JUCS - Journal of Universal Computer Science 27(2): 87-90, doi: 10.3897/jucs.65078
Knowledge Intensive Software Engineering Applications
expand article infoJezreel Mejía, Rafael Valencia-García§, Giner Alor-Hernández|, José A. Calvo-Manzano
‡ Centro de Investigación en Matemáticas A.C., Zacatecas, Zacatecas, Mexico§ Universidad de Murcia, Murcia, Spain| Instituto Tecnológico de Orizaba, Orizaba, Veracruz, Mexico¶ Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain
Open Access

The use of Information and Communication Technologies (ICTs)  has become a competitive strategy that allows organizations to position themselves within their market of action. In addition, the evolution, advancement and use of ICTs within any type of organization have created new domains of interest. In this context, Knowledge-intensive software engineering applications are becoming crucial in organizations to support their performance. Knowledge-based technologies provide a consistent and reliable basis to face the challenges for organization, manipulation and visualization of the data and knowledge, playing a crucial role as the technological basis of the development of a large number of information systems. In software engineering, it involves the integration of various knowledge sources that are in constant change.

Knowledge-intensive software applications are becoming more significant because the domains of many software applications are inherently knowledge-intensive and this knowledge is often not explicitly dealt with in software development. This impedes maintenance and reuse. Moreover, it is generally known that developing software requires expertise and experience, which are currently also implicit and could be made more tangible and reusable using knowledge-based or related techniques. Furthermore, organizations have recognized that the software engineering applications are an optimal way for providing solutions, because it is a file that is constantly evolving due to the new challenges. Examples of approaches that are directly related to this tendency are data analysis, software architectures, knowledge engineering, ontologies, conceptual modelling, domain analysis and domain engineering, business rules, workflow management, human and cultural factors, to mention but a few. Therefore, tools and techniques are necessary to capture and process knowledge in order to facilitate subsequent development efforts, especially in the domain of software engineering.