Kairós: Intelligent system for scenarios recommendation at the beginning of software process improvement

Abstract

Software Process Improvement provides benefits to organizations. However, improvement efforts are not guided by the combined use of Good Practices and Critical Factors that influence success. Resources are dedicated without a prior analysis that guides the actions intentionally. The objective of this research is to support decision-making in Software Process Improvement. To achieve this, an intelligent system is conceived, which based on association rules, identifies dependencies between Good Practices and Critical Success Factors. In addition, this system implements a Genetic Algorithm to optimize improvement scenarios and an evolutionary Artificial Neural Network to predict success in Software Process Improvement. The methods used to validate the results corroborated the contribution and usefulness of the proposal.