Cluster-based Find & Replace
Alisa Marshall & Robert Miller
Abstract
In current text editors, the find & replace command offers
only two options: replace one match at a time prompting for
confirmation, or replace all matches at once without any con-
firmation. Both approaches are prone to errors. This paper
explores a third way: cluster-based find & replace, in which
the matches are clustered by similarity and whole clusters
can be replaced at once. We hypothesized that cluster-based
find & replace would make find & replace tasks both faster
and more accurate, but initial user studies suggest that clustering
may improve speed on some tasks but not accuracy.
Users also prefer using a perfect-selection strategy for find &
replace, rather than an interleaved decision-action strategy.
References:
[1] Robert C. Miller and Alisa A. Marshall. "Cluster-based Find & Replace." Conference on Human Factors in Computing Systems (CHI 2004), April 2004.
[2] Alisa Marshall. "Cluster-Based Find & Replace." MEng thesis, Massachusetts Institute of Technology, June 2003.