Reducing Ambiguities in Customer Requirements Through Historical Knowledge - Capstone Project Example

It is said that on the contrary, adverse scenarios develop, and complex designs are continually expressed, marked by high levels of understandability, verifiability, traceability, and modifiability requirements which are not consistent with complex situations. The intricate situations increase, creating a design reality for Requirements Engineering processes plagued with uncertainty, vacillation, and visualization. The purpose of this study is to present a more conventional philosophical system of thinking, which is ideally grounded on the value-based approach and melted down to the ideal elucidation process in the rigid scenarios.

It will develop a discussion that supports no software engineering may supersede Requirement Engineering. A high degree of quality in Requirement Engineering is paramount to withstand harsh run time errors associated with software engineering development.History has shown that insufficient engineering requirements lead to insufficient engineering products and thus, security risks. Requirements Engineering (RE) consists of development and management and is one of the most important disciplines in the development of Software Engineering (SE) software products.

According to the Software Engineering Body of Knowledge (SWEBOK), software requirements can be defined as “a property which must be exhibited in order to solve some problem in the real world” (Committee 2004). One of the main practices in RE is the elicitation process of software requirements (see fig. 1). During the elicitation process, requirements are analyzed, specified, and verified (SPC, 2002). Software requirements specifications are derived from the requirements elicitation process (see fig. 1). For requirements to be of quality, they must be correct, complete, precise, consistent, verifiable, modifiable, and traceable (Toval et al. 2002). Successful and effective requirements engineering can improve risk management, quality, reusability, and productivity during the software development process.

In this study, ambiguities in new customer requirements are analyzed and reduced using the proposed conceptual method, which involves a historical knowledge base of previously defined requirements (see fig. 2). The ontology represents a set of new requirements as concepts and relationships mapped through rules of inference.