An Efficient Software Fault Prediction Model using Cluster based Classification

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Provided by: International Journal of Applied Information Systems (IJAIS)
Topic: Big Data
Format: PDF
Predicting fault -prone software components is an economically important activity due to limited budget allocation for software testing. In recent years data mining techniques are used to predict the software faults. In this paper, the authors present a cluster based fault prediction classifiers which increases the probability of detection. The expectation from a predictor is to get very high probability of detection to get more reliable and test effective software. In their experiments, they used fault data from mission critical systems.
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