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João Pedro Sousa

Researcher at George Mason University

Publications -  48
Citations -  2760

João Pedro Sousa is an academic researcher from George Mason University. The author has contributed to research in topics: Software system & Ubiquitous computing. The author has an hindex of 19, co-authored 48 publications receiving 2657 citations. Previous affiliations of João Pedro Sousa include Carnegie Mellon University.

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Book ChapterDOI

Software Engineering for Self-Adaptive Systems : A Second Research Roadmap

TL;DR: In this paper, the authors present the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems, focusing on four essential topics of selfadaptation: design space for selfadaptive solutions, software engineering processes, from centralized to decentralized control, and practical run-time verification & validation.
Book ChapterDOI

Aura: an Architectural Framework for User Mobility in Ubiquitous Computing Environments

TL;DR: It is argued that traditional approaches to handling resource variability in applications are inadequate, and an alternative architectural framework is described that is better matched to the needs of ubiquitous computing.
Journal ArticleDOI

Task-based adaptation for ubiquitous computing

TL;DR: Focusing on the engineering issues of self-adaptation in the presence of heterogeneous platforms, legacy applications, mobile users, and resource variable environments, a new approach based on the following key ideas is described.
Proceedings ArticleDOI

Dynamic configuration of resource-aware services

TL;DR: This paper shows how to provide a shared infrastructure that automates configuration decisions given a specification of the user's task and validates this approach both analytically and by applying it to a representative scenario.
Journal ArticleDOI

SASSY: A Framework for Self-Architecting Service-Oriented Systems

TL;DR: The SASSY (Self-architecting Software Systems) framework automatically generates candidate software architectures and selects the one that best serves stakeholder-defined, scenario-based quality-of-service (QoS) goals, which lets domain experts concentrate on functional and QoS requirements.