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Compositional recurrence analysis revisited

Authors:

Zachary Kincaid,

Ashkan Forouhi Boroujeni,

Thomas RepsAuthors Info & Claims

PLDI 2017: Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation

Pages 248 - 262

https://doi.org/10.1145/3062341.3062373

Published: 14 June 2017 Publication History

Abstract

Compositional recurrence analysis (CRA) is a static-analysis method based on a combination of symbolic analysis and abstract interpretation. This paper addresses the problem of creating a context-sensitive interprocedural version of CRA that handles recursive procedures. The problem is non-trivial because there is an "impedance mismatch" between CRA, which relies on analysis techniques based on regular languages (i.e., Tarjan's path-expression method), and the context-free-language underpinnings of context-sensitive analysis.

We show how to address this impedance mismatch by augmenting the CRA abstract domain with additional operations. We call the resulting algorithm Interprocedural CRA (ICRA). Our experiments with ICRA show that it has broad overall strength compared with several state-of-the-art software model checkers.

Supplementary Material

Auxiliary Archive (pldi17-main225-s.zip)

This ZIP archive contains a virtual machine in OVA (Open Virtualization Archive) format. The virtual machine contains an installation of ICRA, which is the program analysis tool that implements the ideas described in the associate publication, "Compositional Recurrence Analysis Revisited." For more information about the virtual machine, see the README.txt file inside the ZIP archive. For detailed information about how to use the virtual machine to run ICRA, see the README.txt file inside the virtual machine at the path "~/Newton/README.txt".

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Cited By

Kura SUnno H(2024)Automated Verification of Higher-Order Probabilistic Programs via a Dependent Refinement Type SystemProceedings of the ACM on Programming Languages10.1145/36746628:ICFP(973-1002)Online publication date: 15-Aug-2024
https://dl.acm.org/doi/10.1145/3674662
Chatterjee KGoharshady AMeggendorfer TŽikelić Đ(2024)Quantitative Bounds on Resource Usage of Probabilistic ProgramsProceedings of the ACM on Programming Languages10.1145/36498248:OOPSLA1(362-391)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3649824
Wang DReps T(2024)Newtonian Program Analysis of Probabilistic ProgramsProceedings of the ACM on Programming Languages10.1145/36498228:OOPSLA1(305-333)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3649822
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Index Terms

Compositional recurrence analysis revisited
1. Software and its engineering
  1. Software organization and properties
    1. Software functional properties
      1. Formal methods
        Automated static analysis
2. Theory of computation
  1. Semantics and reasoning
    1. Program reasoning
      1. Program analysis

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cover image ACM Conferences

PLDI 2017: Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation

June 2017

708 pages

ISBN:9781450349888

DOI:10.1145/3062341

General Chair:
Albert Cohen
Inria, France
,
Program Chair:
Martin Vechev
DeepCode, Switzerland / ETH Zurich, Switzerland

ACM SIGPLAN Notices Volume 52, Issue 6
PLDI '17
June 2017
708 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/3140587
Editor:
Matthew Fluet
Issue’s Table of Contents

Copyright © 2017 ACM.

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Published: 14 June 2017

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PLDI '17: ACM SIGPLAN Conference on Programming Language Design and Implementation

June 18 - 23, 2017

Barcelona, Spain

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Cited By

Kura SUnno H(2024)Automated Verification of Higher-Order Probabilistic Programs via a Dependent Refinement Type SystemProceedings of the ACM on Programming Languages10.1145/36746628:ICFP(973-1002)Online publication date: 15-Aug-2024
https://dl.acm.org/doi/10.1145/3674662
Chatterjee KGoharshady AMeggendorfer TŽikelić Đ(2024)Quantitative Bounds on Resource Usage of Probabilistic ProgramsProceedings of the ACM on Programming Languages10.1145/36498248:OOPSLA1(362-391)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3649824
Wang DReps T(2024)Newtonian Program Analysis of Probabilistic ProgramsProceedings of the ACM on Programming Languages10.1145/36498228:OOPSLA1(305-333)Online publication date: 29-Apr-2024
https://dl.acm.org/doi/10.1145/3649822
Muller SHoffmann J(2024)Modeling and Analyzing Evaluation Cost of CUDA KernelsACM Transactions on Parallel Computing10.1145/363940311:1(1-53)Online publication date: 12-Jan-2024
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Bautista SJensen TMontagu B(2024)An input–output relational domain for algebraic data types and functional arraysFormal Methods in System Design10.1007/s10703-024-00456-zOnline publication date: 13-Jun-2024
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Ghardallou WMohammadi HLinger RPleszkoch MLoh JMili A(2024)Invariant relations for affine loopsActa Informatica10.1007/s00236-024-00457-961:3(261-314)Online publication date: 13-May-2024
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Wang CLin F(2024)On Polynomial Expressions with C-Finite Recurrences in Loops with Nested Nondeterministic BranchesComputer Aided Verification10.1007/978-3-031-65627-9_20(409-430)Online publication date: 24-Jul-2024
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Wang CLin F(2023)Solving Conditional Linear Recurrences for Program Verification: The Periodic CaseProceedings of the ACM on Programming Languages10.1145/35860287:OOPSLA1(28-55)Online publication date: 6-Apr-2023
https://dl.acm.org/doi/10.1145/3586028
Yao PKe JSun JFu HWu RRen K(2023)Demystifying Template-Based Invariant Generation for Bit-Vector Programs2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)10.1109/ASE56229.2023.00069(673-685)Online publication date: 11-Sep-2023
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Akshay SChatterjee KMeggendorfer TŽikelić Đ(2023)MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety ObjectivesComputer Aided Verification10.1007/978-3-031-37709-9_5(86-112)Online publication date: 17-Jul-2023
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