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A Linguistic Analysis of How People Describe Software Problems
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In: http://www.cs.cmu.edu/~ajko/papers/Ko2006LinguisticsOfBugReports.pdf (2006)
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Lightweight Structured Text Processing
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In: http://www.cs.cmu.edu/~rcm/papers/usenix99/usenix99.ps (1999)
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Authoring Interactive Behaviors for Multimedia
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In: http://www.cs.cmu.edu/~NatProg/necjapan.ps (1998)
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Authoring Interactive Behaviors for Multimedia
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In: http://web.cs.cmu.edu/afs/cs.cmu.edu/user/bam/www/papers/necjapandoc.pdf (1998)
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| 6 |
Visual Programming in a Visual Domain: A Case Study of Cognitive Dimensions
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In: http://www.cs.cmu.edu/afs/cs.cmu.edu/project/garnet/www/pbd-group/papers/hci94.ps (1994)
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| 7 |
Visual Programming in a Visual Domain: A Case Study of Cognitive Dimensions
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In: http://www.cs.dal.ca/~pcox/CSCI6304/papers/modugno.pdf (1994)
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Analyzing the Input Stream for Character- Level Errors in Unconstrained Text Entry Evaluations
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In: http://faculty.washington.edu/wobbrock/pubs/tochi-06.pdf
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| 9 |
Abstract Lightweight Structured Text Processing
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In: http://www.cs.cmu.edu/~rcm/papers/usenix99/usenix99.pdf
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Abstract:
Text is a popular storage and distribution format for information, partly due to generic text-processing tools like Unix grep and sort. Unfortunately, existing generic tools make assumptions about text format (e.g., each line is a record) that limit their applicability. Custom-built tools are one alternative, but they require substantial time investment and programming expertise. We describe a new approach, lightweight structured text processing, which overcomes these difficulties by enabling users to define text structure interactively and manipulate the structure with generic tools. Our prototype system, LAPIS, is a web browser that can highlight, filter, and sort text regions described by the user. LAPIS has several advantages over other systems: (1) the ability to define custom structure with a simple, intuitive pattern language; (2) interactive specification, showing pattern matches in context and letting users choose the most convenient combination of manual selection and pattern matching; and (3) external parsers for standard text formats. The pattern language in LAPIS, text constraints, describes text structure in high-level terms, with region relationships like before, after, in, andcontains. We describe an implementation of text constraints using a novel, compact representation of region sets as collections of rectangles, or region intervals. We also illustrate some examples of applying LAPIS to web pages, text files, and source code.
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.71.3601
http://www.cs.cmu.edu/~rcm/papers/usenix99/usenix99.pdf
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