requirements Engineering Conference (RE)

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Using natural language is still a common form of writing software requirements. Tools and techniques to improve the quality of natural language requirements may give better results than attempts to convince industry to use something else. We have combined natural language requirements with tool support using boilerplates and domain ontologies, enabling detection of ambiguities and incompleteness in requirements. This paper reports on a case study where requirement analysts used the developed tool to analyse requirements for a safetycritical control system. The experience showed that people were able to use the tool to develop a domain ontology and apply boilerplates to describe requirements in a structured way, yielding requirements readable for humans and analysable for the tool. The tool support improved the quality of requirements by reducing ambiguities and inconsistent use of terminology, removing redundant requirements, and improving partial and unclear requirements.

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“…Again, this is a requirements ontology and not a domain ontology. The same is true for Innab et al's work [15]. Thus, these methods are of limited use to the working requirement engineer.…”

Section: B Use Of Ontologies In Requirementsmentioning

confidence: 62%

The DODT tool applied to sub-sea software

Stålhane

Wien

2014

2014 IEEE 22nd International Requirements Engineering Conference (RE)

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“…In Information Systems (IS) and related fields, the latter -the facilitation of SU of the domain represented in this ontology -is one of the oft-cited benefits of the use of a domain ontology to support human tasks (Al-Debei & Fitzgerald, 2010;Innab, Kayed, & Sajeev, 2012;Lin, Harding, & Shahbaz, 2004;Uschold, King, Moralee, & Zorgios, 1998).…”

Section: List Of Tablesmentioning

confidence: 99%

“…domain ontologies, is that they facilitate shared understanding (SU) (Al-Debei & Fitzgerald, 2010;Innab et al, 2012;Lin et al, 2004;Uschold et al, 1998). However, such claims have lacked theoretical and empirical validation.…”

Section: Theory Of Domain Ontology Effect On Shared Understanding Andmentioning

confidence: 99%

“…Despite these contributions, there is a lack of empirical evidence to support the claimed effective use of ontologies developed with the purpose of facilitating SU, even though many ontologies were developed with this aim in mind -e.g. the enterprise ontology (Uschold et al, 1998), manufacturing system engineering ontology (Lin et al, 2004), V4 service business model ontology (Al-Debei & Fitzgerald, 2010), the ontology for software requirements modelling (Innab et al, 2012), to name just a few. In fact, after the full text analysis of the additional 216 papers that we collected, we could not find any empirical evidence to justify the effectiveness of ontologies to facilitate SU.…”

Section: Ontology Usementioning

confidence: 99%

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Effect of using domain ontologies to facilitate shared understanding and cross-understanding in groups

Marin¹,

Nelson²

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Shared cognition constructs, such as shared understanding and cross-understanding, are important factors for task performance in groups in organizations. Shared understanding defines the extent of common understanding of a topic among group members, whereas cross-understanding defines the extent to which group members accurately understand the mental model of another group member regarding a specific topic. Although research in different fields has focused on understanding the theoretical effects of these constructs, little emphasis has been placed on improving their development. In Information Systems and related fields, shared understanding of a domain is said to be facilitated using a domain ontology -a domain ontology is a description of concepts and their interrelationships in a domain, and are generally represented in a graphical way. However, there is a lack of empirical evidence to support the benefit of domain ontologies facilitating shared understanding. Accordingly, to address this knowledge deficit regarding the mechanisms to enhance shared understanding and cross-understanding, and the lack of empirical evidence regarding the effect of domain ontologies on shared understanding, this study aims to explore the effect of domain-ontology usage on shared understanding and crossunderstanding in novice group members. Accordingly, we propose a theoretical model that describes the effect of domain-ontology usage on shared understanding and crossunderstanding of domains in groups. To empirically test our model, we focus on a domain ontology developed specifically for providing shared understanding of the compliance management domain. We then tested our proposed model through an experimental research design. Our experimental research design considered a two-group, post-test only, randomized experimental design with a sample of student participants. The results of our experiments indicate that group members who use a domain ontology develop significantly higher levels of shared understanding than those who do not use a domain ontology.Secondly, group members who use a domain ontology have significantly better communication quality in terms of discussion efficiency and communication clarity than those who do not use a domain ontology. Our study also found that group members who use a domain ontology develop a significantly greater cross-understanding than those who do not use a domain ontology. The outcomes of this study are expected to contribute to both theory and practice. From a theoretical perspective, we contribute the model of domainontology effects in facilitating shared understanding and cross-understanding, as well as the operationalization and testing of the cross-understanding construct. From a practical iii perspective, we contribute by improving the understanding of the role domain ontologies can play as a tool to help improve performance in groups.iv

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Model-based requirements verification method: Conclusions from two controlled experiments

Aceituna

Walia

et al. 2014

Information and Software Technology

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Context: Requirements engineering is one of the most important and critical phases in the software development life cycle, and should be carefully performed to build high quality and reliable software. However, requirements are typically gathered through various sources and are represented in natural language (NL), making requirements engineering a difficult, fault prone, and a challenging task. Objective: To ensure high-quality software, we need effective requirements verification methods that can clearly handle and address inherently ambiguous nature of NL specifications. The objective of this paper is to propose a method that can address the challenges with NL requirements verification and to evaluate our proposed method through controlled experiments. Method: We propose a model-based requirements verification method, called NLtoSTD, which transforms NL requirements into a State Transition Diagram (STD) that can help to detect and to eliminate ambiguities and incompleteness. The paper describes the NLtoSTD method to detect requirement faults, thereby improving the quality of the requirements. To evaluate the NLtoSTD method, we conducted two controlled experiments at North Dakota State University in which the participants employed the NLtoSTD method and a traditional fault checklist during the inspection of requirement documents to identify the ambiguities and incompleteness of the requirements. Results: Two experiment results show that the NLtoSTD method can be more effective in exposing the missing functionality and, in some cases, more ambiguous information than the fault-checklist method. Our experiments also revealed areas of improvement that benefit the method's applicability in the future. Conclusion: We presented a new approach, NLtoSTD, to verify requirements documents and two controlled experiments assessing our approach. The results are promising and have motivated the refinement of the NLtoSTD method and future empirical evaluation.

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An ontology for software requirements modelling

Cited by 7 publications

References 15 publications

The DODT tool applied to sub-sea software

The DODT tool applied to sub-sea software

Effect of using domain ontologies to facilitate shared understanding and cross-understanding in groups

Model-based requirements verification method: Conclusions from two controlled experiments

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