Testing Elastic Systems with Surrogate Models

Abstract—We combine search-based test case generation and surrogate models for black-box system testing of elastic systems. We aim to efficiently generate tests that expose functional errors and performance problems related to system elasticity. Elastic systems dynamically change their resources allocation to provide consistent quality of service in face of workload fluctuations. However, their ability to adapt could be a double edged sword if not properly designed: They may fail to acquire the right amount of resources or even fail to release them. Blackbox system testing may expose such problems by stimulating system elasticity with suitable sequences of interactions. However, finding such sequences is far from trivial because the number of possible combinations of requests over time is unbounded. In this paper, we analyze the problem of generating test cases for elastic systems, we cast it as a search-based optimization combined with surrogate models, and present the conceptual framework that supports its execution. Index Terms—model based testing, load testing, genetic algorithm, surrogate models I