An ontology-based approach to support the knowledge management of software quality standards

Abstract

Nowadays, the quality of software systems is crucial for companies to provide high-quality services and products. However, a wide number of software projects still fail. To increase the success probability of projects, it is suitable to adopting software quality standards to guide the process. However, standards are commonly described by means of natural language making difficult its analysis. For example, it is not easy to choose the most suitable standard according to the characteristics of a project. Furthermore, the usage of natural language hinders the automatic detection of inconsistencies and ambiguities. On the other hand, ontologies are an artificial intelligence technique that has been successfully used to represent and analyze knowledge in numerous domains because its capacity to enable the automatic validation and consistency checking of the represented information. This paper aims to present an ontology-based approach to describe and analyze software quality standards. Since this ontology can represent the knowledge of several standards, a reasoner may automatically validate the information and infer new knowledge. This ontology might support the reduction of conceptual ambiguity of standards descriptions and improve its understanding.

Enhancing Software Process Assessment with an Ontology-Based Tool: Integrating CMMI, SPICE, and TMMI Models

“…A software process assessment tool with diverse features should also enable the definition of a new model with a comprehensive meta-model (Yürüm, 2014). In one study, CMMI_Dev version 3.1 and PMBOK presented an ontological approach to represent, guide and analyse knowledge (Silega et al, 2023). However, they mentioned that there is a need to extend the ontology to represent the knowledge of various standards and to identify common concepts between different standards.…”

“…By using ontology, the information about software development standards is represented. However, in order to increase its benefits, there is a need to represent more than one standard on this ontology and to define common concepts between different standards (Silega et al, 2023). In addition, since ontologies have computer-executable semantics, inferences can be made about the maturity level of models of companies based on some data provided by the institution (Soydan & Kokar, 2006).…”