An empirical study into COBOL type inferencing |
| |
Authors: | Arie van Deursen Leon Moonen |
| |
Affiliation: | CWI, P.O. Box 94079, 1090 GB Amsterdam, Netherlands |
| |
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. |
| |
Keywords: | Software maintenance Static program analysis Variable usage Case study |
本文献已被 ScienceDirect 等数据库收录! |
|