Tools Supporting the Communication of Critical Domain Knowledge in High-Consequence Systems Development

Wasson, Kimberly S.; Knight, John; Strunk, Elisabeth A.; Travis, S.R.

doi:10.1007/978-3-540-39878-3_25

Cited by 2 publications

(4 citation statements)

References 8 publications

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“…In this article, we focus on the process to model natural language descriptions of systems and their environments. Therefore, we first review the role of ontology in modeling domain knowledge before reviewing two popular methods for acquiring formal specifications from natural language descriptions: controlled languages [Cregan et al 2007;Konrad and Cheng 2005;Kaljurand and Fuchs 2007;Smith et al 2002] and standard lexicons [Cysneiros and Leite 2004;Kaindl 1996;Overmyer et al 2001;Wasson et al 2003;Wasson 2006]. We conclude by reviewing types of ambiguities identified by Gause and Weinberg [1989].…”

Section: Related Workmentioning

confidence: 98%

“…Several researchers have recognized the need to better align natural language requirements and formal models to prevent the loss of original context [Potts 1997]; incorporate knowledge about the system environment [Jackson 1997;van Lamsweerde 2000;Mylopoulos et al 1997;Nuseibeh and Easterbrook 2000]; improve traceability [Ramesh and Jarke 2001]; apply formal analysis to requirements concepts [van Lamsweerde 2000;Nuseibeh and Easterbrook 2000]; and reduce ambiguous terminology [Gause and Weinberg 1989;Jackson 1997;Denger et al 2003;Wasson et al 2003;Wasson 2006]. In this article, we focus on the process to model natural language descriptions of systems and their environments.…”

Section: Related Workmentioning

confidence: 99%

“…Similarly, Kaindl [1996] showed how to identify binary relationships between nouns in natural language definitions and map them to new classes. Wasson et al employed a domain map to facilitate effective communication between domain experts and engineers [Wasson et al 2003;Wasson 2006]. The domain map contains technical words classified into hierarchies of superordinate and subordinate terms and is used to identify ambiguous terms based on their commonality and domain-specific interpretation.…”

Section: Related Workmentioning

confidence: 99%

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Semantic parameterization

Breaux

Antón

Doyle

2008

ACM Trans. Softw. Eng. Methodol.

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Software engineers must systematically account for the broad scope of environmental behavior, including nonfunctional requirements, intended to coordinate the actions of stakeholders and software systems. The Inquiry Cycle Model (ICM) provides engineers with a strategy to acquire and refine these requirements by having domain experts answer six questions: who, what, where, when, how, and why. Goal-based requirements engineering has led to the formalization of requirements to answer the ICM questions about when, how, and why goals are achieved, maintained, or avoided. In this article, we present a systematic process called Semantic Parameterization for expressing natural language domain descriptions of goals as specifications in description logic. The formalization of goals in description logic allows engineers to automate inquiries using who, what, and where questions, completing the formalization of the ICM questions. The contributions of this approach include new theory to conceptually compare and disambiguate goal specifications that enables querying goals and organizing goals into specialization hierarchies. The artifacts in the process include a dictionary that aligns the domain lexicon with unique concepts, distinguishing between synonyms and polysemes, and several natural language patterns that aid engineers in mapping common domain descriptions to formal specifications. Semantic Parameterization has been empirically validated in three case studies on policy and regulatory descriptions that govern information systems in the finance and health-care domains.

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Section: Related Workmentioning

confidence: 98%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Semantic parameterization

Breaux

Antón

Doyle

2008

ACM Trans. Softw. Eng. Methodol.

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“…Partial automation is essential for this approach to be cost-effective for large software systems. To this end, we plan to integrate this method with existing partially-automated support tools for managing natural language issues in requirements [14].…”

Section: A Note On Process Integrationmentioning

confidence: 99%

Using occurrence properties of defect report data to improve requirements

Wasson

Schmid

Lutz

et al. 2005

13th IEEE International Conference on Requirements Engineering (RE'05)

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Defect reports generated for faults found during testing provide a rich source of information regarding problematic phrases used in requirements documents. These reports indicate that faults often derive from instances of ambiguous, incorrect or otherwise deficient language. In this paper, we report on a method combining elements of linguistic theory and information retrieval to guide the discovery of problematic phrases throughout a requirements specification, using defect reports and correction requests generated during testing to seed our detection process. We found that phrases known from these materials to be problematic have occurrence properties in requirements documents that both allow the direction of resources to prioritize their correction, and generate insights characterizing more general locations of difficulty within the requirements. Our findings lead to some recommendations for more efficiently and effectively managing certain natural language issues in the creation and maintenance of requirements specifications.

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Tools Supporting the Communication of Critical Domain Knowledge in High-Consequence Systems Development

Cited by 2 publications

References 8 publications

Semantic parameterization

Semantic parameterization

Using occurrence properties of defect report data to improve requirements

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