Contractual Safety of Model-Based Requirements: Preliminary Results of an Experimental Study

Abstract

Requirements form the backbone of contracting in acquisition programs. Requirements define the problem boundaries within which contractors try to find acceptable solutions (design systems). At the same time, requirements are the criteria by which a customer measures the extent that their contract has been fulfilled by the supplier. Therefore, requirements are instrumental in the success of acquisition programs. In this context, the quality of a requirement set is determined by the level of contractual safety that it yields. From a technical perspective, contractual safety is driven by the accuracy, precision, and level of completeness of the requirement set. Unfortunately, textual requirements do not provide acceptable levels of contractual safety, as they remain a major source of problems in acquisition programs. This is partly caused by the inherent limitations of natural language to statically capture written statements with precision and accuracy. In addition, natural language is difficult (often impossible) to parse into consistent logical or mathematical statements, which limits the use of systematic and/or automated tools to explore completeness. Model-based requirements have been proposed as an alternative to textual requirements, with the promise of enabling higher accuracy, precision, and completeness when eliciting requirements. However, this promise has not been demonstrated yet. Therefore, research is needed to understand the contractual impacts of using model-based requirements instead of textual requirements before model-based requirements can be widely adopted to support acquisition programs. This paper presents preliminary results of a research project that measures the contractual safety yielded by model-based requirements. Specifically, the research addresses the main question of whether using model-based requirements improves the contractual safety of acquisition programs compared to using textual requirements. The accuracy, precision, and completeness achieved by model-based requirements are empirically measured using an experimental study. We employ a notional airborne solution to a surveillance and detection problem.