Semantic Modeling and Analysis of Natural Language System Requirements

Abstract

System requirements specify how a system meets stakeholder needs. They are a partial definition of the system under design in natural language that may be restricted in syntax terms. Any natural language specification inevitably lacks a unique interpretation and includes underspecified terms and inconsistencies. If the requirements are not validated early in the system development cycle and refined, as needed, specification flaws may cause costly cycles of corrections in design, implementation and testing. However, validation should be based on a consistent interpretation with respect to a rigorously defined semantic context of the domain of the system. We propose a specification approach that, while sufficiently expressive, it restricts the requirements definition to terms from an ontology with precisely defined concepts and semantic relationships in the domain of the system under design. This enables a series of semantic analyses, which guide the engineer towards improving the requirement specification as well as eliciting tacit knowledge. The problems addressed are prerequisites to enable the derivation of verifiable specifications. We present the results from a case study of modest size from the space system domain, as well as an evaluation of our approach from the user's point of view. The requirement types that have been covered demonstrate the applicability of the approach in an industrial context, although the effectiveness of the analysis depends on pre-existing domain ontologies.INDEX TERMS embedded systems, ontologies, requirements validation, semantic reasoning I. INTRODUCTION

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“…One of the main causes of software bugs is from the specification [1] [2]. As software specification gathered from the user's needs is mostly written in common natural languages in the Software Requirements Specification (SRS) document [3][4] [5], this leads unstructured requirements to be ambiguous and misunderstood by software developers [4][6] [7]. Furthermore, in system and user acceptance testing, test cases are generated from the SRS.…”