SOFTWARE DEFECT PREDICTION USING SOFTWARE METRICS WITH NAÏVE BAYES AND RULE MINING ASSOCIATION METHODS

SOFTWARE DEFECT PREDICTION USING SOFTWARE METRICS WITH NAÏVE BAYES AND RULE MINING ASSOCIATION METHODS

Producing software that does not contain defects or a little defects is not an easy task for software developers. Software testing is an important process to ensure software quality. Predicting software damage can help testers decide rational allocation of resources because they can find defects...

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Bibliographic Details
Main Author: Maruli Tua Simanguns, Fernando
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/36876
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Institution: Institut Teknologi Bandung
Language: Indonesia

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