A System Based on Ontology and Case-Based Reasoning to Support Distributed Teams

Abstract

The intrinsic nature of distributed software development (DSD) brings new challenges, such as communication issues and sharing information efficiently. Software companies have a tendency to face these challenges using individual and isolated approaches, making difficult to spread good practices for the DSD community. In other contexts, concepts and techniques from Artificial Intelligence (AI) are frequently used in order to improve the functioning of systems and process. This work is based on the following AI concepts: ontologies, case-based reasoning (CBR) and natural language processing (NLP). We propose a system, based on ontology and case-based reasoning, that operates as follows: i) we use a tool for ontology storage, access and processing; and ii) an ontology-based CBR tool which aims to aid software companies by recommending techniques and best practices for minimizing or solving potential challenges that may be faced by DSD processes. The main results from this research are: i) a specific ontology for distributed software development teams; ii) a tool to facilitate the access and manipulation of the proposed ontology; and iii) a casebased reasoning system that utilizes natural language processing. Initial results of the performed experiments indicate a success rate of 91.7% in the recommendation of solutions for potential problems coming from DSD processes.

CFDSD: a Communication Framework for Distributed Software Development

“…The media can influence communication performance and include underlying communication processes [27,28], and both, transmission of data and individual cognitive processes, to develop information. When addressing the technology-related challenges of DSD, [10] and [17] state that the most evident configuration is the synchrony in communication. Synchronous communication occurs when the participants have access to transmitted messages in real time.…”