Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable

Fighting Against XSS Attacks. A Usability Evaluation of OWASP ESAPI Output Encoding

Cross Site Scripting (XSS) is one of the most critical vulnerabilities exist in web applications. XSS can be prevented by encoding untrusted data that are loaded into browser content of web applications. Security Application Programming Interfaces (APIs) such as OWASP ESAPI provide output encoding functionalities for programmers to use to protect their applications from XSS attacks. However, XSS still being ranked as one of the most critical vulnerabilities in web applications suggests that programmers are not effectively using those APIs to encode untrusted data. Therefore, we conducted an experimental study with 10 programmers where they attempted to fix XSS vulnerabilities of a web application using the output encoding functionality of OWASP ESAPI. Results revealed 3 types of mistakes that programmers made which resulted in them failing to fix the application by removing XSS vulnerabilities. We also identified 16 usability issues of OWASP ESAPI. We identified that some of these usability issues as the reason for mistakes that programmers made. Based on these results, we provided suggestions on how the usability of output encoding APIs should be improved to give a better experience to programmers

A systematic mapping study of API usability evaluation methods

An Application Programming Interface (API) provides a programmatic interface to a software component that is often offered publicly and may be used by programmers who are not the API’s original designers. APIs play a key role in software reuse. By reusing high quality components and services, developers can increase their productivity and avoid costly defects. The usability of an API is a qualitative characteristic that evaluates how easy it is to use an API. Recent years have seen a considerable increase in research efforts aiming at evaluating the usability of APIs. An API usability evaluation can identify problem areas and provide recommendations for improving the API. In this systematic mapping study, we focus on 47 primary studies to identify the aim and the method of the API usability studies. We investigate which API usability factors are evaluated, at which phases of API development is the usability of API evaluated and what are the current limitations and open issues in API usability evaluation. We believe that the results of this literature review would be useful for both researchers and industry practitioners interested in investigating the usability of API and new API usability evaluation methods

Quality Management of Learning Management Systems: A User Experience Perspective

Learning Management Systems (LMS) have been the main vehicle for delivering and managing e-learning courses in educational, business, governmental and vocational learning settings. Since the mid-nineties there is a plethora of LMS in the market with a vast array of features. The increasing complexity of these platforms makes LMS evaluation a hard and demanding process that requires a lot of knowledge, time, and effort. Nearly 50% of respondents in recent surveys have indicated they seek to change their existing LMS primarily due to user experience issues. Yet the vast majority of the extant literature focuses only on LMS capabilities in relation to administration and management of teaching and learning processes. In this study the authors try to build a conceptual framework and evaluation model of LMS through the lens of User Experience (UX) research and practice, an epistemology that is quite important but currently neglected in the e-learning domain. They conducted an online survey with 446 learning professionals, and from the results, developed a new UX-oriented evaluation model with four dimensions: pragmatic quality, authentic learning, motivation and engagement, and autonomy and relatedness. Their discussion on findings includes some ideas for future research