Nguyen, Duy Cu ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Tonella, Paolo; Fondazione Bruno Kessler- FBK > SE Unit
Marchetto, Alessandro; Fondazione Bruno Kessler - FBK > SE Unit
Lakhotia, Kiran; University College London - UCL
Harman, Mark; University College London - UCL
Language :
English
Title :
Automated Generation of State Abstraction Functions using Data Invariant Inference
Publication date :
18 May 2013
Number of pages :
7
Event name :
8th International Workshop on Automation of Software Test (AST’13)
Event date :
May 18-19
References of the abstract :
Model based testing relies on the availability of models that can be defined manually or by means of model inference techniques. To generate models that include meaningful state abstractions, model inference requires a set of abstraction functions as input. However, their specification is difficult and involves substantial manual effort. In this paper, we investigate a technique to automatically infer both the abstraction functions necessary to perform state abstraction and the finite state models based on such abstractions. The proposed approach uses a combi- nation of clustering, invariant inference and genetic algorithms to optimize the abstraction functions along three quality attributes that characterize the resulting models: size, determinism and infeasibility of the admitted behaviors. Preliminary results on a small e-commerce application are extremely encouraging because the automatically produced models include the set of manually defined gold standard models.
