Computational Representation, Analysis and Verification of Requirements in Engineering Design and Systems Engineering

Systems are developed to satisfy a set of requirements derived from stakeholders’ needs, defining the problem space for which the system is created as a feasible solution. The system design process begins with eliciting these requirements and concludes with validating whether the created system meets them. Requirements engineering (RE) encompasses elicitation, representation, analysis, documentation, verification, and validation. However, challenges in RE, such as imprecision in natural language (NL), proprietary restrictions, and a lack of standardized quality metrics, hinder the creation of well-formed and comprehensive requirements. These challenges complicate formalization and analysis of requirements. This dissertation addresses these challenges by proposing a formal method to represent requirements in open-source System Requirement Specification Documents (SyRSDs) as trees. Leaf nodes represent individual requirements, branch nodes reflect components and functions, and edges capture the decomposition hierarchy, mirroring the requirement allocation process. A dataset is introduced with three inter-convertible forms: ReqList (12,701 textual requirements), ReqNet (a network of 17,375 nodes), and ReqSim (10,933 requirement pairs with similarity scores), enabling advanced RE research using natural language processing (NLP), machine learning (ML), and graph theory. We develop Req-sBERT, a fine-tuned Sentence-BERT model, to generate embeddings that estimate semantic similarity between any pair of requirements. These embeddings facilitate detecting the evolution of requirements and documenting them using hierarchical trees. We create a requirements verification framework to evaluate conformance to ISO/IEC/IEEE 29148:2018(E) using 42 INCOSE rules. We introduce the well-formed Requirement Quality (wRQ) index for quality comparison. Our work enhances RE by improving dataset availability, representation, analysis, and verification.