Automated Programming Assessment Systems (APAS) are used for overcoming problems associated with manually managed programming assignments, such as objective and efficient assessing in large classes and providing timely and helpful feedback. In this paper we survey the literature and software in this field and identify the set of necessary features that make APAS comprehensive - such that it can support all key stages in the assessment process. Put differently, comprehensive APAS is generic enough to meet the demands of “any” computer science course. Despite the vast number of publications, the choice of software turns out to be very limited. We contribute by developing Edgar, a comprehensive open-source APAS which, to the best of our knowledge, exceeds any other similar free and/or open-source tool. Edgar is the result of three years of development and usage in, for the time being, eight courses dealing with various programming languages and paradigms (C, Java, SQL, etc.). Edgar supports various text-based programming languages, multi-correct multiple-choice questions, provides rich exam logging and monitoring infrastructure to prevent potential fraudulent behaviour, and subsequent data analysis and visualization of students' scores, exams, question quality, etc. It can be deployed on all major operating systems and is written in a modular fashion so that it can be adjusted and scaled to a custom fit. We comment on the architecture and present data from real-world use-cases to support these claims. Edgar is in active use today (1000+ students per semester) and it is being constantly developed with new features.

This paper analyzes Hat, an open-source framework for developing event-driven component-based SCADA applications, and discusses possibilities to add various analytical tools to such platforms. As a part of the contribution, an open-source component called Artificial Intelligence Model Manager (AIMM) has been developed and integrated into a Hat-based SCADA platform. AIMM is extensible through various plugins, allowing the addition of various models for advanced analytics e.g., machine learning tools, statistical tools, etc. The paper describes AIMM architecture and provides a use case in which state estimation was performed in a medium-voltage distribution grid. This case study demonstrates that it is possible to extend component-based SCADA systems with components for advanced analytics with minimal fundamental system changes.

This paper describes some of the most common problems that can occur while writing an engine for flow control in workflow management software. The emphasis is put on implementing workflow control patterns, particularly on splits and matching synchronization points, and on milestones and mutual exclusions. After brief introduction and description of a background of development of a proprietary workflow management system, typical problems are described and solutions are proposed. Finally, a proprietary workflow parsing algorithm is proposed and explained.

Tree comparisons are used in various areas with various statistical or dissimilarity measures. Given that data in various domains are diverse, and a particular comparison approach could be more appropriate for specific applications, there is a need to evaluate different comparison approaches. As gathering real data is often an extensive task, using generated trees provides a faster evaluation of the proposed solutions. This paper presents three algorithms for generating random trees: parametrized by tree size, shape based on the node distribution and the amount of difference between generated trees. The motivation for the algorithms came from unordered trees that are created from class hierarchies in object-oriented programs. The presented algorithms are evaluated by statistical and dissimilarity measures to observe stability, behavior, and impact on node distribution. The results in the case of dissimilarity measures evaluation show that the algorithms are suitable for tree comparison.