Maurizio Pighin

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The purpose of this paper is to put forward a methodology based on discriminant statistical analysis, which, by evaluating a series of structural parameters of a program, is able to predict its risk level, namely how prone it is to containing faults. The metric was constructed in an experimental context in which the high number of available observations(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t While challenging, the ability to predict faulty modules of a program(More)
abstract The design and configuration of a data warehouse can be difficult tasks especially in the case of very large databases and in the presence of redundant information. In particular, the choice of which attributes have to be considered as dimensions and measures can be not trivial and it can heavily influence the effectiveness of the final system. In(More)
This paper presents a new experimental methodology that operates on a series of programs structural parameters. We calculated some simple metrics on these parameters and then we applied linear programming techniques on them. It was therefore possible to define a model that can predict the risk level of a program, namely how prone it is to containing faults.(More)