2 research outputs found
Verification of a Rule-Based Expert System by Using SAL Model Checker
Verification of a rule-based expert system ensures
that the knowledge base of the expert system is logically correct
and consistent. Application of verification into a rule-based expert
system is one approach to integrate software engineering
methodology and knowledge base system. The expert system,
which we has built, is a rule-based system developed by using
forward chaining method and Dempster-Shafer theory of belief
functions or evidence. We use Z language as the modelling
language for this expert system and SAL model checker as the
verification tool. To be able to use SAL model checker, Z2SAL will
translate the Z specification, which models the system. In this
paper, we present some parts of our Z specification that represent
some parts of our rule-based expert system. We also present some
parts of our SAL specification and theorems that we added to this
SAL specification. At the last, we present the usage of SAL model
checker over these theorems. Based on these model-checking
processes, we argue that the results are expected. This means that
each of theorems can be model checked and the outputs of those
model checking are the same as the outputs that we obtain from
manual investigation; either it is VALID or INVALID. Other
interpretation of the model check’s results is some parts of our
rule-based expert system have been verified
Inferring models with rule-based expert systems.
International audienceMany 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 (ob-served action sequences). This paper presents a new model generation method combining model inference and expert systems. It appears that an engineer is able to recognise the functional behaviours 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 organised into layers. Each yields partial IOSTSs (Input Output Symbolic Transition Systems), which become more and more abstract and understandable