Mining for Graph-Based Library Usage Patterns in COBOL Systems

Ruben Opdebeeck; Johan Fabry; Tim Christiaan Molderez; Jonas De Bleser; Coen De Roover

doi:10.1109/SANER50967.2021.00072

Mining for Graph-Based Library Usage Patterns in COBOL Systems

Ruben Opdebeeck, Johan Fabry, Tim Christiaan Molderez, Jonas De Bleser, Coen De Roover

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

Abstract

When migrating legacy systems to more contemporary platforms, it is not always feasible to migrate their external library dependencies as well. A workaround can be to partially reimplement the library dependencies on the new platform, limiting oneself to the features that are used by the migrated system. For contemporary programming languages, several approaches to mining for library usage patterns have been proposed. For legacy programming languages, in contrast, such tools are lacking. This encumbers establishing what parts of a library need to be rewritten during a migration project, especially when considering large-scale systems.
In this industry track paper, we present an approach to mining library usage patterns in COBOL code. We describe a library usage extractor for COBOL, which produces graphs that capture the control and data flow involved in library calls. The extractor supports legacy control flow features, such as GO TO. We use these graphs as input to two state-of-the-art frequent subgraph mining algorithms, and report on the scalability of their use for mining common library usage patterns in two industrial COBOL systems. The mined library usage patterns can help assess and subsequently steer the migration effort.

Original language	English
Title of host publication	Proceedings of the 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering
Publisher	IEEE
Pages	595-599
ISBN (Electronic)	978-1-7281-9630-5
DOIs	https://doi.org/10.1109/SANER50967.2021.00072
Publication status	Published - 2021
Event	28th IEEE International Conference on Software Analysis, Evolution, and Reengineering - Honolulu, United States Duration: 9 Mar 2021 → 12 Mar 2021 Conference number: 2021

Conference

Conference	28th IEEE International Conference on Software Analysis, Evolution, and Reengineering
Abbreviated title	SANER
Country	United States
City	Honolulu
Period	9/03/21 → 12/03/21

Keywords

legacy code
software renovation
library usage pattern mining

Access to Document

10.1109/SANER50967.2021.00072

https://soft.vub.ac.be/Publications/2021/vub-tr-soft-21-01.pdf

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1 Talk or presentation at a conference

Mining for Graph-Based Library Usage Patterns in COBOL Systems
Ruben Opdebeeck (Speaker)
12 Mar 2021
Activity: Talk or presentation › Talk or presentation at a conference

File

Cite this

@inproceedings{8cd85cc212664d56b3c046528edf5b14,

title = "Mining for Graph-Based Library Usage Patterns in COBOL Systems",

abstract = "When migrating legacy systems to more contemporary platforms, it is not always feasible to migrate their external library dependencies as well. A workaround can be to partially reimplement the library dependencies on the new platform, limiting oneself to the features that are used by the migrated system. For contemporary programming languages, several approaches to mining for library usage patterns have been proposed. For legacy programming languages, in contrast, such tools are lacking. This encumbers establishing what parts of a library need to be rewritten during a migration project, especially when considering large-scale systems.In this industry track paper, we present an approach to mining library usage patterns in COBOL code. We describe a library usage extractor for COBOL, which produces graphs that capture the control and data flow involved in library calls. The extractor supports legacy control flow features, such as GO TO. We use these graphs as input to two state-of-the-art frequent subgraph mining algorithms, and report on the scalability of their use for mining common library usage patterns in two industrial COBOL systems. The mined library usage patterns can help assess and subsequently steer the migration effort.",

keywords = "legacy code, software renovation, library usage pattern mining",

author = "Ruben Opdebeeck and Johan Fabry and Molderez, {Tim Christiaan} and {De Bleser}, Jonas and {De Roover}, Coen",

year = "2021",

doi = "10.1109/SANER50967.2021.00072",

language = "English",

pages = "595--599",

booktitle = "Proceedings of the 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering",

publisher = "IEEE",

}

Opdebeeck, R, Fabry, J, Molderez, TC, De Bleser, J & De Roover, C 2021, Mining for Graph-Based Library Usage Patterns in COBOL Systems. in Proceedings of the 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering. IEEE, pp. 595-599, 28th IEEE International Conference on Software Analysis, Evolution, and Reengineering, Honolulu, United States, 9/03/21. https://doi.org/10.1109/SANER50967.2021.00072

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T1 - Mining for Graph-Based Library Usage Patterns in COBOL Systems

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AU - De Bleser, Jonas

AU - De Roover, Coen

PY - 2021

Y1 - 2021

N2 - When migrating legacy systems to more contemporary platforms, it is not always feasible to migrate their external library dependencies as well. A workaround can be to partially reimplement the library dependencies on the new platform, limiting oneself to the features that are used by the migrated system. For contemporary programming languages, several approaches to mining for library usage patterns have been proposed. For legacy programming languages, in contrast, such tools are lacking. This encumbers establishing what parts of a library need to be rewritten during a migration project, especially when considering large-scale systems.In this industry track paper, we present an approach to mining library usage patterns in COBOL code. We describe a library usage extractor for COBOL, which produces graphs that capture the control and data flow involved in library calls. The extractor supports legacy control flow features, such as GO TO. We use these graphs as input to two state-of-the-art frequent subgraph mining algorithms, and report on the scalability of their use for mining common library usage patterns in two industrial COBOL systems. The mined library usage patterns can help assess and subsequently steer the migration effort.

AB - When migrating legacy systems to more contemporary platforms, it is not always feasible to migrate their external library dependencies as well. A workaround can be to partially reimplement the library dependencies on the new platform, limiting oneself to the features that are used by the migrated system. For contemporary programming languages, several approaches to mining for library usage patterns have been proposed. For legacy programming languages, in contrast, such tools are lacking. This encumbers establishing what parts of a library need to be rewritten during a migration project, especially when considering large-scale systems.In this industry track paper, we present an approach to mining library usage patterns in COBOL code. We describe a library usage extractor for COBOL, which produces graphs that capture the control and data flow involved in library calls. The extractor supports legacy control flow features, such as GO TO. We use these graphs as input to two state-of-the-art frequent subgraph mining algorithms, and report on the scalability of their use for mining common library usage patterns in two industrial COBOL systems. The mined library usage patterns can help assess and subsequently steer the migration effort.

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