ABSTRACT:
Several techniques have been proposed
to accurately predict software defects. These techniques generally exploit
characteristics of the code artefacts (e.g., size, complexity, etc.) and/or of
the process adopted during their development and maintenance (e.g., the number
of developers working on a component) to spot out components likely containing
bugs. While these bug prediction models achieve good levels of accuracy, they
mostly ignore the major role played by human-related factors in the
introduction of bugs. Previous studies have demonstrated that focused
developers are less prone to introduce defects than non-focused developers.
According to this observation, software components changed by focused developers
should also be less error prone than components changed by less focused
developers. We capture this observation by measuring the scattering of changes
performed by developers working on a component and use this information to
build a bug prediction model. Such a model has been evaluated on 26 systems and
compared with four competitive techniques. The achieved results show the
superiority of our model, and its high complementarity
with respect to predictors commonly used in the literature. Based on this
result, we also show the results of a “hybrid” prediction model combining our
predictors with the existing ones.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
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System : Pentium Dual Core.
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Hard Disk : 120 GB.
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Monitor : 15’’ LED
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Input Devices : Keyboard, Mouse
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Ram : 1 GB
SOFTWARE REQUIREMENTS:
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Operating system : Windows 7.
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Coding Language : JAVA/J2EE
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Tool : Netbeans 7.2.1
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Database : MYSQL
REFERENCE:
Dario Di Nucci, Fabio Palomba,
Giuseppe De Rosa, “A Developer Centered Bug
Prediction Model”, IEEE Transactions on Software Engineering, 2018.