This paper explores the analysis of user behavior in information systems through audit records, creating a behavior model represented as a graph. The model captures actions over a specified period, facilitating real-time comparison to identify insider threats exploring anomalies detected in behavior models. "e-StepControl," developed by "ABC software" Ltd., incorporates this approach for monitoring user behavior in different business environments. The study proposes enhancing this solution with automatic user clustering, achieved by grouping individuals exhibiting similar behavior patterns using AI/ML algorithms. The research evaluates various clustering methods, discussing their suitability for grouping users based on their behavior. The subsequent step involves leveraging user class behavior models to identify anomalies by comparing an individual’s actions with the behavior model expected in their specific user group. This extension aims to enhance the system’s ability to detect potentially malicious activities, providing data security administrators with timely alerts in case of deviations from typical behavior.

The paper emphasizes the critical importance of the initial phase in IT project development to avoid implementation errors. It argues that minimizing these errors can be achieved by developing project artifacts at the early stage using a model-driven engineering-based approach. Model transformation plays a basic role in that context. The goal of this paper is to survey publications in which the authors propose generating initial project elements through model-driven engineering and to analyze the level of model transformations offered in their solutions. As a result, the authors would highlight the necessity of understanding which elements of a project can be obtained through automatic transformations and which still require manual manipulation. This distinction is crucial, as it can significantly influence the efficiency and accuracy of the project’s early phases. In general, identifying the project components that can be reliably generated through model transformations helps streamline the project inception and elaboration process performed before IT product implementation.

Improving IS (Information System) end-user experience is one of the most important tasks in the analysis of end-users behaviour, evaluation and identification of its improvement potential. However, the application of Machine Learning methods for the UX (User Experience) usability and effic iency improvement is not widely researched. In the context of the usability analysis, the information about behaviour of end-users could be used as an input, while in the output data the focus should be made on non-trivial or difficult attention-grabbing events and scenarios. The goal of this paper is to identify which data potentially can serve as an input for Machine Learning methods (and accordingly graph theory, transformation methods, etc.), to define dependency between these data and desired output, which can help to apply Machine Learning / graph algorithms to user activity records.

UML diagrams are a base for the planning of development in most software projects. It is used for representing different artefacts during software development and project structure. The use case is one of the diagrams in Unified Modelling Language (UML), which allows describing the dynamic flow of the system. There are a lot of tools that are used for creating this diagram before starting the actual coding process, and the diagram needs to be specific and easily understandable. Meantime, the creation of a UML use case diagram from scratch for complex systems can be time-consuming and confusing for people, which needs to be optimised. The authors of the paper attempt to solve the addressed problem. Therefore, in this research paper a new definition for UML use case diagrams will be introduced, where the main question will be whether it is possible to formalise use case modelling by introducing pre-defined use case patterns. This is academic research and discussion, which is based on the analysis of advanced UML tools, which use case diagram templates contain. The solution to this research question contains an initial set of UML use case patterns, created by analysing of the existing use case diagram templates. Moreover, in order to validate work, the pre-defined patterns were demonstrated on a developed prototype. The operation principle of the prototype focused on giving the ability to the user to construct a use case diagram by the combination of pre-defined patterns. The prototype can be useful for the development/management process in case of correct implementation. It will allow decreasing spent time on the use case diagram creation as well as avoid creating anti-patterns.

In the last 30 years there were numerous model generated software systems offered targeting problems with the development productivity and the resulting software quality. CASE tools developed due today’s date are being advertised as having “complete code-generation capabilities”. Nowadays the Object Management Group (OMG) is calling similar arguments in regards to the Unified Modeling Language (UML) models at different levels of abstraction. It is being said that software development automation using CASE tools enables significant level of automation. Actual today’s CASE tools are usually offering a combination of several features starting with a model editor and a model repository for a traditional ones and ending with code generator (that could be using a scripting or domain-specific (DSL) language), transformation tool to produce the new artifacts from the manually created and transformation definition editor to define new transformations for the most advanced ones. Present paper contains the results of CASE tool (mainly UML editors) comparison against the level of the automation they are offering.