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Software documentation supports a broad set of software maintenance tasks; however, creating and maintaining high-quality, multi-level software documentation can be incredibly time-consuming and therefore many code bases suffer from a lack of adequate documentation. We address this problem through presenting HGEN, a fully automated pipeline that leverages LLMs to transform source code through a series of six stages into a well-organized hierarchy of formatted documents. We evaluate HGEN both quantitatively and qualitatively. First, we use it to generate documentation for three diverse projects, and engage key developers in comparing the quality of the generated documentation against their own previously produced manually-crafted documentation. We then pilot HGEN in nine different industrial projects using diverse datasets provided by each project. We collect feedback from project stakeholders, and analyze it using an inductive approach to identify recurring themes. Results show that HGEN produces artifact hierarchies similar in quality to manually constructed documentation, with much higher coverage of the core concepts than the baseline approach. Stakeholder feedback highlights HGEN's commercial impact potential as a tool for accelerating code comprehension and maintenance tasks.
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ROSplane: Fixed-wing Autopilot for Education and Research
This paper presents a fixed-wing autopilot code base called ROSplane. ROSplane utilizes the ROSflight board, firmware, and driver, which was developed to make autopilot development faster, easier and cheaper. By leveraging a textbook and university course content, the autopilot facilitates education and accelerates research and development. The textbook provides high-level documentation for the code. The code is structured to facilitate learning by providing a framework for student assignments. The addition of ROSplane software and documentation make ROSflight closer to a plugand- play solution while maintaining simplicity and usability for researchers and students. ROSplane has been used in a graduate level flight dynamics class, demonstrated through test flights, and modified for research purposes.
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- Award ID(s):
- 1650547
- PAR ID:
- 10053368
- Date Published:
- Journal Name:
- 2017 International Conference on Unmanned Aircraft Systems (ICUAS)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Software documentation supports a broad set of software maintenance tasks; however, creating and maintaining high-quality, multi-level software documentation can be incredibly time-consuming and therefore many code bases suffer from a lack of adequate documentation. We address this problem through presenting HGEN, a fully automated pipeline that leverages LLMs to transform source code through a series of six stages into a well-organized hierarchy of formatted documents. We evaluate HGEN both quantitatively and qualitatively. First, we use it to generate documentation for three diverse projects, and engage key developers in comparing the quality of the generated documentation against their own previously produced manually-crafted documentation. We then pilot HGEN in nine different industrial projects using diverse datasets provided by each project. We collect feedback from project stakeholders, and analyze it using an inductive approach to identify recurring themes. Results show that HGEN produces artifact hierarchies similar in quality to manually constructed documentation, with much higher coverage of the core concepts than the baseline approach. Stakeholder feedback highlights HGEN's commercial impact potential as a tool for accelerating code comprehension and maintenance tasks. Results and associated supplemental materials can be found at https://zenodo.org/records/11403244.more » « less
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Accepted Manuscript1.0
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- The DOI is not currently available.
