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Tool Uses Machine Learning to Spot Bugs Early in Code Development Cycle


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code with indicated defect, illustration

Altran has released a tool that uses artificial intelligence to help software engineers spot bugs during the coding process instead of at the end.

Code Defect AI, available on GitHub and on the Microsoft AI Lab portal, uses machine learning to analyze existing code, spot potential problems in new code, and suggest tests to diagnose and fix the errors.

The tool will help developers release quality code quickly, says Walid Negm, group chief innovation officer at Altran.

Code Defect AI uses several ML techniques including random decision forests, support vector machines, multilayer perceptron, and logistic regression. The platform extracts, processes, and labels historical data to train the algorithm and build a reliable decision model. Developers can use a confidence score from Code Defect AI that predicts whether the code is compliant or buggy.

Code Defect AI is a scalable solution that can be hosted on premise as well as on cloud computing platforms such as Microsoft Azure. While the solution currently supports GitHub, which is owned by Microsoft, it can be integrated with other source-code management tools as needed, Altran says.

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