Usability Of Application Programming Interfaces Research Articles

SLR: From Saltzer and Schroeder to 2021…47 Years of Research on the Development and Validation of Security API Recommendations

Producing secure software is challenging. The poor usability of security Application Programming Interfaces (APIs) makes this even harder. Many recommendations have been proposed to support developers by improving the usability of cryptography libraries—rooted in wider best practice guidance in software engineering and API design. In this SLR, we systematize knowledge regarding these recommendations. We identify and analyze 65 papers, offering 883 recommendations. Through thematic analysis, we identify seven core ways to improve usability of APIs. Most of the recommendations focus on helping API developers to construct and structure their code and make it more usable and easier for programmers to understand . There is less focus, however, on documentation , writing requirements , code quality assessment , and the impact of organizational software development practices . By tracing and analyzing paper ancestry, we map how this knowledge becomes validated and translated over time. We find that very few API usability recommendations are empirically validated, and that recommendations specific to usable security APIs lag even further behind.

A parallel programming assessment for stream processing applications on multi-core systems

Multi-core systems are any computing device nowadays and stream processing applications are becoming recurrent workloads, demanding parallelism to achieve the desired quality of service. As soon as data, tasks, or requests arrive, they must be computed, analyzed, or processed. Since building such applications is not a trivial task, the software industry must adopt parallel APIs (Application Programming Interfaces) that simplify the exploitation of parallelism in hardware for accelerating time-to-market. In the last years, research efforts in academia and industry provided a set of parallel APIs, increasing productivity to software developers. However, a few studies are seeking to prove the usability of these interfaces. In this work, we aim to present a parallel programming assessment regarding the usability of parallel API for expressing parallelism on the stream processing application domain and multi-core systems. To this end, we conducted an empirical study with beginners in parallel application development. The study covered three parallel APIs, reporting several quantitative and qualitative indicators involving developers. Our contribution also comprises a parallel programming assessment methodology, which can be replicated in future assessments. This study revealed important insights such as recurrent compile-time and programming logic errors performed by beginners in parallel programming, as well as the programming effort, challenges, and learning curve. Moreover, we collected the participants’ opinions about their experience in this study to understand deeply the results achieved.

On the comprehension of application programming interface usability in game engines

AbstractExtensive development of games for various purposes including education and entertainment has resulted in increased development of game engines. Game engines are being used on a large scale as they support and simplify game development to a greater extent. Game developers using game engines are often compelled to use various application programming interfaces (APIs) of game engines in the process of game development. Thus, both quality and ease of development of games are greatly influenced by APIs defined in game engines. Hence, understanding API usability in game engines could greatly help in choosing better game engines among the ones that are available for game development and also could help developers in designing better game engines. In this article, we thus aim to evaluate API usability of 95 publicly available game engine repositories on GitHub, written primarily in C++ programming language. We test API usability of these game engines against the eight structural API usability metrics—AMNOI, AMNCI, AMGI, APXI, APLCI, AESI, ATSI, and ADI. We see this research as a first step toward the direction of improving usability of APIs in game engines. We present the results of the study, which indicate that about 25% of the game engines considered have minimal API usability, with respect to the considered metrics. It was observed that none of the considered repositories have ideal (all metric scores equal to 1) API usability, indicating the need for developers to consider API usability metrics while designing game engines.

Using cognitive dimensions to evaluate the usability of security APIs: An empirical investigation

Abstract Context Usability issues of security Application Programming Interfaces (APIs) are a main factor for mistakes programmers make that could result in introducing security vulnerabilities into applications they develop. This has become a common problem as there is no methodology to evaluate the usability of security APIs. A usability evaluation methodology for security APIs would allow API developers to identify usability issues of security APIs and fix them. A Cognitive Dimensions Framework (CDF) based usability evaluation methodology has been proposed in previous research to empirically evaluate the usability of security APIs. Objective In this research, we evaluated the proposed CDF based methodology through four security APIs (Google Authentication API, Bouncy Castle light weight Crypto API, Java Secure Socket Extension API, OWASP Enterprise Security API). Method We conducted four experiments where in each experiment we recruited programmers and they completed a programming task using one of the four security APIs. Participants’ feedback on each cognitive dimension of the particular API was collected using the cognitive dimensions questionnaire. Usability issues of each API was identified based on this feedback. Results Results of the four experiments revealed that over 83% of the usability issues in a security API could be identified by this methodology with a considerably good validity and reliability. Conclusion The proposed CDF based usability evaluation methodology provides a good platform to conduct usability evaluation for security APIs.