This paper examines the methods of increasing software efficiency based on soft computing technology by analyzing the benefits and challenges of the components used in software development. The functions and features of machine learning, comprising neural networks, perceptron, support vector machines, and fuzzy logic are highlighted and explained, along with those of evolutionary computation (e.g., evolutionary and genetic algorithms) and probability. Recommendations are presented in conclusion.
This paper is one of only a few to investigate and analyze the problems of soft computing technologies. By reviewing the utilization of new estimation methodologies, it contributes to the existing literature and comparative analyses.