FRINK Linked Data Fragments server

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• W54849093 abstract "We present a highly reusable “inverted” project in which students learn asymptotic and practical behaviour of dictionary data structures—linked-lists, arrays, balanced trees, and hash tables—in an atmosphere of mild competition. Much like David Levine’s Nifty Assignment“Sort Detective”, rather than implementing the dictionaries, students’ programs generate input to our (unlabeled) implementations, and students use timing data to label the implementations. Much like Bryant and O’Halloran’s computer architecture labs, students also compete to “convince” a web-based, automated system that their input generators distinguish the dictionaries based on trend-line behaviour. UBC has used the project in three terms, and we plan to use it at UBC and U Toronto in coming terms. 1. SIGNIFICANCE AND RELEVANCE Dictionary data structures (also known as maps) are commonly used in a wide variety of computing applications as well as being an important topic in algorithms and data structures courses in the ACM CS2008 curriculum (e.g., under AL/FundamentalAlgorithms, PF/DataStructures, and various places for analysis of performance and tradeoffs). Modern languages generally support them either as built-in structures (as in Python) or as part of the core libraries (as in Java). A long-running issue in computing education has been to find ways to help students learn to understand these data structures from above the implementation level [3]. Our project builds on the inverted assignment style of Levine [2] and Bryant and O’Hallaron [1] to provide a learning experience for students where they use these data structures from the outside, yet exercise deep and thorough understanding of the crucial idiosyncracies of each implementation’s function. Using a simple command syntax—one command per line where each command is composed of an ‘I’ for insert, ‘F’ for find, or ‘R’ for remove plus a numeric key—students craft experiments to distinguish the dictionary implementations from each other. To do so student must understand best-, average-, and worst-case behaviours of the structures, the form of inputs that produce those behaviours, the performance curves these varied inputs produce, and various practical ramifications of the structures’ function (e.g., the relatively large delays generated by rehashing vs. resizing of arrays). To excel in the competition, students also make educated guesses augmented by further experiments into the structure of implementations. (For example, to force a hash table to generate a “clean” n-shaped curve for a series of n insertions, students might first reverse engineer the hash table’s initial size and resizing strategy.) Finally, this project forces our Computer Science students to coherently describe an experimental plan and use its results to justify their choices, a lamentably rare occurrence in CS projects!" @default.
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• W54849093 date "2012-01-01" @default.
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• W54849093 title "“Dictionary Wars”: An Inverted, Leaderboard-Driven Project for Learning Dictionary Data Structures" @default.
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