Matthew Sottile

Matthew Sottile

This paper presents a novel method for identifying indentations on the boundary of solid 2D shape. It uses the signed curvature at a set of points along the boundary to identify indentations and provides one parameter for tuning the selection mechanism for discriminating indentations from other boundary irregularities. An efficient implementation is described based on the Fourier transform for calculating curvature from a sequence of points obtained from the boundary of a binary blob.

Jason Dagit, Matthew Sottile

Traditional algorithms for detecting differences in source code focus on differences between lines. As such, little can be learned about abstract changes that occur over time within a project. Structural differencing on the program's abstract syntax tree reveals changes at the syntactic level within code, which allows us to further process the differences to understand their meaning. We propose that grouping of changes by some metric of similarity, followed by pattern extraction via antiunification will allow us to identify patterns of change within a software project from the sequence of changes contained within a Version Control System (VCS). Tree similarity metrics such as a tree edit distance can be used to group changes in order to identify groupings that may represent a single class of change (e.g., adding a parameter to a function call). By applying antiunification within each group we are able to generalize from families of concrete changes to patterns of structural change. Studying patterns of change at the structural level, instead of line-by-line, allows us to gain insight into the evolution of software.