Fuzzy Logic Testing Approach for Measuring Software Completeness

Abstract

Due to advancements in science and technology, software is constantly evolving. To adapt to newly demanded requirements in a piece of software, software components are modified or developed. Measuring software completeness has been a challenging task for software companies. The uncertain and imprecise intrinsic relationships within software components have been unaddressed by researchers during the validation process. In this study, we introduced a new fuzzy logic testing approach for measuring the completeness of software. We measured the fuzzy membership value for each software component by a fuzzy logic testing approach called the fuzzy test. For each software component, the system response was tested by identifying which software components in the system required changes. Based on the measured fuzzy membership values for each software component, software completeness was calculated. The introduced approach scales the software completeness between zero and one. A software component with a complete membership value indicates that the software component does not require any modification. A non-membership value specifies that the existing software component is no longer required in the system or that a new software component is required to replace it. The partial membership value specifies that the software component requires few new functionalities according to the new software requirements. Software with a partial membership value requires partial restructuring and design recovery of its components. Symmetric design of software components reduces the complexity in the restructuring of software during modification. In the study, we showed that by using the introduced approach, high-quality software that is faultless, reliable, easily maintained, efficient, and cost-effective can be developed.

Verification and Validation Framework for AFDX Avionics Networks

“…Citation information: DOI 10.1109/ACCESS.2022.3184329 technology roadmap for the introduction of Artificial Intelligence (AI) in aviation [58]. In this way, AI solutions coming from other research fields are expected to be implemented in V&V frameworks, such as testing software completeness [59] and network topology optimization using genetic algorithms [60], in order to significantly accelerate this process and reduce cost. Here, the proposed framework can support the application of AI in avionics by offering an environment to implement the algorithms to automatically evaluate and optimize the network during the design phase.…”

Reliable Requirements Engineering Practices for COVID-19 Using Blockchain

“…Related studies that help in gathering and supporting information are in Tables 1 and 2, which show the advantages, limitations, and key factors that are identified in related studies [80]. The literature in Table 2 is related to the factors of requirement negotiation and its limitations, and it also includes information about the platforms, applications, framework, strengths, and weaknesses of blockchain technology.…”