Bike-sharing systems (BSS) have raised in popularity in the last years due to their potential share in sustainable cities. Although the first attempts to implement a bike-sharing public service date back to 1965 (Amsterdam), their widespread use arrived with the millennium becoming a vibrant research area whose activity has increased steadily in the last decade. Several authors have attempted to summarize the current state of the art, but the literature on BSS is still scattered in different fields. Thus, there is a lack of literature that summarizes and categorizes the available research on BSS. In this paper, we perform a thorough review of the challenges behind rebalancing in bike-sharing systems. The objectives of this paper are to collect papers on the repositioning problem in dock-based bike-sharing services, classify them and point to novel research venues. We render a keyword analysis in the literature and a timeline that shows the evolution of those keywords throughout the last decade. We also include an exhaustive table that will assist researchers from different disciplines to address the open challenges in the field and to transition towards more sustainable cities.

Bicycle-sharing systems (BSS) have become an important component of sustainable urban mobility, but their demand remains difficult to model. Usage varies across hours, stations, weather conditions, and types of day, while the available data often provide only a partial view of the underlying demand process. This study proposes an interpretable probabilistic framework to characterize and generate synthetic demand for BiciMad, Madrid's dock-based BSS, using trip-level data from 2018 and 2019. The contribution is not the introduction of new probability distributions, but the calibrated integration of standard probabilistic components into a demand-side generative framework. Trip distances are modeled with Gamma distributions, and hourly trip counts are represented with Negative Binomial distributions conditioned on hour, day type, and precipitation. These components are combined with empirical station-popularity profiles to generate synthetic origin-destination demand under explicit contextual assumptions. Validation against observed data shows that the framework provides calibrated uncertainty estimates, with empirical coverage of the 95% prediction intervals close to the nominal level across contextual scenarios. An external consistency check using 2019 data further shows the practical value of the approach, as it helped identify systematic timestamp misattributions that were later confirmed by the data provider. The proposed framework is not intended as a full capacity-aware operational simulator. Instead, it provides a simple, interpretable, and uncertainty-aware baseline for demand characterization, synthetic demand generation, exploratory disruption analysis, and data-quality consistency checking in dock-based bicycle-sharing systems.

Government-imposed lockdowns have challenged academic institutions to transition from traditional face-to-face education into hybrid or fully remote learning models. This transition has focused on the technological challenge of guaranteeing the continuity of sound pedagogy and granting safe access to online digital university services. However, a key requisite involves adapting the evaluation process as well. In response to this need, the authors of this paper tailored and implemented a cloud deployment to provide universal access to online summative assessment of university students in a computer programming course that mirrored a traditional in-person monitored computer laboratory under strictly controlled exam conditions. This deployment proved easy to integrate with the university systems and many commercial proctoring tools. This cloud deployment is not only a solution for extraordinary situations; it can also be adapted daily for online collaborative coding assignments, practical lab sessions, formative assessments, and masterclasses where the students connect using their equipment. Connecting from home facilitates access to education for students with physical disabilities. It also allows participation with their students' own adapted equipment in the evaluation processes, simplifying assessment for those with hearing or visual impairments. In addition to these benefits and the evident commitment to the safety rules, this solution has proven cheaper and more flexible than on-premise equivalent installations.