Paper Info
Title
Persa: A Requirements Specification Process For Self-Adaptive Systems Based On Fuzzy Logic And Nfr-Framework
Abstract
Self-Adaptive Systems are able to change their behavior at runtime according to the environment where they are. This study presents an approach to specify the requirements for self-adaptive systems based on the concepts of Fuzzy Logic, which deals with factors such as ambiguity, uncertainties and vague information on the solution of problems; and NFR-Framework, which deals with the non-functional requirements which, very often, vaguely and full of uncertainties present themselves. Adaptive systems consist of (functional and non-functional) requirements, which hold the capacity to modify themselves during the runtime with little or no human intervention at all. Requirements that carry out the feature of wide variability are called adaptive requirements. PERSA (acronym from "Processo de Especificacao de Requisitos Adaptativos", in Portuguese) is reported in this work, using the Fuzzy Logic and the NFR-Framework as a basis, since both offers resources to manage uncertainties, an inherent attribute of self-adaptive systems. This process aims the approach of specification of adaptive requirements in a systematic way providing a guide to support requirements engineers. PERSA Process is settled in three mains phases subdivided into several steps. Two case studies were developed to validate it: the first deals with an automated system to prepare steaks, which needs to adapt to its several types; the second relates to a system for automation for canine diets, which must be adapted to different breeds of dogs according to their size, weight and classification. The case studies provide a first approach of the use and benefits of PERSA Process. In these studied the theoretical proposal was evaluated and discussed in order to establish the degree of understanding, the clarity of activities and the necessary adjustments to improve the proposed achievements, thus obtaining a satisfactory though early assessment which answers the purpose of specifying the requirements for self-adaptive systems.
Year
DOI
Venue
2017
10.1142/S0218488517500064
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
Keywords
Field
DocType
Self-adaptive systems, adaptive requirements, fuzzy logic, NFR-framework
Fuzzy logic,Self adaptive,Artificial intelligence,Software requirements specification,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
25
1
0218-4885
Citations 
PageRank 
References 
1
0.40
0
Authors
2
Name
Order
Citations
PageRank
João Dionisio Paraiba110.40
Luiz Eduardo G. Martins283.97