Understanding Expressions of Unwanted Behaviors in Open Bug Reporting

Open bug reporting allows end-users to express a vast array of unwanted software behaviors. However, users ’ expectations often clash with developers’ implementation intents. We created a classification of seven common expectation violations cited by endusers in bug report descriptions and applied it to 1,000 bug reports from the Mozilla project. Our results show that users largely described bugs as violations of their own personal expectations, of specifications, or of the user community’s expectations. We found a correlation between a reporter’s expression of which expectation was being violated and whether or not the bug would eventually be fixed. Specifically, when bugs were expressed as violations of community expectations rather than personal expectations, they had a better chance of being fixed. 1

Comparing Smartphone Speech Recognition and Touchscreen Typing for Composition and Transcription

International audienceRuan et al. found transcribing short phrases with speech recognition nearly 200% faster than typing on a smartphone. We extend this comparison to a novel composition task, using a protocol that enables a controlled comparison with transcription. Results show that both composing and transcribing with speech is faster than typing. But, the magnitude of this difference is lower with composition, and speech has a lower error rate than keyboard during composition, but not during transcription. When transcribing, speech outperformed typing in most NASA-TLX measures, but when composing, there were no significant differences between typing and speech for any measure except physical demand

Automatic Detection of User Abilities through the SmartAbility Framework

This paper presents a proposed smartphone application for the unique SmartAbility Framework that supports interaction with technology for people with reduced physical ability, through focusing on the actions that they can perform independently. The Framework is a culmination of knowledge obtained through previously conducted technology feasibility trials and controlled usability evaluations involving the user community. The Framework is an example of ability-based design that focuses on the abilities of users instead of their disabilities. The paper includes a summary of Versions 1 and 2 of the Framework, including the results of a two-phased validation approach, conducted at the UK Mobility Roadshow and via a focus group of domain experts. A holistic model developed by adapting the House of Quality (HoQ) matrix of the Quality Function Deployment (QFD) approach is also described. A systematic literature review of sensor technologies built into smart devices establishes the capabilities of sensors in the Android and iOS operating systems. The review defines a set of inclusion and exclusion criteria, as well as search terms used to elicit literature from online repositories. The key contribution is the mapping of ability-based sensor technologies onto the Framework, to enable the future implementation of a smartphone application. Through the exploitation of the SmartAbility application, the Framework will increase technology amongst people with reduced physical ability and provide a promotional tool for assistive technology manufacturers

Understanding Usability Practices in Complex Domains

Although usability methods are widely used for evaluating conventional graphical user interfaces and websites, there is a growing concern that current approaches are inadequate for evaluating complex, domain-specific tools. We interviewed 21 experienced usability professionals, including in-house experts, external consultants, and managers working in a variety of complex domains, and uncovered the challenges commonly posed by domain complexity and how practitioners work around them. We found that despite the best efforts by usability professionals to get familiar with complex domains on their own, the lack of formal domain expertise can be a significant hurdle for carrying out effective usability evaluations. Partnerships with domain experts lead to effective results as long as domain experts are willing to be an integral part of the usability team. These findings suggest that for achieving usability in complex domains, some fundamental educational changes may be needed in the training of usability professionals. ACM Classification H.5.2 [Information interfaces and presentation]: User interfaces—evaluation / methodology

The aligned rank transform for nonparametric factorial analyses using only anova procedures

Nonparametric data from multi-factor experiments arise often in human-computer interaction (HCI). Examples may include error counts, Likert responses, and preference tallies. But because multiple factors are involved, common nonparametric tests (e.g., Friedman) are inadequate, as they are unable to examine interaction effects. While some statistical techniques exist to handle such data, these techniques are not widely available and are complex. To address these concerns, we present the Aligned Rank Transform (ART) for nonparametric factorial data analysis in HCI. The ART relies on a preprocessing step that “aligns” data before applying averaged ranks, after which point common ANOVA procedures can be used, making the ART accessible to anyone familiar with the F-test. Unlike most articles on the ART, which only address two factors, we generalize the ART to N factors. We also provide ARTool and ARTweb, desktop and Web-based programs for aligning and ranking data. Our re-examination of some published HCI results exhibits advantages of the ART