Radoslaw Klimek

Radoslaw Klimek, Leszek Kotulski

The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge representation of user/inhabitant behaviors in multi-agent systems. IoT networks are considered as graph structures. Dynamic preference models, understood as a priority in the selecting, is also introduced. Preference models as a result of observed behaviors base on formal logic, and they are built on-the-fly by software agents. Software agents gather knowledge about user preferences expressed in terms of logical specifications as well as suggest on-the-fly future behavior basing on the logical inference process using the semantic tableaux method. The predictive processes are result of some new and important events in the context of IoT systems that should meet a response. Due to the ubiquitous availability of cyber systems that interact with physical environments, there is a great need to develop technologies that target the whole IoT system as a context-awareness system. Formal approach increases the trustworthy of a system. A simple yet illustrative example is provided.

Radoslaw Klimek

The work relates to the automatic generation of logical specifications, considered as sets of temporal logic formulas, extracted directly from developed software models. The extraction process is based on the assumption that the whole developed model is structured using only predefined workflow patterns. A method of automatic transformation of workflow patterns to logical specifications is proposed. Applying the presented concepts enables bridging the gap between the benefits of deductive reasoning for the correctness verification process and the difficulties in obtaining complete logical specifications for this process.

Radoslaw Klimek, Leszek Kotulski

This work relates to context-awareness of things that belong to IoT networks. Preferences understood as a priority in selection are considered, and dynamic preference models for such systems are built. Preference models are based on formal logic, and they are built on-the-fly by software agents observing the behavior of users/inhabitants, and gathering knowledge about preferences expressed in terms of logical specifications. A 3-level structure of agents has been introduced to support IoT inference. These agents cooperate with each other basing on the graph representation of the system knowledge. An example of such a system is presented.

Radoslaw Klimek

The work concerns automatic generation of logical specifications from requirements models. Logical specifications obtained in such a way can be subjected to formal verification using deductive reasoning. Formal verification concerns correctness of a model behaviour. Reliability of the requirements engineering is essential for all phases of software development processes. Deductive reasoning is an important alternative among other formal methods. However, logical specifications, considered as sets of temporal logic formulas, are difficult to specify manually by inexperienced users and this fact can be regarded as a significant obstacle to practical use of deduction-based verification tools. A method of building requirements models using some UML diagrams, including their logical specifications, is presented step by step. Organizing activity diagrams into predefined workflow patterns enables automated extraction of logical specifications. The crucial aspect of the presented approach is integrating the requirements engineering phase and the automatic generation of logical specifications. A system of the deduction-based verification is proposed. The reasoning process could be based on the semantic tableaux method. A simple yet illustrative example of the requirements elicitation and verification is provided.

Radoslaw Klimek

The work concerns formal verification of workflow-oriented software models using deductive approach. The formal correctness of a model's behaviour is considered. Manually building logical specifications, which are considered as a set of temporal logic formulas, seems to be the significant obstacle for an inexperienced user when applying the deductive approach. A system, and its architecture, for the deduction-based verification of workflow-oriented models is proposed. The process of inference is based on the semantic tableaux method which has some advantages when compared to traditional deduction strategies. The algorithm for an automatic generation of logical specifications is proposed. The generation procedure is based on the predefined workflow patterns for BPMN, which is a standard and dominant notation for the modeling of business processes. The main idea for the approach is to consider patterns, defined in terms of temporal logic,as a kind of (logical) primitives which enable the transformation of models to temporal logic formulas constituting a logical specification. Automation of the generation process is crucial for bridging the gap between intuitiveness of the deductive reasoning and the difficulty of its practical application in the case when logical specifications are built manually. This approach has gone some way towards supporting, hopefully enhancing our understanding of, the deduction-based formal verification of workflow-oriented models.