Towards Constraint Logic Programming over Strings for Test Data Generation

TL;DR

This paper explores the use of constraint logic programming over strings to generate diverse and privacy-compliant test data, demonstrating its application in creating IBANs and calendar dates.

Contribution

It introduces a prototype CLP solver for string constraints and evaluates its effectiveness in generating specific test data types.

Findings

Successfully generated IBAN numbers and calendar dates

Demonstrated potential for privacy-preserving test data generation

Showed feasibility of CLP over strings for test data creation

Abstract

In order to properly test software, test data of a certain quality is needed. However, useful test data is often unavailable: Existing or hand-crafted data might not be diverse enough to enable desired test cases. Furthermore, using production data might be prohibited due to security or privacy concerns or other regulations. At the same time, existing tools for test data generation are often limited. In this paper, we evaluate to what extent constraint logic programming can be used to generate test data, focussing on strings in particular. To do so, we introduce a prototypical CLP solver over string constraints. As case studies, we use it to generate IBAN numbers and calender dates.