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Ant Colony Optimization for Object-Oriented Unit Test Generation

Bruce, D; Menéndez, HD; Barr, ET; Clark, D; (2020) Ant Colony Optimization for Object-Oriented Unit Test Generation. In: Dorigo, M and Stützle, T and Blesa, MJ and Blum, C and Hamann, H and Heinrich, MK and Strobel, V, (eds.) Swarm Intelligence: 12th International Conference, ANTS 2020, Barcelona, Spain, October 26–28, 2020, Proceedings. (pp. pp. 29-41). Springer: Cham, Switzerland. Green open access

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Abstract

Generating useful unit tests for object-oriented programs is difficult for traditional optimization methods. One not only needs to identify values to be used as inputs, but also synthesize a program which creates the required state in the program under test. Many existing Automated Test Generation (ATG) approaches combine search with performance-enhancing heuristics. We present Tiered Ant Colony Optimization (Taco) for generating unit tests for object-oriented programs. The algorithm is formed of three Tiers of ACO, each of which tackles a distinct task: goal prioritization, test program synthesis, and data generation for the synthesised program. Test program synthesis allows the creation of complex objects, and exploration of program state, which is the breakthrough that has allowed the successful application of ACO to object-oriented test generation. Taco brings the mature search ecosystem of ACO to bear on ATG for complex object-oriented programs, providing a viable alternative to current approaches. To demonstrate the effectiveness of Taco, we have developed a proof-of-concept tool which successfully generated tests for an average of 54% of the methods in 170 Java classes, a result competitive with industry standard Randoop.

Type: Proceedings paper
Title: Ant Colony Optimization for Object-Oriented Unit Test Generation
Event: International Conference on Swarm Intelligence: ANTS 2020
ISBN-13: 978-3-030-60375-5
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-60376-2_3
Publisher version: https://doi.org/10.1007/978-3-030-60376-2_3
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10117785
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