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https://hdl.handle.net/2142/66454
Description
Title
The Human as a Constrained Optimal Text Editor
Author(s)
Hammer, John Maynard
Issue Date
1981
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
Text editing is a sequence of two subtasks: locating a line to change, and changing it. User performance on the latter subtask, termed intraline editing, was modeled by a constrained optimal (minimum keystroke) solution. The primary constraint for modeling a given user was to employ only the commands that the user had been observed to issue.
The method for finding an optimal solution to an intraline editing problem had two phases. First, given a line before and after modification, a string-to-string correction algorithm generated a strategy, which identified the substrings to be preserved, deleted, and inserted. The second phase found a cheapest path in a directed graph. Each graph node represented the editor state--the line and position within the line. Each arc represented an editor command and connected node A to node B if the command transformed the text and position of A into those of B. The arcs leading out from each node were generated according to the strategy. A heuristic, depth-first search of the graph was found superior to a classical, breadth-first search.
The editing of thirty users--ten on each of three editors--was collected by monitoring all terminal input and output. Thus, all of the data was from real life text editing, not from a laboratory experiment. The data was divided into a derivation and a validation data set. The ten different users' problems in the derivation data were solved with the constrained optimal model. Keystrokes in excess of this solution were categorized as feedback requests, inappropriate command selection, or human error. These categories were iteratively refined and then frozen for analysis of the validation data.
The model--a constrained optimal solution plus the descriptive categories--explained 85 to 95% of the keystrokes in both data sets. Significant differences among editors were found in the percentage of keystrokes due to feedback requests and in the ratio of optimal to constrained optimal performance. In addition, several recommendations were developed for improving the human factors of text editors.
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