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Evaluating the effectiveness of deep learning models for foundational program analysis tasks, (OOPSLA2024)
- Abstract: While deep neural networks provide state-of-the-art solutions to a wide range of programming language tasks, their effectiveness in dealing with foundational program analysis tasks remains under explored. In this paper, we present an empirical study that evaluates four prominent models of code (i.e., CuBERT, CodeBERT, GGNN, and Graph Sandwiches) in two such foundational tasks: (1) alias prediction, in which models predict whether two pointers must alias, may alias or must not alias; and (2) equi...
- Labels: static analysis, pointer analysis, equivalence checking, code model, code model training, source code model