VLDB 2026 Research / reviewers in the wild / expert
Gerald Mitchell
dblp:393/9704
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0003-1085-9687ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Program verification · 56% Program synthesis and code generation · 28% Software testing · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program synthesis and code generation
code translation |
0.8 | 1 | 2024 | Automated Validation of COBOL to Java Transformation · ASE 2024 |
Program verification
equivalence checking |
0.8 | 1 | 2024 | Automated Validation of COBOL to Java Transformation · ASE 2024 |
Program verification
semantic equivalence |
0.8 | 1 | 2024 | Automated Validation of COBOL to Java Transformation · ASE 2024 |
Program analysis
symbolic execution |
0.2 | 1 | 2024 | Automated Validation of COBOL to Java Transformation · ASE 2024 |
Software testing
test generation |
0.2 | 1 | 2024 | Automated Validation of COBOL to Java Transformation · ASE 2024 |
Methods — techniques the papers use, named apart from their topics
test generation · 0.8symbolic execution · 0.8large language model · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Automated Validation of COBOL to Java TransformationabstractRecent advances in Large Language Model (LLM) based Generative AI techniques have made it feasible to translate enterpriselevel code from legacy languages such as COBOL to modern languages such as Java or Python. While the results of LLM-based automatic transformation are encouraging, the resulting code cannot be trusted to correctly translate the original code. We propose a framework and a tool to help validate the equivalence of COBOL and translated Java. The results can also help repair the code if there are some issues and provide feedback to the AI model to improve. We have developed a symbolic-execution-based test generation to automatically generate unit tests for the source COBOL programs which also mocks the external resource calls. We generate equivalent JUnit test cases with equivalent mocking as COBOL and run them to check semantic equivalence between original and translated programs. Demo Video: https://youtu.be/aqF_agNP-lU Atul Kumar 0002, Diptikalyan Saha, Toshiaki Yasue, Kohichi Ono, Saravanan Krishnan, Sandeep Hans, Fumiko Satoh, Gerald Mitchell, Sachin Kumar 0011 |
ASE | 8 |