Software Sustainability: Research on Usability, Maintainability, and Reproducibility

Permanent URI for this collectionhttps://hdl.handle.net/10125/107582

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    Understanding Open-Source NLP Artifact Adoption Through Information Systems Success Factors
    (2024-01-03) Liu, Kaiyue
    Open-Source Software (OSS) movement has significantly shaped the landscape of data science, particularly in the subfield of natural language process (NLP). Despite the popularity and rapid growth of OSS tools in the field of data science, prior IS literature did not examine the adoption of NLP artifacts through the lens of OSS success. This study applies and extends the DeLone and McLean Information Systems Success Model to the context of OSS in the domain of NLP. Our extended model examines the moderating effects of task type on the relationship between system quality, information quality, and adoption. In this study, we gather model cards of NLP artifacts, and their download/endorsement counts from Hugging Face and empirically examine the adoption behavior of OSS NLP artifacts. Our expected findings would suggest that system quality affects adoption more for analysis tasks compared to generation tasks, while information quality affects adoption more for generation tasks compared to analysis tasks.
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    Effects of Coding Norm Violations on Visual Effort, Trustworthiness Perceptions, and Reuse Intentions
    (2024-01-03) Willis, Sasha; Jessup, Sarah; Alarcon, Gene; Lee, Michael
    Efficient evaluation strategies are essential when reviewing computer code for potential reuse. Previous researchers have examined the factors that influence these assessments. However, researchers have yet to empirically demonstrate the direct influence of the specific factors that affect visual/cognitive effort, which can be inferred through eye tracking metrics. Programmers were recruited to complete a Java code review task, providing evaluations for a code file’s trustworthiness and reusability after various errors had been introduced to the file’s source reputation, readability, and organization. Analyses of the eye-tracking data revealed increases in fixation counts and durations for manipulated code. An exploratory analysis of areas containing readability and organization errors revealed misuses of case and misuses of declarations garnered the most attention from participants relative to the rest of the code. Implications of the current study extend to recommendations for writing code that is easily reusable by decreasing the visual effort needed for code review.
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