Duck Futures: A Generative Approach to Transparent Futures

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2015-06-24
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Lin, Eric
Upadhyaya, Ganesha
Mooney, Sean
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Rajan, Hridesh
Professor and Department Chair of Computer Science
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Computer Science

Computer Science—the theory, representation, processing, communication and use of information—is fundamentally transforming every aspect of human endeavor. The Department of Computer Science at Iowa State University advances computational and information sciences through; 1. educational and research programs within and beyond the university; 2. active engagement to help define national and international research, and 3. educational agendas, and sustained commitment to graduating leaders for academia, industry and government.

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The Computer Science Department was officially established in 1969, with Robert Stewart serving as the founding Department Chair. Faculty were composed of joint appointments with Mathematics, Statistics, and Electrical Engineering. In 1969, the building which now houses the Computer Science department, then simply called the Computer Science building, was completed. Later it was named Atanasoff Hall. Throughout the 1980s to present, the department expanded and developed its teaching and research agendas to cover many areas of computing.

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1969-present

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Futures offer a convenient abstraction for encapsulating delayed computation. It is a mechanism to introduce concurrency through a rewrite of the sequential program. However, managing futures is tedious and requires knowledge of concurrency and its concerns. The notion of transparent futures is used to hide the complexity of futures from developers. A number of techniques based on transparency have been proposed to create and manage futures. Previous techniques make use of reflection. In this paper, we propose duck futures that use a generative approach. We show that duck futures are much more efficient compared to previous notions of transparent futures. We also present the first large scale study of the applicability and utility of duck futures in practice using the Boa infrastructure for mining large scale open source repositories. Our study finds that transparent futures, despite their limitations, can be very useful in practice.

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