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QuickerChick

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Ivan Mladenov, Alperen Keles, Leonidas Lampropoulos

Programming Languages · Submitted 13 Sep 2026

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim In this work, we describe how we optimized QuickChick, exploiting various opportunities offered by program extraction to significantly improve each test's extraction, compilation, and running time.

how it is stated · asserted 1.00 read the record →

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arXiv ID2609.16079 (version 1)
Pith ID5GAHS5RA, Pith's permanent record of this paper and its review
CitationAlperen Keles, Ivan Mladenov, Leonidas Lampropoulos. "QuickerChick." arXiv:2609.16079 (2026). https://pith.science/paper/5GAHS5RA
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,541 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.14 · human participants 0.02 · controlled comparison 0.30 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.49 · mentions code or data availability 0.05.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

Property-based testing (PBT) with QuickChick relies on extracting Rocq programs to OCaml. However, this extraction mechanism, while crucial for QuickChick to function, has significant performance implications. In this work, we describe how we optimized QuickChick, exploiting various opportunities offered by program extraction to significantly improve each test's extraction, compilation, and running time. We also evaluate these improvements using the ETNA benchmarking platform for PBT to assess how individual improvements impacted the overall test run time.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Property-based testing (PBT) with QuickChick relies on extracting Rocq programs to OCaml. background 1.00 0.07 0.03 asserted 1.00
s1 However, this extraction mechanism, while crucial for QuickChick to function, has significant performance implications. background 0.91 0.12 0.05 asserted 1.00
s2 In this work, we describe how we optimized QuickChick, exploiting various opportunities offered by program extraction to significantly improve each test's extraction, compilation, and running time. contribution 0.95 0.95 0.55 asserted 1.00
s3 We also evaluate these improvements using the ETNA benchmarking platform for PBT to assess how individual improvements impacted the overall test run time. method 0.87 0.94 0.08 asserted 0.91

What kind of paper the classifier reports this is: method or tool 0.99 · evidence from observation or experiment 0.94.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Property-based testing (PBT) with QuickChick relies on extracting Rocq programs to OCaml. However, this extraction mechanism, while crucial for QuickChick to function, has significant performance implications. In this work, we describe how we optimized QuickChick, exploiting various opportunities offered by program extraction to significantly improve each test's extraction, compilation, and running time. We also evaluate these improvements using the ETNA benchmarking platform for PBT to assess how individual improvements impacted the overall test run time.

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