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soict14

Abstract

Many works related to software engineering rely upon formal models, e.g., to perform model-checking or automatic test case generation. Nonetheless, producing such models is usually tedious and error-prone. Model inference is a research field helping in producing models by generating partial models from documentation or execution traces (observed action sequences). This paper presents a new model generation method combining model inference and expert systems. It appears that an engineer is able to recognize the functional behaviors of an application from its traces by applying deduction rules. We propose a framework, applied to Web applications, simulating this reasoning mechanism, with inference rules organized into layers. Each yields partial IOSTSs (Input Output Symbolic Transition Systems), which become more and more abstract and understandable.

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[PhD] Soict'14

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