AuthorsA. van Deursen and L. Moonen
TitleAn Empirical Study Into Cobol Type Inferencing
AfilliationSoftware Engineering, Software Engineering
StatusPublished
Publication TypeJournal Article
Year of Publication2001
JournalScience of Computer Programming
Volume40
Number2-3
Pagination189-211
Date PublishedJuly
Abstract

In a typical COBOL program, the data division consists of 50% of the lines of code. Automatic type inference can help to understand the large collections of variable declarations contained therein, showing how variables are related based on their actual usage. The most problematic aspect of type inference is pollution, the phenomenon that types become too large, and contain variables that intuitively should not belong to the same type. The aim of the paper is to provide empirical evidence for the hypothesis that the use of subtyping is an effective way for dealing with pollution. The main results include a tool set to carry out type inference experiments, a suite of metrics characterizing type inference outcomes, and the experimental observation that only one instance of pollution occurs in the case study conducted.

Citation Keydeursen-2001-esi