Developer-Friendly Test Cases: Detection and Removalof Unnecessary Casts

Hi and welcome to my replication package for the paper: "Developer-Friendly Test Cases: Detection and Removalof Unnecessary Casts" Author: G. J. B. Vegelien, C. Brandt, and A. Zaidman. This package inlcudes 1 file (the paper) and 3 folders : * test-cube * DSpot * Data test-cube is where you can find the deleters that I have tested. See for more information the readme.md in the repository. DSpot is includid because there are some extra functions added to github DSpot for running tests. For more information on this open the readme in test-cube. Data is an overview of the data obtaind by runnning my tests. Here you can also find the java test files on which I have tested the deleters. Abstract Test-cube is a tool that focuses on developer-friendly test amplification. Test amplification is a technique to improve a test suite by generating new tests based on manually written ones. Currently, these generated tests contain much redundant casting. Our study aimed to improve the readability of these generated test cases by reducing superfluous casting. To test this, we developed multiple cast deleters categorized into two types: simple and fine-grained cast deleters. A simple cast deleter removes casts based on limited knowledge but can make errors. A fine-grained cast deleter only removes casts if it knows they are redundant based on much contextual information. We compared these two types in terms of accuracy by gathering statistical data when running them against real-world examples of amplified test cases. We also discussed the types of casting cases for which they performed well or could be improved based on manual code inspections. In this study, when amplifying all the tests of four public repositories, we found 3,085 casts in 281 tests containing casts. Of these, 97.18% were redundant, and our fine-grained deleter detected and deleted 98.87% of these. We found this fine-grained deleter to be the worthwhile option compared to a simple cast deleter. This was not because the simple cast deleter was slightly less accurate at 97.18% rather than 98.80% but because it showed extremely inconsistent accuracy. The second benefit of the fine-grained deleter was that it caused no tests to fail, while the simple cast deleter caused 18.15% of tests to fail. This paper provides excellent insights and techniques to reduce vast amounts of redundant casting in test amplification. We hope it will make test amplification more developer-friendly and increase its overall practicality