Towards a framework for constraint-based test case generation

Paper

First seen 7/11/2026

Last seen 7/11/2026

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RELATIONSHIPS

25 connections

heap-allocated data structures evaluates → 95% 2e

The paper shows that the technique can deal with arbitrary pointer-based data structures allocated on the heap.

Constraint Handling Rules uses → 95% 2e

Constraint Handling Rules are used to implement propagation rules for environment and heap constraints.

ATGen compares with → 80% 2e

The paper mentions ATGen as an existing tool using symbolic execution for structural coverage.

Spark ADA mentions → 85% 2e

The paper mentions Spark ADA as the target language of the related ATGen tool.

depth-bounded search uses → 95% 2e

The paper uses depth-bounded search to limit exploration of execution paths.

ImpL imperative language uses → 100% 2e

The paper develops its framework in the context of ImpL, a small deterministic imperative language.

CP search strategies uses → 100% 1e

The paper advocates the use of standard CP search strategies to control test case generation.

branch-and-bound optimization uses → 90% 1e

The paper uses branch-and-bound optimization to capture minimality criteria in test selection.

Constraint Propagation uses → 95% 1e

The paper defines constraint propagation rules for the environment and heap mappings.

SWI-Prolog prototype uses → 100% 1e

An initial prototype was developed in SWI-Prolog.

Graphviz uses → 95% 1e

Graphviz is used to visualize input/output pairs involving heap-allocated data structures.

Monadic Constraint Programming framework uses → 90% 1e

The authors are working on a new implementation within the Monadic Constraint Programming framework.

random test data generation compares with → 80% 1e

The paper discusses random test data generation as an existing simpler method in contrast to the proposed approach.

Coverage Criterion evaluates → 90% 1e

The paper discusses generating test cases according to different coverage criteria using CP search strategies.

MC/DC coverage evaluates → 80% 1e

The paper mentions MC/DC coverage as one of the coverage criteria that can be addressed.

Regression Testing mentions → 90% 1e

The paper mentions regression testing as an application for the generated test suites.

Mercury logic programming language mentions → 90% 1e

The paper mentions Mercury as the language used in the previous work that this paper extends.

whitebox testing uses → 95% 1e

The paper applies the whitebox testing approach to generate test cases for structural coverage.

François Degrave authored by → 100% 1e

François Degrave is listed as an author of the paper.

structural coverage uses → 95% 1e

The paper generates test inputs that cover a substantial part of the source code for structural coverage.

Tom Schrijvers authored by → 100% 1e

Tom Schrijvers is listed as an author of the paper.

Wim Vanhoof authored by → 100% 1e

Wim Vanhoof is listed as an author of the paper.

constraint-based test case generation introduces → 100% 1e

The paper proposes an approach for automated test case generation based on constraint programming techniques.

Constraint Programming uses → 100% 1e

The paper uses constraint programming as its foundational technique.

Symbolic Execution uses → 100% 1e

The paper uses symbolic execution to replace unknown values by constraint variables.