Ontology-Driven Guidance for Requirements Elicitation

Farfeleder, Stefan; Moser, Thomas; Krall, Andreas; Stålhane, Tor; Omoronyia, Inah; Zojer, H.

doi:10.1007/978-3-642-21064-8_15

Cited by 50 publications

(21 citation statements)

References 14 publications

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“…Domain ontologies make the tool more than just a database for requirements [4]. We can make sure that similar requirements are written using the same structure and that each term is interpreted correctly.…”

Section: A the Dodt Toolmentioning

confidence: 99%

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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Section: A the Dodt Toolmentioning

confidence: 99%

The DODT tool applied to sub-sea software

Stålhane

Wien

2014

2014 IEEE 22nd International Requirements Engineering Conference (RE)

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“…Farfeleder et al [14] presented a tool that uses ontology-based reasoning to guide the requirements engineers and enforced this guidance by using boilerplates.…”

Section: B Ambiguity Preventionmentioning

confidence: 99%

Implementation of a Formal Software Requirements Ambiguity Prevention Tool

Alomari¹,

Elazhary²

2018

ijacsa

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Abstract-The success of the software engineering process depends heavily on clear unambiguous software requirements. Ambiguity refers to the possibility to understand a requirement in more than one way. Unfortunately, ambiguity is an inherent property of the natural languages used to write the software user requirements. This could cause a final faulty system implementation, which is too expensive to correct. The basic requirements ambiguity resolution approaches in the literature are ambiguity detection, ambiguity avoidance, and ambiguity prevention. Ambiguity prevention is the least tackled approach because it requires designing formal languages and templates, which are hard to implement. The main goal of this paper is to provide full implementation of an ambiguity prevention tool and then study its effectiveness using real requirements. Towards this goal, we developed a set of Finite State Machine (FSMs) implementing templates of various requirement types. We then used Python to implement the ambiguity prevention tool based on those FSMs. We also collected a benchmark of 2460 real requirements and selected a random set of forty real requirements to test the effectiveness of the developed tool. The experiment showed that the implemented ambiguity prevention tool can prevent critical requirements ambiguity issues such as missing information or domain ambiguity. Nevertheless, there is a tradeoff between ambiguity prevention and the effort needed to write the requirements using the imposed templates.

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“…Various studies [1,2,3,4,5,15,21,38,39,41 and 49] depict the application of ontologies for knowledge management in Requirement Engineering however the main concern surrounds three main areas (I) handling ambiguity, inconsistency and incompleteness of requirements; (ii) Support for domain knowledge representation to guide requirements elicitation (iii) the use of ontologies to help requirements management. Domain knowledge representation for requirement elicitation is one of focused area of research [3,5]. Some work highlighted the application of wiki for knowledge management and a study is conducted to extend requirement wiki to semantic wiki [6,38].…”

Section: Sub Question No 2: How Use Of Ontology Can Minimize the Limmentioning

confidence: 99%

Unstructured source artifacts ontology for requirement validation in GDSD

Altaf¹,

Shah²,

Ali³

et al. 2018

IJET

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Analyst while transformation, may not capture true representation of user opinion thus creating deviation from actual user needs. Role of stakeholder is primary in both requirement elicitation and validation process. In elicitation stage they are initiator whereas in validation stage they are authenticator of their needs. Invalid requirements if verified may not be a deviation from specified behavior but deviation from user needs. Requirement validation process ensure that requirements should be representing all primary and intermediary artifacts as well a shared opinions of their contributors. This highlights the importance of source artifacts without which requirement validation cannot assured. Researchers didn't propose any framework for requirement validation in context of GDSD in which source artifacts grows exponentially, and stakeholders are located in diversified locations. Due to unstructured nature of source artifacts, they are not electronically indexed and versioned controlled and this makes difficulty in preserving them. Requirement validation is not possible when source artifacts are not available along with their contributors. The major contribution of this paper to address problem of requirement validation in GDSD in absence of stakeholder to make it collocating environment. This paper introduced ontological solution of requirement validation in which target artifacts are validated against source artifact using their semantic relationship. This paper proposed an unstructured source artifact based ontological model for requirement validation in GDSD environment.

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Ontology-Driven Guidance for Requirements Elicitation

Cited by 50 publications

References 14 publications

The DODT tool applied to sub-sea software

The DODT tool applied to sub-sea software

Implementation of a Formal Software Requirements Ambiguity Prevention Tool

Unstructured source artifacts ontology for requirement validation in GDSD

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