An SMT-Based Concolic Testing Tool for Logic Programs

Fortz, Sophie; Mesnard, Frédéric; Payet, Étienne; Perrouin, Gilles; Vanhoof, Wim; Vidal, Germán

doi:10.1007/978-3-030-59025-3_13

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…We plan to investigate heuristics to distinguish both cases. Another interesting avenue for future research is to combine our approach with more directed testing techniques, such as, e.g., concolic testing [17].…”

Section: Discussionmentioning

confidence: 99%

Testing Your (Static Analysis) Truths

Casso

Morales

López-García

et al. 2021

Lecture Notes in Computer Science

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Static analysis is nowadays an essential component of many software development toolsets. Despite some notorious successes in the validation of compilers, comparatively little work exists on the systematic validation of static analyzers, whose correctness and reliability is critical if they are to be inserted in production environments. Contributing factors may be the intrinsic difficulty of formally verifying code that is quite complex and of finding suitable oracles for testing it. In this paper, we propose a simple, automatic method for testing abstract interpretationbased static analyzers. Broadly, it consists in checking, over a suite of benchmarks, that the properties inferred statically are satisfied dynamically. The main advantage of our approach is its simplicity, which stems directly from framing it within the Ciao assertion-based validation framework, and its blended static/dynamic assertion checking approach. We show that in this setting, the analysis can be tested with little effort by combining the following components already present in the framework: the static analyzer, the assertion run-time checking mechanism, the random test case generator, and the unit-test framework . Together they compose a tool that can effectively discover and locate errors in the different components of the analysis framework. We apply our approach to test some of CiaoPP's analysis domains over a wide range of programs, successfully finding non-trivial, previously undetected bugs, with a low degree of effort.logic programming Partially funded by MICINN PID2019-108528RB-C21 ProCode and the Madrid P2018/TCS-4339 BLOQUES-CM program.

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Section: Discussionmentioning

confidence: 99%

Testing Your (Static Analysis) Truths

Casso

Morales

López-García

et al. 2021

Lecture Notes in Computer Science

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“…In turn, Fortz et al (2020) essentially showed that one could rely on an SMT solver to implement a concolic testing tool for Prolog. The paper is focused on designing a more efficient alternative implementation of contest, as well as trying to avoid the unsoundness of the original approach by Mesnard et al (2015a).…”

Section: Related Workmentioning

confidence: 99%

Concolic Testing in CLP

Mesnard¹,

Payet²,

Vidal³

2020

Theory and Practice of Logic Programming

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Concolic testing is a popular software verification technique based on a combination of concrete and symbolic execution. Its main focus is finding bugs and generating test cases with the aim of maximizing code coverage. A previous approach to concolic testing in logic programming was not sound because it only dealt with positive constraints (by means of substitutions) but could not represent negative constraints. In this paper, we present a novel framework for concolic testing of CLP programs that generalizes the previous technique. In the CLP setting, one can represent both positive and negative constraints in a natural way, thus giving rise to a sound and (potentially) more efficient technique. Defining verification and testing techniques for CLP programs is increasingly relevant since this framework is becoming popular as an intermediate representation to analyze programs written in other programming paradigms.

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An SMT-Based Concolic Testing Tool for Logic Programs

Cited by 2 publications

References 13 publications

Testing Your (Static Analysis) Truths

Testing Your (Static Analysis) Truths

Concolic Testing in CLP

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