Grey-Box Checking

Abstract

Abstract. There are many cases where we want to verify a system that does not have a usable formal model: the model may be missing, out of date, or simply too big to be used. A possible method is to analyze the system while learning the model (black box checking). However, learning may be an expensive task, thus it needs to be guided, e.g., using the checked property or an inaccurate model (adaptive model checking). In this paper, we consider the case where some of the system components are completely specified (white boxes), while others are unknown (black boxes), giving rise to a grey box system. We provide algorithms and lower bounds, as well as experimental results for this model.

Integration Testing of Distributed Components Based on Learning Parameterized I/O Models

“…As in previous related work [3,4], we adapt Angluin's algorithm [1] to a testing context, in an incremental approach. Our contribution extends this approach in two directions.…”

“…In requirements engineering approaches [7,8], the equivalence query used to get counterexamples is provided by an expert. Here we follow the approach used in [4,3] where the query is implemented by testing the integrated system which acts as an oracle. The outline of the integration methodology is as follows.…”

“…A general approach [4,2,3] is to generate formal models of COTS through their incremental learning. In [6], we proposed an approach to learn I/O models of COTS (using a slight modification of Angluin's Algorithm [1]), and define an Integration Testing Procedure based upon these models.…”

Improving System Reliability Assessment of Safety-Critical Systems using Machine Learning Optimization Techniques

“…Motivated by the fact that numerical model-checking approaches cannot be directly applied to black-box components as a usable formal model is not available, we focus on modelchecking driven black-box testing [6] and statistical model-checking techniques [8]. However, there exist some approaches for interactively learning finite state systems of black-box components (see [9] and [10]), which are proposed as black box checking in [11]. Learning a model is an expensive task, as the interactively learned model has to be adapted due to inaccuracy reasons.…”

Modular System Verification by Inference, Testing and Reachability Analysis

“…In our work, the state k-equivalence relation can be viewed as an approximated equivalence oracle. Learning and testing through model checking approach is used to infer a grey box system [15]. However, the upper bound on the number of states in the system is required to test conformance of the conjectured model to the actual system.…”