| Pattern matching is heavily used for searching, filtering, and transforming text, but existing pattern languages offer few opportunities for reuse. Lightweight structure is a new approach that solves the reuse problem. Lightweight structure has three parts: a model of text structure as contiguous segments of text, or regions; an extensible library of structure that can be implemented by any kind of pattern or parser; and a region programming, enabling construction of a reusable library.; Lightweight structure has been implemented in LAPIS, a web browser/text editor that demonstrates several novel techniques: (1) Text constraints based on the region algebra. Text constraint patterns are simple and high-level, and user studies have shown that users can generate and comprehend them. (2) Simultaneous editing uses multiple selections for repetitive text editing. Multiple selections are inferred from examples given by the user, drawing on the lightweight structure library to make fast, accurate, domain-specific inferences from very few examples. In user studies, simultaneous editing required only 1.26 examples per selection, approaching the 1-example ideal. (3) Outlier finding draws the user's attention to inconsistent selections or pattern matches—both possible false positives and possible false negatives. When integrated into simultaneous editing and tested in a user study, outlier finding reduced user errors. (4) Unix tools for structured text extend tools like grep and sort with lightweight structure, and the browser shell integrates a Unix command prompt into a web browser, offering new ways to build pipelines and automate web browsing. Theoretical contributions include a formal definition of the region algebra, data structures and algorithms for efficient implementation, and a characterization of the classes of languages recognized by algebra expressions.; Lightweight structure enables efficient composition and reuse of structure to pattern matching, text processing, web automation, repetitive text editing, inference of patterns from examples, and error detection. |
