Web-based labs are key tools for distance education that help to illustrate scientific phenomena, which require costly or difficult-to-assemble equipment. Easy Java Simulations (EJS) is an authoring tool that speeds up the creation of these kind of labs. An excellent proof of the EJS potential is the open source physics (OSP) repository, which hosts hundreds of free EJS labs. Learning management systems, such as Moodle, provide social contexts where students interact with each other. The work described in this paper looks for the synergy of both tools, EJS and Moodle, by supporting the deployment of EJS labs into Moodle and thus enriching them with social features (e.g., chat, forums, and videoconference). To test this approach, the authors have created the ball and beam lab, which helps students of automatic control engineering to train different advanced techniques (robust, fuzzy, and reset control), and compare their performance in relation to a conventional proportional-integral-derivative control.

Virtual and remote laboratories (VRLs) are e-learning resources that enhance the accessibility of experimental setups providing a distance teaching framework which meets the student's hands-on learning needs. In addition, online collaborative communication represents a practical and a constructivist method to transmit the knowledge and experience from the teacher to students, overcoming physical distance and isolation. This paper describes the extension of two open source tools: (1) the learning management system Moodle, and (2) the tool to create VRLs Easy Java Simulations (EJS). Our extension provides: (1) synchronous collaborative support to any VRL developed with EJS (i.e., any existing VRL written in EJS can be automatically converted into a collaborative lab with no cost), and (2) support to deploy synchronous collaborative VRLs into Moodle. Using our approach students and/or teachers can invite other users enrolled in a Moodle course to a real-time collaborative experimental session, sharing and/or supervising experiences at the same time they practice and explore experiments using VRLs.

Many analyses on configurable software systems are intractable when confronted with colossal and highly-constrained configuration spaces. These analyses could instead use statistical inference, where a tractable sample accurately predicts results for the entire space. To do so, the laws of statistical inference requires each member of the population to be equally likely to be included in the sample, i.e., the sampling process needs to be “uniform”. SAT-samplers have been developed to generate uniform random samples at a reasonable computational cost. However, there is a lack of experimental validation over colossal spaces to show whether the samplers indeed produce uniform samples or not. This paper (i) proposes a new sampler named , (ii) presents a new statistical test to verify sampler uniformity, and (iii) reports the evaluation of and five other state-of-the-art samplers: , , , , and . Our experimental results show only satisfies both scalability and uniformity.