Exploring the impacts of semi-automated storytelling on programmers' comprehension of software histories

Software developers have difficulty understanding the rationale and intent behind original developers' design decisions. Code histories aim to provide richer contexts for code changes over time, but can introduce a large amount of information to the already cognitively demanding task of code co...

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Bibliographic Details
Published inProceedings (IEEE Symposium on Visual Languages and Human-Centric Computing) pp. 148 - 162
Main Authors Allen, John, Kelleher, Caitlin
Format Conference Proceeding
LanguageEnglish
Published IEEE 02.09.2024
Subjects
Accuracy
code histories
Codes
Generative AI
History
Programming
Software
software versioning
storytelling
Visualization
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Summary:Software developers have difficulty understanding the rationale and intent behind original developers' design decisions. Code histories aim to provide richer contexts for code changes over time, but can introduce a large amount of information to the already cognitively demanding task of code comprehension. Storytelling has shown benefits in communicating complex, time-dependent information, yet programmers are reluctant to write stories for their code changes. We explored the utility of narratives made by generative AI. We conducted a within-subjects study comparing the performance of 16 programmers when recalling code history information from a list-view format versus a comparable AI-generated narrative format. Our study found that when using the story-view, participants were 16% more successful at recalling code history information, and had 30% less error when assessing the correctness of their responses. We did not find any significant differences in programmer's perceived mental effort or their attitudes towards reuse when using narrative code stories.
ISSN:1943-6106
DOI:10.1109/VL/HCC60511.2024.00025