# InterEvo-TR: Interactive Evolutionary Test Generation With Readability Assessment

arXiv: https://arxiv.org/abs/2401.07072 · HTML: https://mlsanity.com/paper/2401.07072/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 42 references that are in the map.
- First posted on arXiv 13 Jan 2024.

## Builds on (most cited first, 5 of 5)

- [Cognitive Biases in Software Engineering: A Systematic Mapping Study](https://mlsanity.com/paper/1707.03869/) (2017)
- [An Experience Report On Applying Software Testing Academic Results In Industry: We Need Usable Automated Test Generation](https://mlsanity.com/paper/1901.03865/) (2019)
- [Interactive Multi-Objective Evolutionary Optimization of Software Architectures](https://mlsanity.com/paper/2401.04192/) (2024)
- [Tester Interactivity makes a Difference in Search-Based Software Testing: A Controlled Experiment](https://mlsanity.com/paper/1512.04812/) (2015)
- [Transferring Interactive Search-Based Software Testing to Industry](https://mlsanity.com/paper/1804.09232/) (2018)

## Built on by (most cited first, 3 of 3)

- [Toward Automated Validation of Language Model Synthesized Test Cases using Semantic Entropy](https://mlsanity.com/paper/2411.08254/) (2024)
- [DiffuTester: Accelerating Unit Test Generation for Diffusion LLMs via Mining Structural Pattern](https://mlsanity.com/paper/2509.24975/) (2025)
- [Navigating the Labyrinth: Path-Sensitive Unit Test Generation with Large Language Models](https://mlsanity.com/paper/2509.23812/) (2025)

## Abstract (arXiv)

Automated test case generation has proven to be useful to reduce the usually high expenses of software testing. However, several studies have also noted the skepticism of testers regarding the comprehension of generated test suites when compared to manually designed ones. This fact suggests that involving testers in the test generation process could be helpful to increase their acceptance of automatically-produced test suites. In this paper, we propose incorporating interactive readability assessments made by a tester into EvoSuite, a widely-known evolutionary test generation tool. Our approach, InterEvo-TR, interacts with the tester at different moments during the search and shows different test cases covering the same coverage target for their subjective evaluation. The design of such an interactive approach involves a schedule of interaction, a method to diversify the selected targets, a plan to save and handle the readability values, and some mechanisms to customize the level of engagement in the revision, among other aspects. To analyze the potential and practicability of our proposal, we conduct a controlled experiment in which 39 participants, including academics, professional developers, and student collaborators, interact with InterEvo-TR. Our results show that the strategy to select and present intermediate results is effective for the purpose of readability assessment. Furthermore, the participants' actions and responses to a questionnaire allowed us to analyze the aspects influencing test code readability and the benefits and limitations of an interactive approach in the context of test case generation, paving the way for future developments based on interactivity.