Name
Abstract | ||
|---|---|---|
ABSTRACTNavigation of source code typically requires extensive use of a traditional mouse and keyboard which can present significant barriers for developers with physical impairments. We present research exploring how commonly used code navigation approaches (e.g. locating references to user-defined identifiers, jumping to function definitions, conducting a search for specific syntax, etc.) can be optimized for multimodal voice interaction. An exploratory study was initially conducted with five developers who have physical impairments to elicit insights around their experiences in navigating code within existing voice-controlled development environments. Findings from this study informed the design of a code editor integrating different navigation features tailored for multimodal speech input. A user evaluation with 14 developers with physical impairments was conducted with results demonstrating that all participants were able to successfully complete a series of standard navigation tasks. Participants also highlighted that the code navigation techniques were intuitive to use and provided a high-level of usability. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3536221.3556600 | Multimodal Interfaces and Machine Learning for Multimodal Interaction |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bharat Paudyal | 1 | 0 | 0.34 |
| Chris Creed | 2 | 0 | 0.34 |
| Ian Williams | 3 | 0 | 0.34 |
| Maite Frutos-Pascual | 4 | 0 | 0.34 |