Giuseppe Valetto

In recent years, environmental sustainability has emerged as a critical issue for society, prompting governments, local authorities, and private organizations to promote initiatives that encourage more sustainable lifestyles. One such initiative is the AWorld application, which leverages gamification to educate, raise awareness, and inspire positive behavioral changes. The app engages users through personalized challenges, or missions, that require interaction with its features and reward participants with in-game points. In this article, we present a hierarchical Multi-Armed Bandit (MAB) framework, MABTree, designed to replace AWorld’s current random mission assignment with a targeted and adaptive approach guided by a custom reward function. Using real-world interaction data from AWorld, we evaluated MABTree in an offline setting across multiple policies and configurations. Results show that MABTree improves cumulative reward, user coverage, and mission diversity compared to classical MAB baselines, with particularly strong gains in balancing exploration of new features and exploitation of known user preferences. While these findings indicate the potential of MABTree to enhance personalization and engagement in sustainability-focused applications, further online testing is needed to validate its real-world impact on long-term user behavior change.

Unstructured superpeer overlays are an approach to peer-to-peer systems that enables collective organization and ensures the efficient participation and use of divers peers with heterogenous capabilities and resources. Such overlays are, however, vulnerable to failures and attacks that target the superpeers in an attempt to disrupt the overlay. In this paper, we present SODAP (Self-Organized Degree Adaptation Protection), a self-organized strategy for the self-protection of the overlay, based on the local adaptation of a peer's degree in response to disconnections, whether directly detected, or indirectly discovered with the assistance of neighbor peers. When network conditions deteriorate, the SODAP mechanism induces the creation of redundant connections to superpeers, which leads to the adjustment of the entire overlay to a topology that is more resilient to disconnection, while still allowing the system to continue exploiting heterogeneous peer capabilities. When network conditions improve, SODAP responds by reducing peer degrees to reduce redundancy and streamline the topology. We demonstrate this mechanism and evaluate its effectiveness as an extension to Myconet, a self-organized superpeer overlay for unstructured peer-to-peer networks.

In this position paper, we argue that a new methodological paradigm and software platform is required for developing citizen-oriented social computing applications. The platform that we propose is based on the idea of 'Collective Intelligence as a Service', and is grounded in the formalisation of computational models derived from an empirical analysis of psychological processes and social practices. This in turn provides the enablers for developing radically innovative tools for computational sustainability and computer-supported collective action in smart communities (e.g. Smart cities). Our vision is illustrated with two exemplars, one a healthcare application for patients with peripheral arterial disease, and the other an application for collaborative energy conservation to meet targets set out in a city's Sustainable Energy Action Plan.

Sustaining large open source development efforts requires recruiting new participants; however, a lack of architectural documentation might inhibit new participants since large amounts of project knowledge are unavailable to newcomers. We present the results of a multitrait, multimethod analysis of the effects of introducing architectural documentation into a substantial open source project-the Hadoop Distributed File System (HDFS). HDFS had only minimal architectural documentation, and we wanted to discover whether the putative benefits of architectural documentation could be observed over time. To do this, we created and publicized an architecture document and then monitored its usage and effects on the project. The results were somewhat ambiguous: by some measures the architecture documentation appeared to effect the project but not by others. Perhaps of equal importance is our discovery that the project maintained, in its Web-accessible JIRA archive of software issues and fixes, enough architectural discussion to support architectural thinking and reasoning. This “emergent” architecture documentation served an important purpose in recording core project members' architectural concerns and resolutions. However, this emergent architecture documentation did not serve all project members equally well; it appears that those on the periphery of the project-newcomers and adopters-still require explicit architecture documentation, as we will show.

We present Mycocloud, a fully self-organized approach to service placement. Mycocloud supports service elasticity within a network of hosts with heterogeneous computational capacity. Mycocloud proposes a completely decentralized algorithm that continuously calculates the dynamic placement of different services on the host nodes, in response to the varying demand for each service, the churn and dynamism of the node set contributing resources to the system, and the changes in the overlay topology. Our simulation results show how Mycocloud provides good performance in terms of convergence rate, response time, system load and network traffic overhead.

When software developers fail to coordinate, build failures, duplication of work, schedule slips and software defects can result. However, developers are often unaware of when they need to coordinate, and existing methods and tools that help make developers aware of their coordination needs do not provide timely or efficient recommendations. We describe our techniques to identify timely and efficient coordination recommendations, which we developed and evaluated in a study of coordination needs in the Mylyn software project. We describe how data obtained from tools that capture developer actions within their Integrated Development Environment (IDE) as they occur can be used to timely identify coordination needs; we also describe how properties of tasks coupled with machine learning can focus coordination recommendations to those that are more critical to the developers to reduce information overload and provide more efficient recommendations. We motivate our techniques through developer interviews and report on our quantitative analysis of coordination needs in the Mylyn project. Our results suggest that by leveraging IDE logging facilities, properties of tasks and machine learning techniques awareness tools could make developers aware of critical coordination needs in a timely way. We conclude by discussing implications for software engineering research and tool design.

The goal of this one-day workshop is to bring together researchers interested in techniques and tools that leverage context information that accumulates around development activities. Developers continuously make use of context to make decisions, coordinate their work, understand the purpose behind their tasks, and understand how their tasks fit with the rest of the project. However, there is little research on defining what context is, how we can model it, and how we can use those models to better support software development at large. This workshop brings together scholars interested in identifying, gathering and modelling context information in software development, as well as discussing its applications.

Large collaborative software engineering projects are interesting examples for evolving complex systems. The complexity of these systems unfolds both in evolving software structures, as well as in the social dynamics and organization of development teams. Due to the adoption of Open Source practices and the increasing use of online support infrastructures, large-scale data sets covering both the social and technical dimension of collaborative software engineering processes are increasingly becoming available. In the analysis of these data, a growing number of studies employ a network perspective, using methods and abstractions from network science to generate insights about software engineering processes. Featuring a collection of inspiring works in this area, with this topical issue, we intend to give an overview of state-of-the-art research. We hope that this collection of articles will stimulate downstream applications of network-based data mining techniques in empirical software engineering.

A collective adaptive system is composed of a set of heterogeneous, autonomous and self-adaptive entities that come into a collaboration with one another in order to improve the effectiveness with which they can accomplish their individual goals. In this paper, we offer a characterization of ensembles, as the main concept around which systems that exhibit collective adaptability can be built. Our conceptualization of ensembles enables to define a collective adaptive system as an emergent aggregation of autonomous and self-adaptive process-based elements. To elucidate our approach to ensembles and collective adaptation, we draw an example from a scenario in the urban mobility domain, we describe an architecture that enables that approach, and we show how our approach can address the problems posed by the motivating scenario.

Several methods exist to detect the coordination needs within software teams. Evidence exists that developers’ awareness about coordination needs improves work performance. Distinguishing with certainty between critical and trivial coordination needs and identifying and prioritizing which specific tasks a pair of developers should coordinate about remains an open problem. We investigate what work dependencies should be considered when establishing coordination needs within a development team. We use our conceptualization of work dependencies named Proximity and leverage machine learning techniques to analyze what additional task properties are indicative of coordination needs. In a case study of the Mylyn project, we were able to identify from all potential coordination requirements a subset of 17% that are most critical. We define critical coordination requirements as those that can cause the most disruption to task duration when left unmanaged. These results imply that coordination awareness tools could be enhanced to make developers aware of only the coordination needs that can bring about the highest performance benefit.