What question did this study set out to answer?

This research aims to enhance random testing methodologies using Q-grams for more effective software testing.

February 8, 20260 citationsOpen Access

Adaptive Test Generation with Q-grams

MBMatteo BiagiolaUniversity of St.Gallen RFRobert FeldtChalmers University of Technology PTPaolo TonellaUniversità della Svizzera italiana

Key Points

This research aims to enhance random testing methodologies using Q-grams for more effective software testing.
Discussed the adaptive random testing technique.
Introduced the Q-grams approach for test generation.
Analyzed its efficacy within software engineering contexts.
Demonstrated that Q-grams significantly improve test coverage.
Observed enhanced efficiency in identifying software defects.

Abstract

In this article, we summarize our paper Adaptive Random Testing with Q-grams: The Illusion Comes True BFT25, which has been accepted for presentation at the 33rd ACM International Conference on the Foundations of Software Engineering (FSE 2025).

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