Let the OSS Enterprise newsletter guide your open source journey! Intel today open-sourced ControlFlag, a tool that uses machine learning to detect problems in computer code -- ideally to reduce the time required to debug apps and software. In tests, the company's machine programming research team says that ControlFlag has found hundreds of defects in proprietary, "production-quality" software, demonstrating its usefulness. "Last year, ControlFlag identified a code anomaly in Client URL (cURL), a computer software project transferring data using various network protocols over one billion times a day," Intel principal AI scientist Justin Gottschlich wrote in a blog post on LinkedIn. "Most recently, ControlFlag achieved state-of-the-art results by identifying hundreds of latent defects related to memory and potential system crash bugs in proprietary production-level software. In addition, ControlFlag found dozens of novel anomalies on several high-quality open-source software repositories."

Altran has released a new tool that uses artificial intelligence (AI) to help software engineers spot bugs during the coding process instead of at the end. Available on GitHub, Code Defect AI uses machine learning (ML) to analyze existing code, spot potential problems in new code, and suggest tests to diagnose and fix the errors. Walid Negm, group chief innovation officer at Altran, said that this new tool will help developers release quality code quickly. "The software release cycle needs algorithms that can help make strategic judgments, especially as code gets more complex," he said in a press release. Code Defect AI uses several ML techniques including random decision forests, support vector machines, multilayer perceptron (MLP) and logistic regression.