Abstract
Software engineering is the process of developing software by utilizing applications of computer engineering. In the present day, predicting the reliability of the software system become a recent issue and an attractive issue for the research area in the field of software engineering. Different techniques have been applied to estimate and predict the reliability of a system. To make new software from the beginning is a difficult task. Component-Based Software Engineering (CBSE) helps in minimizing these efforts in making new software because it utilizes factors like reusability, component dependency, and component interaction that results in decreasing complexity of the system. Soft computing may be applied to estimate reliability. A new model is proposed to estimate the reliability of Component-based Software (CBS) using series and parallel reliability models and later on, the proposed component-based software reliability model is evaluated using two soft computing techniques- Fuzzy Logic and PSO. The experimental results conclude that the proposed reliability model has a lower error rate in predicting CBSE reliability as compared to reliability prediction utilizing fuzzy logic and PSO.
Highlights
Software engineering consists of building, designing, testing, and validation of various software products
Component-Based Software Engineering (CBSE) is a branch of software engineering that mainly depends on component dependency, component interaction and component reusability
Evaluation of CBSRM: MATLAB is used for Particle Swarm Optimization (PSO) implementation using 5 factors of reliability i.e. Reusability, Complexity, Component Interaction, Component Dependency, and failure
Summary
Software engineering consists of building, designing, testing, and validation of various software products. As the technologies vary according to time, the concepts like component reusability, component interaction, and failure rate must be used to make a new product within time. Component-Based Software (CBS) is a recent approach in the field of software engineering that focuses on aggregating components into complex software systems with the rapid development of component technology This approach provides several advantages such as productivity, quality, reusability, reduces maintenance overheads and time-tomarket. The reliability predicting models are related to the factors like effort, Kilo Delivered Lines of Code (KDLOC), fault density, reusability, availability, performance, serviceability, capability, maintainability, interface complexity, adaptability, fitness value and computational time, average execution time, reliability, probability, failure rate, fitness function, ants, etc
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