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Self-diagnosis is a fundamental capability of self-adaptive systems. In order to recover from faults, systems need to know which part is responsible for the incorrect behavior. In previous work we showed how to apply a design-time diagnosis technique at run time to identify faults at the architectural level of a system. Our contributions address three major shortcomings of our previous work: 1) we...
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,...
Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and specifically in the area of self-adaptive systems (SASs), little progress has been made in the application...
Mobile applications run in environments where the context is continuously changing. Therefore, it is necessary to provide support for the run-time adaptation of these applications. This support is usually achieved by middleware platforms that offer a context-aware dynamic reconfiguration service. However, the main shortcoming of existing approaches is that both the list of possible configurations...
Given the elasticity, dynamicity and on-demand nature of the cloud, cloud-based applications require dynamic models for Quality of Service (QoS), especially when the sensitivity of QoS tends to fluctuate at runtime. These models can be autonomically used by the cloud-based application to correctly self-adapt its QoS provision. We present a novel dynamic and self-adaptive sensitivity-aware QoS modeling...
Self-adaptation mechanisms modify target systems dynamically to address adaptation goals, which may evolve continuously due to changes in system requirements. These changes affect values and thresholds of observed context variables and monitoring logic, or imply the addition and/or deletion of context variables, thus compromising self-adaptivity effectiveness under static monitoring infrastructures...
Today' software systems have to cope with changing environments while at the same time facing high non-functional requirements such as flexibility and dependability. Recently, these non-functional requirements are addressed using self-adaptivity features, that is, the system monitors its environment and adjusts its structure or behavior in reaction to changes. In classical model-driven software engineering...
The great impact that law has on the design of software systems has been widely recognized in past years. However, little attention has been paid to the challenge of coping with variability characterizing the legal domain (e.g., multiple ways to comply with a given law, frequent updates to regulations, different jurisdictions, etc.) on the design of software systems. This position paper advocates...
It is challenging to design, develop, and validate a dynamically adaptive system (DAS) that satisfies requirements, particularly when requirements can change at run time. Testing at design time can help verify and validate that a DAS satisfies its specified requirements and constraints. While offline tests may demonstrate that a DAS is capable of satisfying its requirements before deployment, a DAS...
The growing interest in adaptive software systems has resulted in a number of different proposals for the design of adaptive systems. Some approaches adopt architectural models, whereas others model adaptation options, at the level of requirements. This dichotomy has motivated us to perform a comparative study between two proposals for the design of adaptive systems: the Rainbow Framework (architecture-based)...
In 2002 I helped organize the 1st ACM Workshop on Self-healing Systems (WOSS), a workshop that eventually morphed into this SEAMS Conference. As with SEAMS today, the goal then was to bring researchers together to gain a better understanding of the software engineering challenges and approaches for this emerging area. Now, just over 10 years later, it seems a fitting time to reflect back on the progress...
Elastic controllers autonomically adjust the allocation of resources in cloud computing systems. Usually such controllers assume that control actions will take immediate effect. In clouds, however, actuation times may be long, and the controllers can hardly guarantee acceptable levels of service if they neglect these actuation delays. Therefore, the ability to correctly estimate the time that control...
The 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'13) was held in San Francisco during May 20-21 2013, in conjunction with the 35th International Conference on Software Engineering (ICSE??13). SEAMS is the leading international forum for presenting and discussing novel ideas, innovations, trends and experiences in engineering software with self-managing...
Although architecture-based self-adaptation has been widely used, there is still little understanding about the validity and tradeoffs of incorporating it into real-world software-intensive systems which already feature built-in adaptation mechanisms. In this paper, we report on our experience in integrating Rainbow, a platform for architecture-based self-adaptation, and an industrial middleware employed...
Providing high-quality software in the face of uncertainties, such as dealing with new user needs, changing availability of resources, and faults that are difficult to predict, raises fundamental challenges to software engineers. These challenges have motivated the need for self-adaptive systems. One of the primary claimed benefits of self-adaptation is that a design with external feedback loops provide...
Recent trends in science have made computational capabilities an essential part of scientific discovery. This is often referred to as enhanced scientific discovery, or eScience. eScience has been an integral part of high energy physics for several decades due to the complexity and volume of data produced by experiments. In the 1990s, eScience become central to biology with the sequencing of the human...
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