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Open Access | Just Accepted

Output Type Guided Random Test Case Generation for String Validation Routines

Chenhui Cui1Rubing Huang1( )Jinfu Chen2Yunan Zhou2

1 School of Computer Science and Engineering, Macau University of Science and Technology, Macau 999078, China

2 School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China

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Abstract

String validation routines have been widely used in many real-world applications, such as email validation and postcode validation. String test cases are adopted to test these validation routines, to identify potential defects and security risks. Random Testing (RT) is a well-known testing approach to randomly generate string test cases from the input domain (i.e., the set of all possible test inputs), which is simple to implement at a low cost. However, its testing effectiveness may be unsatisfactory for string validation routines. The main reason for this is that RT may have a high probability to generate invalid rather than valid string test cases, due to its randomness property. This research proposes a new RT approach based on the output types (i.e., valid and invalid strings) for string validation routines, namely Output-type-guided Random Testing (RTO), which attempts to randomly generate both valid and invalid string test cases with a certain probability. This research performed an empirical study involving several real-world string validation routines collected from ten Java open-source projects, to investigate and compare testing performances of RT-O against the previous two widely-used RT methods. The results show that the generated string test cases by RT-O outperform test cases generated by other RT methods.

Tsinghua Science and Technology
Cite this article:
Cui C, Huang R, Chen J, et al. Output Type Guided Random Test Case Generation for String Validation Routines. Tsinghua Science and Technology, 2025, https://doi.org/10.26599/TST.2024.9010023

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Received: 06 November 2023
Revised: 04 January 2024
Accepted: 25 January 2024
Available online: 28 April 2025

© The author(s) 2025

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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