Since programming languages offer a wide variety of grammers, desired functions can be implemented in a variety of ways. We consider that there is a large amount of source code that has different implementations of the same functions, and that those can be compiled into a dataset useful for various research in software engineering. In this study, we construct a dataset of functionally equivalent Java methods from about 36 million lines of source code. The constructed dataset is available at https://zenodo.org/record/5912689.

Since many enterprise systems contain complex business rules, it is important that developers find logical faults during code review. Techniques for extracting specifications help developers understand business rules implemented in source code. The developers can then find logical faults by reviewing the extracted specification. However, when the implemented business rules are complex, it is a problem that the size of the extracted specification is too large for developers to review. To overcome that problem, in the present study, an approach to reduce the size of the extracted specification that has to be reviewed is proposed. This approach focuses on logical faults that can be inferred without having the correct business specification and identifies the part of the specification including those faults as the specification that has to be reviewed. Three patterns that infer such faults in a business specification are defined, and a technique for detecting those patterns in an extracted specification is proposed. To evaluate the proposed technique, it was applied to seven sets of business specifications extracted from an enterprise information system. The results of the evaluation show that the technique successfully reduces the size of the specification that has to be reviewed (by 83% on average), although the reduced specification contains some misdetections. They also show that the technique makes it easier to understand and review a business specification implemented in source code.