摘要 : We review machine learning approaches for detecting (and correcting) vulnerabilities in source code, finding that the biggest challenges ahead involve agreeing to a benchmark, increasing language and error type coverage, and using... 展开 We review machine learning approaches for detecting (and correcting) vulnerabilities in source code, finding that the biggest challenges ahead involve agreeing to a benchmark, increasing language and error type coverage, and using pipelines that do not flatten the code’s structure. 收起