A Taxonomy of Testable HTML5 Canvas Issues
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911799442407424 |
|---|---|
| author | Macklon, Finlay Viggiato, Markos Romanova, Natalia Buzon, Chris Paas, Dale Bezemer, Cor-Paul |
| author_facet | Macklon, Finlay Viggiato, Markos Romanova, Natalia Buzon, Chris Paas, Dale Bezemer, Cor-Paul |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2201_07351 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | A Taxonomy of Testable HTML5 Canvas Issues Macklon, Finlay Viggiato, Markos Romanova, Natalia Buzon, Chris Paas, Dale Bezemer, Cor-Paul Software Engineering 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. |
| title | A Taxonomy of Testable HTML5 Canvas Issues |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2201.07351 |