Design of intelligent agents for collaborative testing of service-based systems

Abstract

Testing on services-based systems faces the challenges of dynamic collaboration. Services are distributed software that can be bound to establish collaborations on-demand. To verify and validate the services, testing needs to react automatically in a coordinated approach. Software agents, which are characterized by persistence, autonomy, social ability and reactivity, are thus introduced to facilitate test deployment, execution, collaboration, and run-time decision making. This paper proposes a design of test agent model, including agents' knowledge, events, actions and interpreter. The knowledge represents the detected environment status, such as test results and changes in services under test. The action models testing behavior such as test configuration, test deployment and test schedule. The Interpreter defines the rules to select actions or parameters on certain events and conditions. In this way, given a set of knowledge at a certain time, a test agent dynamically adjusts its behavior according to its pre-defined rules and strategies. Case studies and experiments are exercised to apply the generic agent design to specific testing tasks such as performance testing and coverage-based testing.

Aplib: Tactical Agents for Testing Computer Games

“…With aplib we have another usecase, namely automated testing. Using agents for software testing has actually been attempted before [36,33,5,35]. However, these works use agents to test services or web applications, which are software types that can already be handled by non-agent techniques such as model based [43] or search based [20,1] testing, whereas we argued that high interactivity of computer games poses a different level of challenge for automated testing.…”

Test Agents: The Next Generation of Test Cases

“…Distributor agents take assignments and map them to the available testing agents. Other contributions have relied on the agent-based paradigm to specifically target service-oriented systems [15]. The Belief Desire Intention (BDI) agent architecture is used by Rao et al [16] to distinguish between two types of agents: coordinators and runners.…”

Vee@Cloud: The virtual test lab on the cloud

“…In this research, the Multi-Agent Framework is applied to support distributed workload simulation and to achieve adaptability and massive scalability. In our previous work, the MAST framework is designed and applied to testing Internet applications [16].…”