Abstract
Data races, a condition where two memory accesses to the same memory location occur concurrently, have been shown to be a major source of concurrency bugs in distributed systems. Unfortunately, data races are often triggered by non-deterministic event orderings that are hard to detect when testing complex distributed systems. In this paper, we propose Spider, an automated tool for identifying data races in distributed system traces. Spider encodes the causal relations between the events in the trace as a symbolic constraint model, which is then fed into an SMT solver to check for the presence of conflicting concurrent accesses. To reduce the constraint solving time, Spider employs a pruning technique aimed at removing redundant portions of the trace. Our experiments with multiple benchmarks show that Spider is effective in detecting data races in distributed executions in a practical amount of time, providing evidence of its usefulness as a testing tool. © Springer Nature Switzerland AG 2020.

Abstract
In today’s software industry, systems are constantly changing. To maintain their quality and to prevent failures at controlled costs is a challenge. One way to foster quality is through thorough and systematic testing. Therefore, the definition of adequate tests is crucial for saving time, cost and effort. This paper presents a framework that generates software test cases automatically based on user interaction data. We propose a data-driven software test generation solution that combines the use of frequent sequence mining and Markov chain modeling. We assess the quality of the generated test cases by empirically evaluating their coverage with respect to observed user interactions and code. We also measure the plausibility of the distribution of the events in the generated test sets using the Kullback-Leibler divergence. © 2020, Springer Nature Switzerland AG.

Abstract
There are countless reasons cited in scientific studies to explain the difficulties in programming learning. The reasons range from the subject's complexity, the ineffective teaching and study methods, to psychological aspects such as demotivation. Still, learning programming often boils down to practice on exercise solving. Hence, it is essential to understand that the nature of a programming exercise is an important factor for the success and consistent learning. This paper explores different approaches on the creation of a programming exercise, starting with realizing how it is currently formalized, presented and evaluated. From there, authors suggest variations that seek to broaden the way an exercise is solved and, with this diversity, increase student engagement and learning outcome. The several types of exercises presented can use gamification techniques fostering student motivation. To contextualize the student with his peers, we finish presenting metrics that can be obtained by existing automatic assessment tools. 2012 ACM Subject Classification Applied computing ! Education.

Abstract
Learning programming relies on practicing it which is often hampered by the barrier of difficulty. The combined use of automated assessment, which provides fast feedback to the students experimenting with their code, and gamification, which provides additional motivation for the students to intensify their learning effort, can help pass the barrier of difficulty in learning programming. In such environment, students keep receiving the relevant feedback no matter how many times they try (thanks to automated assessment), and their engagement is retained (thanks to gamification). While there is a number of open software and programming exercise collections supporting automated assessment, up to this date, there are no available open collections of gamified programming exercises, no open interactive programming learning environment that would support such exercises, and even no open standard for the representation of such exercises so that they could be developed in different educational institutions and shared among them. This gap is addressed by Framework for Gamified Programming Education (FGPE), an international project whose primary objective is to provide necessary prerequisites for the application of gamification to programming education, including a dedicated gamification scheme, a gamified exercise format and exercises conforming to it, software for editing the exercises and an interactive learning environment capable of presenting them to students. This paper presents the FGPE project, its architecture and main components, as well as the results achieved so far. 2012 ACM Subject Classification Social and professional topics ! Computer science education.

Abstract
Little is known about the impact of the addition of each stimulus in multisensory augmented reality experiences in cultural heritage contexts. This paper investigates the impact of different sensory conditions on a users sense of presence, enjoyment, knowledge about the cultural site, and value of the experience. Five different multisensory conditions, namely, Visual, Visual+ Audio, Visual +Smell, and Visual + Audio + Smell conditions, and regular visit referred to as None condition, were evaluated by a total of 60 random visitors distributed across the specified conditions. According to the results, the addition of particular types of stimuli created a different impact on the sense of presence subscale scores, namely, on spatial presence, involvement, and experienced realism, but did not influence the overall presence score. Overall, the results revealed that the addition of stimuli improved enjoyment and knowledge scores and did not affect the value of the experience scores. We concluded that each stimulus has a differential impact on the studied variables, demonstrating that its usage should depend on the goal of the experience: smell should be used to privilege realism and spatial presence, while audio should be adopted when the goal is to elicit involvement.

Abstract
Currently, the use of free and open-source software is increasing. The flexibility, availability, and maturity of this software could be a key driver to develop useful and interesting solutions. In general, open-source solutions solve specific tasks that can replace commercial solutions, which are often very expensive. This is even more noticeable in areas requiring analysis and manipulation/visualization of a large volume of data. Considering that there is a major gap in the development of web applications for photogrammetric processing, based on open-source technologies that offer quality results, the application presented in this article is intended to explore this niche. Thus, in this article a solution for photogrammetric processing is presented, based on the integration of MicMac, GeoServer, Leaflet, and Potree software. The implemented architecture, focusing on open-source software for data processing and for graphical manipulation, visualization, measuring, and analysis, is presented in detail. To assess the results produced by the proposed web application, a case study is presented, using imagery acquired from an unmanned aerial vehicle in two different areas.