ml-for-plse

• Convergent representations of computer programs in human and artificial neural networks (01 Oct 2022)
  What aspects of computer programs are represented in the human brain during program comprehension?
• CLAWSAT - Towards both robust and accurate code models (10 Jan 2022)
  Can adversarial codes be used to improve the generalization and robustness of pre-trained code models? Yes.
• Generating adversarial programs (12 Jan 2021)
  A differentiable generator of adversarial computer programs which can deceive ML models trained on computer programs
• Dependency-based neural representations for classifying lines of programs (15 Feb 2020)
  How can ML models be used to represent lines of programs? We design a dependency-graph based neural representation of programs, which evaluates whether a given line of code has a vulnerability in it or not.
• Evaluating human skills using machine learning (15 Jul 2016)
  At Aspiring Minds, we showed how the problem of quantifying human skills can be cast as a problem in machine learning. Our CACM paper provides details on this framework, while our KDD works show how we evaluate computer programs using ML.