BUG PREDICTION: Log approach – version approach
Lucio Ciraci'
BUG PREDICTION: Log approach – version approach.
Rel. Elio Piccolo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2019
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Abstract
Bug prediction has generated widespread interest for a long time. The general scenario have been many applications with different approaches. The raising of properties of programming languages made it necessary a study about the correlation between classes, packages and files. In order to improve the quality of code and the developers satisfaction. In the last 20 years there are studied many metrics to evaluate a coding and to limit bugs. In further detail for instance, the Chidamber and Kemerer (CK) object-oriented metrics suite based on coupling between objects, numbers of children or depth of an inheritance tree. We will focus on different levels of granularity (class, method or package), paying attention on a featuring selection like to reduce or to combine metrics.
In this work using the last Data analysis approach (neural network, decision tree, linear regression), it was possible to obtain models in order to predict bugs based on five relevant software system (Eclipse JDT Core - Eclipse PDE UI etc.)
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