A Taxonomy of Testable HTML5 Canvas Issues

TL;DR

This paper presents a detailed taxonomy of testable issues in HTML5 Canvas applications, based on analysis of GitHub issues, to guide future testing research and improve debugging tools.

Contribution

It introduces a novel taxonomy of Canvas issues derived from real-world data, categorizing common problems to aid targeted testing and debugging efforts.

Findings

Visual issues are the most common (35%)

Performance issues are relatively rare (5%)

Many visual issues are caused by other web components

Abstract

The HTML5 <canvas> is widely used to display high quality graphics in web applications. However, the combination of web, GUI, and visual techniques that are required to build <canvas> applications, together with the lack of testing and debugging tools, makes developing such applications very challenging. To help direct future research on testing <canvas> applications, in this paper we present a taxonomy of testable <canvas> issues. First, we extracted 2,403 <canvas>-related issue reports from 123 open-source GitHub projects that use the HTML5 <canvas>. Second, we constructed our taxonomy by manually classifying a random sample of 332 issue reports. Our manual classification identified five broad categories of testable <canvas> issues, such as Visual and Performance issues. We found that Visual issues are the most frequent (35%), while Performance issues are relatively infrequent (5%). We also found that many testable <canvas> issues that present themselves visually on the <canvas> are actually caused by other components of the web application. Our taxonomy of testable <canvas> issues can be used to steer future research into <canvas> issues and testing.