The document discusses the application of machine learning in static analysis of program source code, focusing on its potential benefits and limitations. It reviews various machine learning-based static analyzers like DeepCode, Infer, and CodeGuru, highlighting their capabilities and challenges in accurately identifying bugs and vulnerabilities. Despite the enthusiasm for machine learning, the authors convey skepticism about its practicality and reliability for certain diagnostic tasks compared to traditional analysis methods.