Exploring the Impact of Integrating UI Testing in CI/CD Workflows on GitHub

• URL: http://arxiv.org/abs/2504.19335v1
• Date: Sun, 27 Apr 2025 19:13:14 GMT
• Title: Exploring the Impact of Integrating UI Testing in CI/CD Workflows on GitHub
• Authors: Xiaoxiao Gan, Chris Brown,
• Abstract summary: We aim to investigate the current usage of popular UI testing frameworks-Selenium, Playwright and Cypress-in CI/CD pipelines among GitHub repositories.<n>Our goal is to understand how UI testing tools are used in CI/CD processes and assess their potential impacts on open-source development activity.
• Score: 2.3480418671346164
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Background: User interface (UI) testing, which is used to verify the behavior of interactive elements in applications, plays an important role in software development and quality assurance. However, little is known about the adoption of UI testing frameworks in continuous integration and continuous delivery (CI/CD) workflows and their impact on open-source software development processes. Objective: We aim to investigate the current usage of popular UI testing frameworks-Selenium, Playwright and Cypress-in CI/CD pipelines among GitHub repositories. Our goal is to understand how UI testing tools are used in CI/CD processes and assess their potential impacts on open-source development activity and CI/CD workflows. Method: We propose an empirical study to examine GitHub repositories that incorporate UI testing in CI/CD workflows. Our exploratory evaluation will collect repositories that implement UI testing frameworks in configuration files for GitHub Actions workflows to inspect UI testing-related and non-UI testing-related workflows. Moreover, we further plan to collect metrics related to repository development activity and GitHub Actions workflows to conduct comparative and time series analyses exploring whether UI testing integration and usage within CI/CD processes has an impact on open-source development.

Related papers

• Commit0: Library Generation from Scratch [77.38414688148006]
  Commit0 is a benchmark that challenges AI agents to write libraries from scratch.<n>Agents are provided with a specification document outlining the library's API as well as a suite of interactive unit tests.<n> Commit0 also offers an interactive environment where models receive static analysis and execution feedback on the code they generate.
  arXiv  Detail & Related papers  (2024-12-02T18:11:30Z)
• CI/CD Configuration Practices in Open-Source Android Apps: An Empirical Study [0.1433758865948252]
  We conduct an empirical study on Continuous Integration and Continuous Delivery practices in 2,564 Android apps. We observe a lack of commonality and standards across projects and services, leading to complex YML configurations. Our study emphasizes the necessity for automation and AI-powered tools to improve CI/CD processes for mobile applications.
  arXiv  Detail & Related papers  (2024-11-09T05:46:43Z)
• Codev-Bench: How Do LLMs Understand Developer-Centric Code Completion? [60.84912551069379]
  We present the Code-Development Benchmark (Codev-Bench), a fine-grained, real-world, repository-level, and developer-centric evaluation framework. Codev-Agent is an agent-based system that automates repository crawling, constructs execution environments, extracts dynamic calling chains from existing unit tests, and generates new test samples to avoid data leakage.
  arXiv  Detail & Related papers  (2024-10-02T09:11:10Z)
• Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows? [73.81908518992161]
  We introduce Spider2-V, the first multimodal agent benchmark focusing on professional data science and engineering. Spider2-V features real-world tasks in authentic computer environments and incorporating 20 enterprise-level professional applications. These tasks evaluate the ability of a multimodal agent to perform data-related tasks by writing code and managing the GUI in enterprise data software systems.
  arXiv  Detail & Related papers  (2024-07-15T17:54:37Z)
• Detecting Continuous Integration Skip : A Reinforcement Learning-based Approach [0.4297070083645049]
  Continuous Integration (CI) practices facilitate the seamless integration of code changes by employing automated building and testing processes. Some frameworks, such as Travis CI and GitHub Actions have significantly contributed to simplifying and enhancing the CI process. Developers continue to encounter difficulties in accurately flagging commits as either suitable for CI execution or as candidates for skipping.
  arXiv  Detail & Related papers  (2024-05-15T18:48:57Z)
• Automated DevOps Pipeline Generation for Code Repositories using Large Language Models [5.011328607647701]
  The research scrutinizes the proficiency of GPT 3.5 and GPT 4 in generating GitHub, while assessing the influence of various prompt elements in constructing the most efficient pipeline. Results indicate substantial advancements in GPT 4. The research introduces a GitHub App built on Probot, empowering users to automate workflow generation within GitHub ecosystem.
  arXiv  Detail & Related papers  (2023-12-20T17:47:52Z)
• PyRCA: A Library for Metric-based Root Cause Analysis [66.72542200701807]
  PyRCA is an open-source machine learning library of Root Cause Analysis (RCA) for Artificial Intelligence for IT Operations (AIOps) It provides a holistic framework to uncover the complicated metric causal dependencies and automatically locate root causes of incidents.
  arXiv  Detail & Related papers  (2023-06-20T09:55:10Z)
• The GitHub Development Workflow Automation Ecosystems [47.818229204130596]
  Large-scale software development has become a highly collaborative endeavour. This chapter explores the ecosystems of development bots and GitHub Actions. It provides an extensive survey of the state-of-the-art in this domain.
  arXiv  Detail & Related papers  (2023-05-08T15:24:23Z)
• pymdp: A Python library for active inference in discrete state spaces [52.85819390191516]
  pymdp is an open-source package for simulating active inference in Python. We provide the first open-source package for simulating active inference with POMDPs.
  arXiv  Detail & Related papers  (2022-01-11T12:18:44Z)
• Nirikshak: A Clustering Based Autonomous API Testing Framework [0.0]
  Nirikshak is a self-reliant testing framework for REST API testing. It achieves level 2 of autonomy in executing REST API testing procedures. Nirikshak is publicly available as an open-source software for the community at https://github.com/yashmahalwal/nirikshak.
  arXiv  Detail & Related papers  (2021-12-15T18:05:27Z)
• Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs [0.2538209532048866]
  This article provides the motivation and overview of the Collective Knowledge framework (CK or cKnowledge) The CK concept is to decompose research projects into reusable components that encapsulate research artifacts. The long-term goal is to accelerate innovation by connecting researchers and practitioners to share and reuse all their knowledge.
  arXiv  Detail & Related papers  (2020-11-02T17:42:59Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.