DeepTC-Enhancer: Improving the Readability of Automatically Generated Tests
Abstract
Automated test case generation tools have been successfully proposed to reduce the amount of human and infrastructure resources required to write and run test cases. However, recent studies demonstrate that the readability of generated tests is very limited due to (i) uninformative identifiers and (ii) lack of proper documentation. Prior studies proposed techniques to improve test readability by either generating natural language summaries or meaningful methods names. While these approaches are shown to improve test readability, they are also affected by two limitations: (1) generated summaries are often perceived as too verbose and redundant by developers, and (2) readable tests require both proper method names but also meaningful identifiers (within-method readability).
BibTeX
@inproceedings{Roy-al:ASE20,
author = {Devjeet Roy and
Ziyi Zhang and
Maggie Ma and
Venera Arnaoudova and
Annibale Panichella and
Sebastiano Panichella and
Danielle Gonzalez and
Mehdi Mirakhorli},
title = {{DeepTC-Enhancer:} Improving the Readability of Automatically Generated Tests},
booktitle = {ASE},
pages = {287--298},
publisher = {{IEEE}},
year = {2020},
}