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Da Silva Filho, J.I., Onuki, A.S., Ferrara, L.F.P., Mário, M.C., Camargo, J.M., Garcia, D.V., Dos Santos, M.R. and Rocco, A. (2012) Electric Power System Operation Decision Support by Expert System Built with Paraconsistent Annotated Logic, Advances in Expert Systems. InTech.
http://dx.doi.org/10.5772/51379

has been cited by the following article:

• TITLE: An Application of Paraconsistent Annotated Logic for Design Software Testing Strategies

  AUTHORS: Marcos Ribeiro do Nascimento, Luiz Alberto Vieira Dias, Joao Inacio Da Silva Filho

  KEYWORDS: Paraconsistent Logic, Design Testing Strategies, Software Testability, Paraconsistent Decision Making Model

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.7 No.5, May 13, 2014

  ABSTRACT: Nowadays, application model systems for decision-making based on non-classical logic such as Paraconsistent Logic are used successfully in the treatment of uncertainties. The method presented in this paper is based on the fundamental concepts of Paraconsistent Annotated Logic with annotation of 2 values (PAL2v). In this study, two algorithms based on PAL2v are presented gradually, to extract the effects of the contradiction in signals of information from a database of uncertain knowledge. The Paraconsistent Extractors Algorithms of Contradiction Effect-Para Extrctr is applied to filters of networks of analyses (PANets) of signal information, where uncertain and contradictory signals may be found. Software test case scenarios are subordinated to an application model of Paraconsistent decision-making, which provides an analysis using Paraconsistent Logic in the treatment of uncertainties for design software testing strategies. This quality-quantity criterion to evaluate the software product quality is based on the characteristics of software testability analysis. The Para consistent reasoning application model system presented in this case study, reveals itself to be more efficient than the traditional methods because it has the potential to offer an appropriate treatment to different originally contradicting source information.