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Test Agents: Adaptive, Autonomous and Intelligent Test Cases

Fulltext:


Publication Type:

Report

Venue:

Computing Research Repository


Abstract

Growth of software size, lack of resources to perform regression testing, and failure to detect bugs faster have seen increased reliance on continuous integration and test automation. Even with greater hardware and software resources dedicated to test automation, software testing is faced with enormous challenges, resulting in increased dependence on complex mechanisms for automated test case selection and prioritisation as part of a continuous integration framework. These mechanisms are currently using simple entities called test cases that are concretely realised as executable scripts. Our key idea is to provide test cases with more reasoning, adaptive behaviour and learning capabilities by using the concepts of intelligent software agents. We refer to such test cases as test agents. The model that underlie a test agent is capable of flexible and autonomous actions in order to meet overall testing objectives. Our goal is to increase the decentralisation of regression testing by letting test agents to know for themselves when they should be executing, how they should update their purpose, and when they should interact with each other. In this paper, we envision software test agents that display such adaptive autonomous behaviour. Emerging developments and challenges regarding the use of test agents are explored-in particular, new research that seeks to use adaptive autonomous agents in software testing.

Bibtex

@techreport{Enoiu5138,
author = {Eduard Paul Enoiu and Mirgita Frasheri },
title = {Test Agents: Adaptive, Autonomous and Intelligent Test Cases},
month = {February},
year = {2018},
url = {http://www.es.mdh.se/publications/5138-}
}