Towards Constraint Logic Programming over Strings for Test Data Generation

Abstract

Software is notoriously hard to test. Some of the difficulties stem from the test data available for data-intensive applications such as data warehouses. Existing test data might not be diverse enough to enable desired test cases, while at the same time the use of real data might be prohibited due to security or privacy concerns or other regulations. However, existing test case generation tools are often too lacking. In this article, we evaluate to what extend 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 a case study, we use it to generate IBAN numbers.

Publication
Accepted for 33rd Workshop on (Constraint) Logic Programming (WLP 2019)
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Sebastian Krings
Postdoc

My research interests include formal methods, model checking and logic programming.

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