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Checkification: A Practical Approach for Testing Static Analysis Truths.

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Title: Checkification: A Practical Approach for Testing Static Analysis Truths.
Authors: FERREIRO, DANIELA, CASSO, IGNACIO, MORALES, JOSE F., LÓPEZ-GARCÍA, PEDRO, HERMENEGILDO, MANUEL V.
Source: Theory & Practice of Logic Programming; Sep2025, Vol. 25 Issue 5, p829-866, 38p
Subject Terms: ASSERTIONS (Logic), COMPUTER software testing, SOURCE code, EMPIRICAL research, DEFECT tracking (Computer software development)
Abstract: Static analysis is an essential component of many modern software development tools. Unfortunately, the ever-increasing complexity of static analyzers makes their coding error-prone. Even analysis tools based on rigorous mathematical techniques, such as abstract interpretation, are not immune to bugs. Ensuring the correctness and reliability of software analyzers is critical if they are to be inserted in production compilers and development environments. While compiler validation has seen notable success, formal validation of static analysis tools remains relatively unexplored. In this paper we present checkification , a simple, automatic method for testing 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 lies in its simplicity, which stems directly from framing it within the Ciao assertion-based validation framework, and its blended static/dynamic assertion checking approach. We demonstrate that in this setting, the analysis can be tested with little effort by combining the following components already present in the framework: 1) the static analyzer , which outputs its results as the original program source with assertions interspersed; 2) the assertion run-time checking mechanism, which instruments a program to ensure that no assertion is violated at run time; 3) the random test case generator , which generates random test cases satisfying the properties present in assertion preconditions; and 4) the unit-test framework , which executes those test cases. We have applied our approach to the CiaoPP static analyzer, resulting in the identification of many bugs with reasonable overhead. Most of these bugs have been either fixed or confirmed, helping us detect a range of errors not only related to analysis soundness but also within other aspects of the framework. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:Static analysis is an essential component of many modern software development tools. Unfortunately, the ever-increasing complexity of static analyzers makes their coding error-prone. Even analysis tools based on rigorous mathematical techniques, such as abstract interpretation, are not immune to bugs. Ensuring the correctness and reliability of software analyzers is critical if they are to be inserted in production compilers and development environments. While compiler validation has seen notable success, formal validation of static analysis tools remains relatively unexplored. In this paper we present checkification , a simple, automatic method for testing 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 lies in its simplicity, which stems directly from framing it within the Ciao assertion-based validation framework, and its blended static/dynamic assertion checking approach. We demonstrate that in this setting, the analysis can be tested with little effort by combining the following components already present in the framework: 1) the static analyzer , which outputs its results as the original program source with assertions interspersed; 2) the assertion run-time checking mechanism, which instruments a program to ensure that no assertion is violated at run time; 3) the random test case generator , which generates random test cases satisfying the properties present in assertion preconditions; and 4) the unit-test framework , which executes those test cases. We have applied our approach to the CiaoPP static analyzer, resulting in the identification of many bugs with reasonable overhead. Most of these bugs have been either fixed or confirmed, helping us detect a range of errors not only related to analysis soundness but also within other aspects of the framework. [ABSTRACT FROM AUTHOR]
ISSN:14710684
DOI:10.1017/S1471068425100069