WebEV: A Dataset on the Behavior of Testers for Web Application End to End Testing

Abstract

Automated End-to-End (E2E) web testing is a key component in modern rapid development to validate system functionality. However, there are no resources supporting practitioners on how diverse scenarios are tested manually. This paper presents WebEV, a dataset containing E2E test cases from open-source popular projects. Projects are selected based on - i) Cypress-based automation, ii) popularity on GitHub and iii) executability of test cases. The dataset contains information regarding each test command along with the incurred state change representation. Snapshots of the application are used to retrieve - i) the current URL of the application, ii) the screenshot and HTML text of the entire page, and iii) the screenshot and HTML text of an operated UI element. This process is done both before and after each command execution to capture the perception of testers on each state transition, i.e., extract their thought process during testing. This dataset can assist the research community to model user web interaction, predicting the tester’s perception, and improving the state of automated testing approaches. Moreover, WebEV can be used to mine how automated approaches differ from real-life E2E test scenarios.