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A Taxonomy of Testable HTML5 Canvas Issues

Finlay Macklon, Markos Viggiato, Natalia Romanova, Chris Buzon, Dale Paas, Cor-Paul Bezemer

TL;DR

This paper extracted 2,403 <monospace><canvas></monospace>-related issue reports from 123 open source GitHub projects that use the HTML5 < monospace>< canvas></ monospace> and constructed a taxonomy of testable <mon aerospace><can canvas></mon Aerospace> issues, finding that visual issues are the most frequent and performance issues are relatively infrequent.

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.

A Taxonomy of Testable HTML5 Canvas Issues

TL;DR

This paper extracted 2,403 <monospace><canvas></monospace>-related issue reports from 123 open source GitHub projects that use the HTML5 < monospace>< canvas></ monospace> and constructed a taxonomy of testable <mon aerospace><can canvas></mon Aerospace> issues, finding that visual issues are the most frequent and performance issues are relatively infrequent.

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.
Paper Structure (38 sections, 1 equation, 4 figures, 6 tables)

This paper contains 38 sections, 1 equation, 4 figures, 6 tables.

Figures (4)

  • Figure 1: <canvas> contents are not represented in the DOM.
  • Figure 2: Study methodology overview.
  • Figure 3: Sample instances of Visual issues reported in the open source projects.
  • Figure 4: Taxonomy of GUI faults lelli2015classifying and taxonomy of web faults marchetto2009empirical mapped to our taxonomy.