Sonifying Git History

Version control is a technique that software developers use in industry to manage their source code artifacts. One benefit of using version control is that it produces a history of every change made to a codebase, which developers frequently analyze in order to aid the software development process. However, version control history contains highly multidimensional and temporal data. State of the art techniques can show several of these dimensions, but they cannot show a large number of dimensions simultaneously without becoming difficult to understand. An alternative technique to understand temporal data with high dimensionality is sonification. Sonification maps information to sound. In this thesis we propose the use of earcons and parameter mapping sonification to show version control history. Using sonification, we can show more dimensions of version history simultaneously than other state of the art techniques. Our first technique, GitSonifier, uses only sonification to portray version history and historical conflict data. A user study shows that developers can easily understand the sonification, but we also find limitations where visualization may be preferred. Our second technique, GitVS, uses a combination of both visualization and sonification to overcome these limitations. Advisors: Myra B. Cohen and Anita Sarm

Sonifying Git History

Version control is a technique that software developers use in industry to manage their source code artifacts. One benefit of using version control is that it produces a history of every change made to a codebase, which developers frequently analyze in order to aid the software development process. However, version control history contains highly multidimensional and temporal data. State of the art techniques can show several of these dimensions, but they cannot show a large number of dimensions simultaneously without becoming difficult to understand. An alternative technique to understand temporal data with high dimensionality is sonification. Sonification maps information to sound. In this thesis we propose the use of earcons and parameter mapping sonification to show version control history. Using sonification, we can show more dimensions of version history simultaneously than other state of the art techniques. Our first technique, GitSonifier, uses only sonification to portray version history and historical conflict data. A user study shows that developers can easily understand the sonification, but we also find limitations where visualization may be preferred. Our second technique, GitVS, uses a combination of both visualization and sonification to overcome these limitations. Advisors: Myra B. Cohen and Anita Sarm

Non-visual overviews of complex data sets

This paper describes the design and preliminary testing of an interface to obtain overview information from complex numerical data tables non-visually, which is something that cannot be done with currently available accessibility tools for the blind and visually impaired users. A sonification technique that hides detail in the data and highlights its main features without doing any computations to the data, is combined with a graphics tablet for focus+context interactive navigation, in an interface called TableVis. Results from its evaluation suggest that this technique can deliver better scores than speech in time to answer overview questions, correctness of the answers and subjective workload

Timbral Data Sonification from Parallel Attribute Graphs

Parallel coordinate plotting is an established data visualization technique that provides means for graphing and exploring multidimensional relational datasets on a two-dimensional display. Each vertical axis represents the range of values for one attribute, and each data tuple appears as a connected path traveling left-to-right across the plot, connecting attribute values for that tuple on the vertical axes. Parallel coordinate plots look like timedomain audio signal waveforms, and they can be translated into audio signals through straightforward mapping algorithms. This study looks at three data sonification algorithms, sonification being the mapping of data into sounds for perceptual exploration, similar to uses of data visualization. Sound-response survey results and subsequent analyses reveal that the most direct method for mapping parallel coordinates of data tuples to audio waveforms is the most accurate for generating sounds that listeners can use to classify data. Future work has begun on improving the accuracy of this audio waveform-based, timbral approach to classifying data

Google Maps to collect spatial responses in a survey environment

This paper examines the use of Google Maps-based tools to collect spatial responses from participants during academic research surveys conducted via the Internet. Using two recent examples from the University of East Anglia it discusses the online survey context and how Google Maps was used, issues surrounding the technical implementation of these tools, processing and use of the collected data, and concludes with considerations for future research that might employ similar methods