University of Copenhagen Faculty of Science

About: University of Copenhagen Faculty of Science is a based out in . It is known for research contribution in the topics: Computer science & Inference. The organization has 1031 authors who have published 1266 publications receiving 25779 citations.

Program Analysis and Specialization for the C Programming Language

Abstract: Software engineers are faced with a dilemma. They want to write general and wellstructured programs that are flexible and easy to maintain. On the other hand, generality has a price: efficiency. A specialized program solving a particular problem is often significantly faster than a general program. However, the development of specialized software is time-consuming, and is likely to exceed the production of today’s programmers. New techniques are required to solve this so-called software crisis. Partial evaluation is a program specialization technique that reconciles the benefits of generality with efficiency. This thesis presents an automatic partial evaluator for the Ansi C programming language. The content of this thesis is analysis and transformation of C programs. We develop several analyses that support the transformation of a program into its generating extension. A generating extension is a program that produces specialized programs when executed on parts of the input. The thesis contains the following main results. • We develop a generating-extension transformation, and describe specialization of the various parts of C, including pointers and structures. • We develop constraint-based inter-procedural pointer and binding-time analysis. Both analyses are specified via non-standard type inference systems, and implemented by constraint solving. • We develop a side-effect and an in-use analysis. These analyses are developed in the classical monotone data-flow analysis framework. Some intriguing similarities with constraint-based analysis are observed. • We investigate separate and incremental program analysis and transformation. Realistic programs are structured into modules, which break down inter-procedural analyses that need global information about functions. • We prove that partial evaluation at most can accomplish linear speedup, and develop an automatic speedup analysis. • We study the stronger transformation technique driving, and initiate the development of generating super-extensions. The developments in this thesis are supported by an implementation. Throughout the chapters we present empirical results.

Climate-smart agriculture for food security

Abstract: Climate-smart agriculture (CSA) is an approach to the development of agricultural systems intended to help support food security under climate change. This Perspective outlines a set of CSA actions needed from public, private and civil society stakeholders: building evidence; increasing local institutional effectiveness; fostering coherence between climate and agricultural policies; and linking climate and agricultural financing.

Internet of Things: A survey on the security of IoT frameworks

Abstract: The Internet of Things (IoT) is heavily affecting our daily lives in many domains, ranging from tiny wearable devices to large industrial systems. Consequently, a wide variety of IoT applications have been developed and deployed using different IoT frameworks. An IoT framework is a set of guiding rules, protocols, and standards which simplify the implementation of IoT applications. The success of these applications mainly depends on the ecosystem characteristics of the IoT framework, with the emphasis on the security mechanisms employed in it, where issues related to security and privacy are pivotal. In this paper, we survey the security of the main IoT frameworks, a total of 8 frameworks are considered. For each framework, we clarify the proposed architecture, the essentials of developing third-party smart apps, the compatible hardware, and the security features. Comparing security architectures shows that the same standards used for securing communications, whereas different methodologies followed for providing other security properties.

Context-Aware Recommender Systems for Learning: A Survey and Future Challenges

Abstract: Recommender systems have been researched extensively by the Technology Enhanced Learning (TEL) community during the last decade. By identifying suitable resources from a potentially overwhelming variety of choices, such systems offer a promising approach to facilitate both learning and teaching tasks. As learning is taking place in extremely diverse and rich environments, the incorporation of contextual information about the user in the recommendation process has attracted major interest. Such contextualization is researched as a paradigm for building intelligent systems that can better predict and anticipate the needs of users, and act more efficiently in response to their behavior. In this paper, we try to assess the degree to which current work in TEL recommender systems has achieved this, as well as outline areas in which further work is needed. First, we present a context framework that identifies relevant context dimensions for TEL applications. Then, we present an analysis of existing TEL recommender systems along these dimensions. Finally, based on our survey results, we outline topics on which further research is needed.

Learning analytics dashboard applications

Abstract: This article introduces learning analytics dashboards that visualize learning traces for learners and teachers. We present a conceptual framework that helps to analyze learning analytics applications for these kinds of users. We then present our own work in this area and compare with 15 related dashboard applications for learning. Most evaluations evaluate only part of our conceptual framework and do not assess whether dashboards contribute to behavior change or new understanding, probably also because such assessment requires longitudinal studies.