Agent-oriented approaches for model-based software testing: A mapping study

 

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Autoři: Ramírez Méndez, Jose Pablo, Quesada López, Christian Ulises, Martínez Porras, Alexandra, Jenkins Coronas, Marcelo
Médium: comunicación de congreso
Datum vydání:2021
Popis:Automated software testing reduces manual work, increases test coverage, and improves error detection. Model-Based Testing (MBT) is a testing approach that automatically executes test cases generated from a model representing the system behavior. The parallelization of MBT process stages, such as model creation and exploration, or test case generation and execution, could improve its scalability to handle complex systems. Agent-Oriented Software Testing (AOST) refers to the use of intelligent agents focusing on the automation of complex testing tasks. AOST could improve the testing process by providing a high level of decomposition, independence, parallel activation, intelligence, autonomy, sociality, mobility, and adaptation. In this work, we conducted a systematic mapping study of the existing AOST approaches for MBT. We identified 36 primary studies over the period 2002–2020. We classified agent approaches according to the MBT process stages, and tasks and roles covered as part of their implementation. We found 25 implemen- tations of AOST approaches in the test case generation stage, 20 in the test execution, 10 in the model construction, and 3 in the test criteria selection. Studies reported the test generator role 25 times, test executor role 20 times, and the monitor-coordinator of activities 12 times. Additional studies to understand the benefits of agent-oriented approaches for model-based testing are required.
Země:Kérwá
Instituce:Universidad de Costa Rica
Repositorio:Kérwá
Jazyk:Inglés
OAI Identifier:oai:kerwa.ucr.ac.cr:10669/102208
On-line přístup:https://hdl.handle.net/10669/102208
https://doi.org/10.1007/978-3-030-68285-9_33
Klíčové slovo:model-based testing
agent-oriented testing
systematic mapping review