Knowledge Model of a Therapy Administration Task – Applied to an Agricultural Domain

One of the major problems when developing complex software systems is that of Requirement Engineering. The methodologies usually propose iterations in which requirements are to be reviewed and re-written until the final version is obtained. This chapter focuses on the construction of “Requisites”, a Bayesian network designed to be used as a predictor that tells us whether a requirements specification has enough quality to be considered as a baseline. Requisites have been defined using several information sources, such as standards and reports, and through interaction with experts, in order to structure and quantify the final model. This Bayesian network reflects the knowledge needed when assessing a requirements specification. The authors show how Requisites can be used through the study of some use cases. After the propagation over the network of information collected about the certainty of a subset of variables, the value predicted will determine if the requirements specification has to be revised.

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Knowledge Model of a Therapy Administration Task – Applied to an Agricultural Domain

Cited by 2 publications

References 4 publications

Olive Fly Infestation Prediction Using Machine Learning Techniques

Olive Fly Infestation Prediction Using Machine Learning Techniques

A Bayesian Network for Predicting the Need for a Requirements Review

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