Didac Gil de la Iglesia

A survey of formal methods in self-adaptive systems

One major challenge in self-adaptive systems is to assure the required quality properties. Formal methods provide the means to rigorously specify and reason about the behaviors of self-adaptive systems, both at design time and runtime. To the best of our knowledge, no systematic study has been performed on the use of formal methods in self-adaptive systems. As a result, there is no clear view on what methods have been used to verify self-adaptive systems, and what support these methods offer to software developers. As such insight is important for researchers and engineers, we performed a systematic literature review covering 12 main software engineering venues and 4 journals, resulting in 75 papers used for data collection. The study shows that the attention for self-adaptive software systems is gradually increasing, but the number of studies that employ formal methods remains low. The main focus of formalization is on modeling and reasoning. Model checking and theorem proving have gained limited attention. The main concerns of interest in formalization of self-adaptation are efficiency/performance and reliability. Important adaptation concerns, such as security and scalability, are hardly considered. To verify the concerns of interest, a set of new properties are defined, such as interference freedom, responsiveness, mismatch, and loss-tolerance. A relevant part of the studies use formal methods at runtime, but the use is limited to modeling and analysis. Formal methods can be applied to other runtime activities of self-adaptation, and there is a need for light-weight tools to support runtime verification.

Enhancing Mobile Learning Activities by the Use of Mobile Virtual Devices -- Some Design and Implementation Issues

The use of multiple mobile devices is increasing in mobile learning, bringing a need for collaboration and resource sharing among participating pupils. This paper presents an approach that addresses information and resource sharing for mobile devices in indoors and outdoors settings. Our solution consists of aggregated mobile devices, forming organizations. These Mobile Virtual Devices (MVDs) provide a new mechanism that facilitates design of mobile learning activities offering a virtual complex device that combines the features of several mobile devices.

MAPE-K Formal Templates to Rigorously Design Behaviors for Self-Adaptive Systems

Designing software systems that have to deal with dynamic operating conditions, such as changing availability of resources and faults that are difficult to predict, is complex. A promising approach to handle such dynamics is self-adaptation that can be realized by a MAPE-K feedback loop (Monitor-Analyze-Plan-Execute plus Knowledge). To provide evidence that the system goals are satisfied, given the changing conditions, the state of the art advocates the use of formal methods. However, little research has been done on consolidating design knowledge of self-adaptive systems. To support designers, this paper contributes with a set of formally specified MAPE-K templates that encode design expertise for a family of self-adaptive systems. The templates comprise: (1) behavior specification templates for modeling the different components of a MAPE-K feedback loop (based on networks of timed automata), and (2) property specification templates that support verification of the correctness of the adaptation behaviors (based on timed computation tree logic). To demonstrate the reusability of the formal templates, we performed four case studies in which final-year Masters students used the templates to design different self-adaptive systems.

Guaranteeing robustness in a mobile learning application using formally verified MAPE loops

Mobile learning applications support traditional indoor lectures with outdoor activities using mobile devices. An example scenario is a team of students that use triangulation techniques to learn properties of geometrical figures. In previous work, we developed an agent-based mobile learning application in which students use GPS-enabled phones to calculate distances between them. From practical experience, we learned that the required level of GPS accuracy is not always guaranteed, which undermines the use of the application. In this paper, we explain how we have extended the existing application with a self-adaptation layer, making the system robust to degrading GPS accuracy. The self-adaptive layer is conceived as a set of interacting MAPE loops (Monitor-Analysis-Plan-Execute), distributed over the phones. To guarantee the robustness requirements, we formally specify the self-adaptive behaviors using timed automata, and the required properties using timed computation tree logic. We use the Uppaal tool to model the self-adaptive system and verify the robustness requirements. Finally, we discuss how the formal design supported the implementation of the self-adaptive layer on top of the existing application.

A Self-Adaptive Multi-Agent System Approach for Collaborative Mobile Learning

Mobile technologies have emerged as facilitators in the learning process, extending traditional classroom activities. However, engineering mobile learning applications for outdoor usage poses severe challenges. The requirements of these applications are challenging, as many different aspects need to be catered, such as resource access and sharing, communication between peers, group management, activity flow, etc. Robustness is particularly important for learning scenarios to guarantee undisturbed and smooth user experiences, pushing the technological aspects in the background. Despite significant research in the field of mobile learning, very few efforts have focused on collaborative mobile learning requirements from a software engineering perspective. This paper focuses on aspects of the software architecture, aiming to address the challenges related to resource sharing in collaborative mobile learning activities. This includes elements such as autonomy for personal interactive learning, richness for large group collaborative learning (indoor and outdoor), as well as robustness of the learning system. Additionally, we present self-adaptation as a solution to mitigate risks of resource unavailability and organization failures that arise from environment and system dynamism. Our evaluation provides indications regarding the system correctness with respect to resource sharing and collaboration concerns, and offers qualitative evidence of self-adaptation benefits for collaborative mobile learning applications.

Tangible and wearable user interfaces for supporting collaboration among emergency workers

Ensuring a constant flow of information is essential for offering quick help in different types of disasters. In the following, we report on a work-in-progress distributed, collaborative and tangible system for supporting crisis management. On one hand, field operators need devices that collect information--personal notes and sensor data--without interrupting their work. On the other hand, a disaster management system must operate in different scenarios and be available to people with different preferences, backgrounds and roles. Our work addresses these issues by introducing a multi-level collaborative system that manages real-time data flow and analysis for various rescue operators.

Designing a Decentralized Distributed Self-Adaptive System in M-Learning Activities

The use of mobile technologies in education has increased the amount of tools that can be used for pedagogical purposes. However, the introduction of these technologies comes with challenges that require from attention. The first of them is concerning with the limitations that these devices have in features when compared with laptop and desktop computers, naming the screen size, performance and memory space among others. A mechanism to address this limitation can be the combination of multiple devices in groups and share the resources within these groups. The second limitation that this paper addresses is with regard to these devices being prone to failures in relation with their availability, due to its battery life, connectivity, etc. This paper presents a decentralized distributed self-adaptive system that attempts to cover both the limitations in features of these devices, by combining the devices in organizations, named MVD, and the weakness in availability by providing a self-adaptation mechanism. Moreover, the paper presents the identified required components for the creation of a system that provides such benefits and illustrates the internal functionality of the system to provide the self-adaptive quality.

Supporting Teachers’ Orchestration of Mobile Learning Activities

In this chapter we explore how an innovative mobile learning activity, designed by the authors can be implemented by mathematics classroom teachers. The focal part of the activity involves spatial orientation tasks that are executed with the support of customized mobile technologies in an outdoor setting. In this chapter, we present a comprehensive account of our research efforts spanning a five-year period and focus on providing didactical and technological support for teachers’ informed orchestration of the technology enabled learning activity.