skip to main content
10.1007/978-981-97-2300-3_4guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
Article

A Complete Dependency Pair Framework for Almost-Sure Innermost Termination of Probabilistic Term Rewriting

Published: 21 June 2024 Publication History

Abstract

Recently, we adapted the well-known dependency pair (DP) framework to a dependency tuple framework in order to prove almost-sure innermost termination (iAST) of probabilistic term rewrite systems. While this approach was incomplete, in this paper, we improve it into a complete criterion for iAST by presenting a new, more elegant definition of DPs for probabilistic term rewriting. Based on this, we extend the probabilistic DP framework by new transformations. Our implementation in the tool AProVE shows that they increase its power considerably.

References

[1]
Agrawal, S., Chatterjee, K., Novotný, P.: Lexicographic ranking supermartingales: an efficient approach to termination of probabilistic programs. Proc. ACM Program. Lang. 2(POPL) (2017).
[2]
Arts, T., Giesl, J.: Termination of term rewriting using dependency pairs. Theor. Comput. Sci. 236(1–2), 133–178 (2000).
[3]
Avanzini, M., Dal Lago, U., Yamada, A.: On probabilistic term rewriting. Sci. Comput. Program. 185 (2020).
[4]
Avanzini, M., Moser, G., Schaper, M.: A modular cost analysis for probabilistic programs. Proc. ACM Program. Lang. 4(OOPSLA) (2020).
[5]
Baader, F., Nipkow, T.: Term Rewriting and All That. Cambridge University Press (1998).
[6]
Batz, K., Kaminski, B.L., Katoen, J.-P., Matheja, C., Verscht, L.: A calculus for amortized expected runtimes. Proc. ACM Program. Lang. 7(POPL) (2023).
[7]
Beutner, R., Ong, L.: On probabilistic termination of functional programs with continuous distributions. In: Freund, S.N., Yahav, E. (eds.) PLDI 2021, pp. 1312–1326 (2021).
[8]
Bournez O and Kirchner C Tison S Probabilistic rewrite strategies applications to ELAN Rewriting Techniques and Applications 2002 Heidelberg Springer 252-266
[9]
Bournez O and Garnier F Giesl J Proving positive almost-sure termination Term Rewriting and Applications 2005 Heidelberg Springer 323-337
[10]
Chatterjee, K., Fu, H., Novotný, P.: Termination analysis of probabilistic programs with martingales. In: Barthe, G., Katoen, J.-P., Silva, A. (eds.) Foundations of Probabilistic Programming, pp. 221–258. Cambridge University Press (2020).
[11]
Dal Lago U and Grellois C Yang H Probabilistic termination by monadic affine sized typing Programming Languages and Systems 2017 Heidelberg Springer 393-419
[12]
Dal Lago, U., Faggian, C., Della Rocca, S.R.: Intersection types and (positive) almost-sure termination. Proc. ACM Program. Lang. 5(POPL) (2021).
[13]
Faggian, C.: Probabilistic rewriting and asymptotic behaviour: on termination and unique normal forms. Log. Methods Comput. Sci. 18(2) (2022).
[14]
Ferrer Fioriti, L.M., Hermanns, H.: Probabilistic termination: soundness, completeness, and compositionality. In: Rajamani, S.K., Walker, D. (eds.) POPL 2015, pp. 487–501 (2015).
[15]
Giesl J, Thiemann R, and Schneider-Kamp P Baader F and Voronkov A The dependency pair framework: combining techniques for automated termination proofs Logic for Programming, Artificial Intelligence, and Reasoning 2005 Heidelberg Springer 301-331
[16]
Giesl J, Thiemann R, Schneider-Kamp P, and Falke S Mechanizing and improving dependency pairs J. Autom. Reason. 2006 37 3 155-203
[17]
Giesl J et al. Analyzing program termination and complexity automatically with AProVE J. Autom. Reason. 2017 58 1 3-31
[18]
Giesl J, Rubio A, Sternagel C, Waldmann J, and Yamada A Beyer D, Huisman M, Kordon F, and Steffen B The termination and complexity competition Tools and Algorithms for the Construction and Analysis of Systems 2019 Cham Springer 156-166
[19]
Giesl J, Giesl P, and Hark M Fontaine P Computing expected runtimes for constant probability programs Automated Deduction – CADE 27 2019 Cham Springer 269-286
[20]
Gramlich B Abstract relations between restricted termination and confluence properties of rewrite systems Fundam. Informaticae 1995 24 2-23
[21]
Hirokawa N and Middeldorp A Automating the dependency pair method Inf. Comput. 2005 199 1–2 172-199
[22]
Huang, M., Fu, H., Chatterjee, K., Goharshady, A.K.: Modular verification for almost-sure termination of probabilistic programs. Proc. ACM Program. Lang. 3(OOPSLA) (2019).
[23]
Kaminski BL, Katoen J-P, Matheja C, and Olmedo F Weakest precondition reasoning for expected runtimes of randomized algorithms J. ACM 2018 65 1-68
[24]
Kaminski, B.L., Katoen, J.-P., Matheja, C.: Expected runtime analysis by program verification. In: Barthe, G., Katoen, J.-P., Silva, A. (eds.) Foundations of Probabilistic Programming, pp. 185–220. Cambridge University Press (2020).
[25]
Kassing JC and Giesl J Pientka B and Tinelli C Proving almost-sure innermost termination of probabilistic term rewriting using dependency pairs Automated Deduction 2023 Cham Springer 344-364
[26]
Kassing, J.-C., Dollase, S., Giesl, J.: A complete dependency pair framework for almost-sure innermost termination of probabilistic term rewriting. CoRR abs/2309.00344 (2023).
[27]
Kassing, J.-C., Frohn, F., Giesl, J.: From innermost to full almost-sure termination of probabilistic term rewriting. In: In: Kobayashi, N., Worrell, J. (eds.) FoSSaCS 2024. LNCS, vol. 14575, pp. 206–228. Springer, Cham (2024). Long version available at CoRR abs/2310.06121. https://doi.org/10.48550/arXiv.2310.06121
[28]
Lankford, D.S.: On Proving Term Rewriting Systems are Noetherian. Memo MTP-3, Mathematics Department, Louisiana Technical University, Ruston, LA (1979). http://www.ens-lyon.fr/LIP/REWRITING/TERMINATION/Lankford_Poly_Term.pdf
[29]
Leutgeb L, Moser G, and Zuleger F Shoham S and Vizel Y Automated expected amortised cost analysis of probabilistic data structures Computer Aided Verification 2022 Cham Springer 70-91
[30]
McIver, A., Morgan, C., Kaminski, B.L., Katoen, J.-P.: A new proof rule for almost-sure termination. Proc. ACM Program. Lang. 2(POPL) (2018).
[31]
Meyer F, Hark M, and Giesl J Groote JF and Larsen KG Inferring expected runtimes of probabilistic integer programs using expected sizes Tools and Algorithms for the Construction and Analysis of Systems 2021 Cham Springer 250-269
[32]
Moosbrugger M, Bartocci E, Katoen JP, and Kovács L Yoshida N Automated termination analysis of polynomial probabilistic programs Programming Languages and Systems 2021 Cham Springer 491-518
[33]
Ngo, V.C., Carbonneaux, Q., Hoffmann, J.: Bounded expectations: resource analysis for probabilistic programs. In: Foster, J.S, Grossman, D. (eds.) PLDI 2018, pp. 496–512 (2018).
[35]
Wang, D., Kahn, D.M., Hoffmann, J.: Raising expectations: automating expected cost analysis with types. Proc. ACM Program. Lang. 4(ICFP) (2020).

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings
Functional and Logic Programming: 17th International Symposium, FLOPS 2024, Kumamoto, Japan, May 15–17, 2024, Proceedings
May 2024
335 pages
ISBN:978-981-97-2299-0
DOI:10.1007/978-981-97-2300-3
  • Editors:
  • Jeremy Gibbons,
  • Dale Miller

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 21 June 2024

Qualifiers

  • Article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 28 Dec 2024

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media