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Domain Specific Language for Modular Knitting Pattern Definitions: Purl

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Abstract

Purl is a language to be used for modular definition and verification of knitting patterns. The syntax is similar to the standard knitting pattern notation provided by the Craft Yarn Council. Purl provides constructs not available in the standard notation to allow reuse of segments of patterns. This report describes the basics of knitting and hand-knitting patterns. A knitting pattern language more terse than the standard notation is presented with the implementation of a compiler to this standard.
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... The KnitSpeak compiler interprets a pseudo-natural language often used in hand-knitting patterns -KnitSpeak -into a Knit-Graph data structure. The KnitSpeak compiler is not the frst to handle this task [6,7], however it is the frst language demonstrated over a large number of patterns and to support both machine knitting and hand knitting output. The KnitGraph data structure builds on the structure presented by Narayanan et al. [23], which automatically generates machine knitting instructions to ft arbitrary 3D meshes. ...
Conference Paper
Knitting creates complex, soft fabrics with unique texture properties that can be used to create interactive objects.However, little work addresses the challenges of designing and using knitted textures computationally. We present KnitPick: a pipeline for interpreting hand-knitting texture patterns into KnitGraphs which can be output to machine and hand-knitting instructions. Using KnitPick, we contribute a measured and photographed data set of 472 knitted textures. Based on findings from this data set, we contribute two algorithms for manipulating KnitGraphs. KnitCarving shapes a graph while respecting a texture, and KnitPatching combines graphs with disparate textures while maintaining a consistent shape. KnitPick is the first system to bridge the gap between hand- and machine-knitting when creating complex knitted textures.
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The past ten years have witnessed substantial improvements in programming methodology. This advance, carried out under the banner of “structured programming,” has led to programs that are more reliable and easier to comprehend; yet the results are not entirely satisfactory. My purpose in the present paper is to propose another motto that may be appropriate for the next decade, as we attempt to make further progress in the state of the art. I believe that the time is ripe for significantly better documentation of programs, and that we can best achieve this by considering programs to be works of literature. Hence, my title: “Literate Programming.”
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