Trust in Software: Attributes of Computer Code and the Human Factors that Influence Utilization Metrics

Capiola, August; Nelson, Alex D.; Walter, Charles; Ryan, Tyler J.; Jessup, Sarah A.; Alarcon, Gene M.; Gamble, Rose F.; Pfahler, Marc D.

doi:10.1007/978-3-030-23522-2_24

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Participants spent more time examining the code (i.e., an indication of systematic processing) if it was from a reputable source, coming to a more accurate assessment. These results have been replicated across several studies [17][18][19]. Similarly, Alarcon and colleagues [20] found changing only the comments within the code-thus leaving the source code intact-influenced trust perceptions and manual time spent on code review that was similar to prior studies.…”

Section: Trust In Codesupporting

confidence: 61%

Would You Fix This Code for Me? Effects of Repair Source and Commenting on Trust in Code Repair

Alarcon

Walter

Gibson

et al. 2020

Systems

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Automation and autonomous systems are quickly becoming a more engrained aspect of modern society. The need for effective, secure computer code in a timely manner has led to the creation of automated code repair techniques to resolve issues quickly. However, the research to date has largely ignored the human factors aspects of automated code repair. The current study explored trust perceptions, reuse intentions, and trust intentions in code repair with human generated patches versus automated code repair patches. In addition, comments in the headers were manipulated to determine the effect of the presence or absence of comments in the header of the code. Participants were 51 programmers with at least 3 years’ experience and knowledge of the C programming language. Results indicated only repair source (human vs. automated code repair) had a significant influence on trust perceptions and trust intentions. Specifically, participants consistently reported higher levels of perceived trustworthiness, intentions to reuse, and trust intentions for human referents compared to automated code repair. No significant effects were found for comments in the headers.

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