  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 prioritization as part of a continuous
integration framework. These mechanisms are currently using simple entities
called test cases that are concretely realized as executable scripts. Our key
idea is to provide test cases with more reasoning, adaptive behavior 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 decentralization 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 behavior. 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.
