Software Quality Assurance is an important factor in IT industry.The work reported in this thesis arose as part of an idea whose goal is to develop an adaptive SQA by defect prediction.In this regard we use SVM machine learning approach to predict the degree of fault proneness of software modules. The machine learning technique for defect forecasting and handling SQA called appendage log training and analysis can be referred as ALTA.The proposed defect forecasting of in-appendage software development log works is to deal the forecasted defects accurately and spontaneously while developing the...