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Inferring Region Types via an Abstract Notion of Environment Transformation

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Programming Languages and Systems (APLAS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13658))

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Abstract

Region-based type systems are a powerful tool for various kinds of program analysis. We introduce a new inference algorithm for region types based on an abstract notion of environment transformation. It analyzes the code of a method only once, even when there are multiple invocations of the method of different region types in the program. Elements of such an abstract transformation are essentially constraints for equality and subtyping that capture flow information of the program. In particular, we work with access graphs in the definition of abstract transformations to guarantee the termination of the inference algorithm, because they provide a finite representation of field access paths.

Supported by the German Research Foundation (DFG) under the research grant 250888164 (GuideForce).

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Acknowledgements

We thank Fredrick Nordvall Forsberg for the fruitful discussion on this work and the anonymous reviewers for their valuable comments and suggestions on the paper and its accompanying artifact.

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  1. fortiss GmbH, Guerickestraße 25, 80805, Munich, Germany

    Ulrich Schöpp & Chuangjie Xu

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  1. Ulrich Schöpp
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Correspondence to Chuangjie Xu .

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  1. National University of Singapore, Singapore, Singapore

    Ilya Sergey

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Schöpp, U., Xu, C. (2022). Inferring Region Types via an Abstract Notion of Environment Transformation. In: Sergey, I. (eds) Programming Languages and Systems. APLAS 2022. Lecture Notes in Computer Science, vol 13658. Springer, Cham. https://doi.org/10.1007/978-3-031-21037-2_3

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  • DOI: https://doi.org/10.1007/978-3-031-21037-2_3

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