Semantics-based reverse engineering of object-oriented data models
Proceedings of the 28th international conference on Software engineering
Using logical data models for understanding and transforming legacy business applications
IBM Systems Journal - Model-driven software development
Migrating legacy data structures based on variable overlay to Java
Journal of Software Maintenance and Evolution: Research and Practice - Working Conference on Reverse Engineering (WCRE 2008)
Dependent types for program understanding
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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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 conclusion that only one instance of pollution was found in the case study conducted.