Abstract
Forecasts of the effort or delivery date can play an important role in managing software projects, but the estimates provided by development teams are often inaccurate and time-consuming to produce. This is not surprising given the uncertainty that underlies this activity. This work studies the use of Monte Carlo simulations for generating forecasts based on project historical data. We have designed and run experiments comparing these forecasts against what happened in practice and to estimates provided by developers, when available. Comparisons were made based on the mean magnitude of relative error (MMRE). We did also analyze how the forecasting accuracy varies with the amount of work to be forecasted and the amount of historical data used. To minimize the requirements on input data, delivery date forecasts for a set of user stories were computed based on takt time of past stories (time elapsed between the completion of consecutive stories); effort forecasts were computed based on full-time equivalent (FTE) hours allocated to the implementation of past stories. The MMRE of delivery date forecasting was 32% in a set of 10 runs (for different projects) of Monte Carlo simulation based on takt time. The MMRE of effort forecasting was 20% in a set of 5 runs of Monte Carlo simulation based on FTE allocation, much smaller than the MMRE of 134% of developers' estimates. A better forecasting accuracy was obtained when the number of historical data points was 20 or higher. These results suggest that Monte Carlo simulations may be used in practice for delivery date and effort forecasting in agile projects, after a few initial sprints. © 2021 ACM.

Abstract
Secure databases have emerged to securely store and process sensitive data at untrusted infrastructures (e.g., Cloud Computing). To be secure and efficient, the encryption schemes used by these systems must be carefully chosen. Indeed, this task requires expertise both in databases and security, and is currently being done manually, which is time-consuming and error-prone and can lead to security violations, poor performance, or both. This paper presents ATOCS, a novel framework that analyses the applications' code and, from the inferred requirements, determines the best combination of encryption schemes and related configurations for the underlying secure NoSQL database. Its design is modular and extensible thus facilitating the support of different applications and database solutions. Our evaluation with real-world applications shows that ATOCS is fast (it takes 44 seconds to analyse more than 12K LoC), accurate, and simplifies the configuration of secure databases.

Abstract
Although new, renewed, and innovative museum experiences are constantly provided to the sighted public, millions of visually impaired persons worldwide are still deprived of access to enjoying and engaging with collections. This research aims to investigate the limitations of blind or partially sighted persons in visiting a museum nowadays. Semistructured interviews with seventy-two visually impaired Portuguese individuals revealed reasons and factors that contribute to positive and negative visiting experiences, and the assessment of sixteen accessibility resources demonstrates their frequency and potential usefulness in museum visits. It concludes that the actual limited experiences in museums could be surpassed and enhanced by moving beyond accessibility, embracing inclusion, and focusing on the creation of multimodal and multisensory approaches to promote exceptional, memorable, and exciting visiting opportunities for all.

Abstract
This extended abstract reports on on-going research on quantum algorithmic approaches to the problem of generalised tree search that may exhibit effective quantum speedup, even in the presence of non-constant branching factors. Two strategies are briefly summarised and current work outlined.

Abstract
Mobile devices have become indispensable in our daily life and reducing the energy consumed by them has become essential. However, developing energy-efficient mobile applications is not a trivial task. To address this problem, we present EcoAndroid, an Android Studio plugin that automatically applies energy patterns to Java source code. It currently supports ten different cases of energy-related refactorings, divided over five energy patterns taken from the literature. We used EcoAndroid to analyze 100 Java mobile applications (approximate to 1.5M LOC) and we found that 35 of the projects had a total of 95 energy code smells. EcoAndroid was able to automatically refactor all the code smells identified.

Abstract
Hands are the most important tool to interact with virtual environments, and they should be available to perform the most critical tasks. For example, a surgeon in VR should keep his/her hands on the instruments and be able to do secondary tasks without performing a disruptive event to the operative task. In this common scenario, one can observe that hands are not available for interaction. The goal of this systematic review is to survey the literature and identify which hands-free interfaces are used, the performed interaction tasks, what metrics are used for interface evaluation, and the results of such evaluations. From 79 studies that met the eligibility criteria, the voice is the most studied interface, followed by the eye and head gaze. Some novel interfaces were brain interfaces and face expressions. System control and selection represent most of the interaction tasks studied and most studies evaluate interfaces for usability. Despite the best interface depending on the task and study, the voice was found to be versatile and showed good results amongst the studies. More research is recommended to improve the practical use of the interfaces and to evaluate the interfaces more formally.