Empirical Studies to Predict Fault Proneness: A Review

software quality in the past years. This paper provides a review of empirical studies to predict software fault proneness with a specific focus on techniques used. The paper highlights the milestone studies done from 1995 to 2010 in this area. Results show that use of machine learning languages have started.This paper reviews works done in the field of software fault prediction studies. The study is concentrated on statistical techniques and their usage to predict fault proneness. The conclusion drawn is the future studies should use more of class level metrics and the best technique to derive fault predictors amongst statistical techniques is logistic regression.