Many modern programming languages support basic generic programming, sufficient to implement type-safe polymorphic containers. Some languages have moved beyond this basic support to a broader, more powerful interpretation of generic programming, and their extensions have proven valuable in practice. This paper reports on a comprehensive comparison of generics in six programming languages: C , Standard ML, Haskell, Eiffel, Java (with its proposed generics extension), and Generic C#. By implementing a substantial example in each of these languages, we identify eight language features that support this broader view of generic programming. We find these features are necessary to avoid awkward designs, poor maintainability, unnecessary run-time checks, and painfully verbose code. As languages increasingly support generics, it is important that language designers understand the features necessary to provide powerful generics and that their absence causes serious difficulties for programmers.

In this paper, we explore an extension to Haskell type classes that allows a type class declaration to define data types as well as values (or methods). Similarly, an instance declaration gives a witness for such data types, as well as a witness for each method. It turns out that this extension directly supports the idea of a type-indexed type, and is useful in many applications, especially for self-optimising libraries that adapt their data representations and algorithms in a type-directed manner.

Arrangements of planar curves are fundamental structures in computational geometry. Recently, the arrangement package of Cgal, the Computational Geometry Algorithms Library, has been redesigned and re-implemented exploiting several advanced programming techniques. The resulting software package, which constructs and maintains planar arrangements, is easier to use, to extend, and to adapt to a variety of applications. It is more efficient space- and time-wise, and more robust. The implementation is complete in the sense that it handles degenerate input, and it produces exact results. In this paper we describe how various programming techniques were used to accomplish specific tasks within the context of computational geometry in general and Arrangements in particular. These tasks are exemplified by several applications, whose robust implementation is based on the arrangement package. Together with a set of benchmarks they assured the successful application of the adverted programming techniques. 1

This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird’s eye view of today’s scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, 1 this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science.

“Concepts ” are an essential language feature needed to support generic programming in the large. Concepts allow for succinct expression of bounds on type parameters of generic algorithms, enable systematic organization of problem domain abstractions, and make generic algorithms easier to use. In this paper we formalize the design of a type system and semantics for concepts that is suitable for non-type-inferencing languages. Our design shares much in common with the type classes of Haskell, though our primary influence is from best practices in the C ++ community, where concepts are used to document type requirements for templates in generic libraries. The technical development in this paper defines an extension to System F and a type-directed translation from the extension back to System F. The translation is proved sound; the proof is written in the human readable but machine checkable Isar language and has been automatically verified by the Isabelle proof assistant. This document was generated directly from the Isar theory files using Isabelle’s support for literate proofs.

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Globally minimal surfaces by continuous maximal flows In this paper we address the computation of globally minimal curves and surfaces for image segmentation and stereo reconstruction. We present a solution, simulating a continuous maximal flow by a novel system of partial differential equations. Existing methods are either grid-biased (graph-based methods) or sub-optimal (active contours and surfaces). The solution simulates the flow of an ideal fluid with isotropic velocity constraints. Velocity constraints are defined by a metric derived from image data. An auxiliary potential function is introduced to create a system of partial differential equations. It is proven that the algorithm produces a globally maximal continuous flow at convergence, and that the globally minimal surface may be obtained trivially from the auxiliary potential. The bias of minimal surface methods toward small objects is also addressed. An efficient implementation is given for the flow simulation. The globally minimal surface algorithm is applied to segmentation in 2D and 3D as well as to stereo matching. Results in 2D agree with an existing minimal contour algorithm for planar images. Results in 3D segmentation and stereo matching demonstrate that the new algorithm is robust and free from grid bias. I.

First and foremost I thank my parents for all their love and for teaching me to enjoy learning. I especially thank my wife Katie for her support and understanding through this long and sometimes stressful process. I also thank Katie for insisting on good error messages for G! My advisor, Andrew Lumsdaine, deserves many thanks for his support and guidance and for keeping the faith as I undertook this long journey away from scientific computing and into the field of programming languages. I thank my thesis committee: R. Kent Dybvig, Daniel P. Friedman, Steven D. Johnson, and Amr Sabry for their advice and encouragement. A special thanks goes to Ronald Garcia, Christopher Mueller, and Douglas Gregor for carefully editing and catching the many many times when I accidentally skipped over the important stuff. Thanks to Jaakko and Jeremiah for hours of stimulating discussions and arguments concerning separate compilation and concept-based overloading. Thanks to David Abrahams for countless hours spent debating the merits of one design over another while jogging through the hinterlands of Norway. Thanks to Alexander Stepanov and David Musser for getting all this started, and thank you for the encouragement over the years. Thanks to Matthew Austern, his book Generic Programming in the STL was both an inspiration

Generic programming has recently emerged as a paradigm for developing highly reusable software libraries, most notably in C++. We have designed and implemented a constrained generics extension for C++ to support modular type checking of generic algorithms and to address other issues associated with unconstrained generics. To be as broadly applicable as possible, generic algorithms are defined with minimal requirements on their inputs. At the same time, to achieve a high degree of efficiency, generic algorithms may have multiple implementations that exploit features of specific classes of inputs. This process of algorithm specialization relies on non-local type information and conflicts directly with the local nature of modular type checking. In this paper, we review the design and implementation of our extensions for generic programming in C++, describe the issues of algorithm specialization and modular type checking in detail, and discuss the important design tradeoffs in trying to accomplish both. We present the particular design that we chose for our implementation, with the goal of hitting the sweet spot in this interesting design space.

In this paper we propose a WUM recommender system, called SUGGEST 3.0, that dynamically generates links to pages that have not yet been visited by a user and might be of his potential interest. Differently from the recommender systems proposed so far, SUGGEST 3.0 does not make use of any off-line component, and is able to manage Web sites made up of pages dynamically generated. To this purpose SUGGEST 3.0 incrementally builds and maintains historical information by means of an incremental graph partitioning algorithm, requiring no off-line component. The main innovation proposed here is a novel strategy that can be used to manage large Web sites. Experiments, conducted in order to evaluate SUGGEST 3.0 performance, demonstrated that our system is able to anticipate users' requests that will be made farther in the future, introducing a limited overhead on the Web server activity .