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Internet Protocol Television (IPTV) has had a significant impact on live TV content consumption in the past decade, as improvements in the broadband speed have allowed more data volume to be delivered. In addition to existing infrastructure, which is mostly based on the set top boxes, new content providers have emerged, utilizing newly developed proprietary streaming platforms. As the number of IPTV users grew, more volume and variety of data became available for analysis. By analyzing stored user actions, it is possible to create a multivariate time series that represents user behavior over time. The approach presented in the paper is based on multivariate time series generation from user data and determining the similarity between them. Time series are created for each user based on the proposed quantified action sets, grouped in the feature groups and summarized over time. The action sets and feature groups can be adjusted to a certain IPTV platform. The end result of the analysis is the similarity score matrix, generated by calculating the similarities of all users’ time series, where the similarity measure calculation can be chosen arbitrarily.

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.