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SD Times Open-Source Project of the Week: Code Defect AI

Altran announced this week a new machine learning open-source tool for finding bugs. Code Defect AI is designed to help developers find bugs earlier and minimizes the cost and time required to fix them.

By applying machine learning (ML) to historical data, the tool identifies areas of the code that are potentially buggy and then suggests a set of tests to diagnose and fix the flaws.

“It’s well known that software developers are under constant pressure to release code fast without compromising on quality. The reality however is that the software release cycle needs more than automation of assembly and delivery activities. It needs algorithms that can help make strategic judgments ‒ especially as code gets more complex,” said Walid Negm, the group chief innovation officer at Altran. “Code Defect AI does exactly that.”

Code Defect AI uses machine learning techniques such as random decision forests, support vector machines, multilayer perceptron (MLP) and logistic regression. It supports integration with third-party analysis tools and can itself help identify bugs in a given program code. The solution currently supports GitHub, but it can also be integrated with other source-code management tools. 

Additionally, the Code Defect AI tool allows developers to assess which features in the code have higher weightage in terms of bug prediction, i.e., if there are two features in the software that play a role in the assessment of a probable bug, which feature will take precedence.

Additional details are available here.

The post SD Times Open-Source Project of the Week: Code Defect AI appeared first on SD Times.



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