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Computer Science > Software Engineering

arXiv:2103.07370 (cs)
[Submitted on 12 Mar 2021 (v1), last revised 18 Mar 2021 (this version, v2)]

Title:Test case generation for agent-based models: A systematic literature review

Authors:Andrew G. Clark, Neil Walkinshaw, Robert M. Hierons
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Abstract:Agent-based models play an important role in simulating complex emergent phenomena and supporting critical decisions. In this context, a software fault may result in poorly informed decisions that lead to disastrous consequences. The ability to rigorously test these models is therefore essential. In this systematic literature review, we answer five research questions related to the key aspects of test case generation in agent-based models: What are the information artifacts used to generate tests? How are these tests generated? How is a verdict assigned to a generated test? How is the adequacy of a generated test suite measured? What level of abstraction of an agent-based model is targeted by a generated test? Our results show that whilst the majority of techniques are effective for testing functional requirements at the agent and integration levels of abstraction, there are comparatively few techniques capable of testing society-level behaviour. Additionally, we identify a need for more thorough evaluation using realistic case studies that feature challenging properties associated with a typical agent-based model.
Subjects: Software Engineering (cs.SE); Multiagent Systems (cs.MA)
Cite as: arXiv:2103.07370 [cs.SE]
  (or arXiv:2103.07370v2 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2103.07370
Related DOI: https://doi.org/10.1016/j.infsof.2021.106567

Submission history

From: Andrew Clark [view email]
[v1] Fri, 12 Mar 2021 16:07:12 UTC (9,182 KB)
[v2] Thu, 18 Mar 2021 09:56:13 UTC (1,051 KB)
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