Gaze-control and gaze-assistance in software development tools have so far been explored in the setting of code editing, but other developer activities like code review could also benefit from this kind of tool support. In this paper, we present GANDER, a platform for user studies on gaze-assisted code review. As a proof of concept, we extend the platform with an assistant that highlights name relationships in the code under review based on gaze behavior, and we perform a user study with 7 participants. While the participants experience the interaction as overwhelming and lacking explicit actions (seen in other similar user studies), the study demonstrates the platform’s capability for mobility, real-time gaze interaction, data logging, replay and analysis.

Code review is a common practice in software development and numerous studies have described different aspects of the process; its characteristics, the expectations on that process, issues around reviewer allocation, and more. However, one aspect that has not been studied to a large extent is the experience of the developers in the code review process. This is unfortunate given the significant amount of time that developers spend on this activity, where problems that degrade developers’ experience on a daily basis can create work environment issues.

Context: Software development is moving towards a place where data about development is gathered in a systematic fashion in order to improve the practice, for example, in tuning of static code analysis. However, this kind of data gathering has so far primarily happened within organizations, which is unfortunate as it tends to favor larger organizations with more resources for maintenance of developer tools. Objective: Over the years, we have seen a lot of benefits from open source and recently there has been a lot of development in open data. We see this as an opportunity for cross-organisation community building and wonder to what extent the views on using and sharing open source software developer tools carry across to open data-driven tuning of software development tools. Method: An exploratory study with 11 participants divided into 3 focus groups discussing using and sharing of static code analyzers and data about these analyzers. Results: While using and sharing open-source code (analyzers in this case) is perceived in a positive light as part of the practice of modern software development, sharing data is met with skepticism and uncertainty. Developers are concerned about threats to the company brand, exposure of intellectual property, legal liabilities, and to what extent data is context-specific to a certain organisation. Conclusions: Sharing data in software development is different from sharing data about software development. We need to better understand how we can provide solutions for sharing of software development data in a fashion that reduces risk and enables openness.

We ask how users interact with `knowledge' in the context of artificial intelligence systems. Four examples of visual interfaces demonstrate the need for such systems to allow room for negotiation between domain experts, automated statistical models, and the people who are involved in collecting and providing data.

In this position paper we consider the ways in which users can be given control over technology and information, considering the spectrum of design possibilities from 'generative component' solutions, to 'appliance' solutions. We show how security concerns and the processes of user centered design tend to encourage a migration towards the appliance end of the spectrum and then describe problems that arise from this. We then suggest an alternative route towards allowing users more direct control over their information via end user programming, discuss some of the challenges in doing so and how they might be overcome and conclude with a suggestion of a practical first step that system designers might consider.

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Experiences of computation vary widely between people. Users ranging from artists to scientists struggle to create programs to meet their needs. Further, the usability implications of designers 'thinking computationally' about social relations such as 'friendship' are highlighted by problems of privacy in Facebook and similar systems. This variability in the experience of computation is more than just an annoyance. Many believe that increasing access to computation will help progress other fields. If they are correct, then these problematic experiences represent a barrier to such progress. This research seeks to addresses this variability in the experience of computation. Computation for creativity, science and society are discussed.