BuildBot: Robotic Monitoring of Agile Software Development Teams
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we describe BuildBot, a robotic interface developed to assist with the continuous integration process utilized by co-located agile software development teams. BuildBot's physical nature allows us to engage the agile software development team members through vision, hearing and touch. In this way, BuildBot becomes an active part of the development process by bringing together human-robot interaction, human group dynamics and software engineering concepts through a number of interaction modalities. In this paper we describe the design and implementation of the BuildBot prototype, a robotic interface that can sense virtual stimuli, in this case the state of a software build, and react accordingly in a physical way via vision, sound and touch. We present an early evaluation comparing BuildBot to two other tools used by an agile team to monitor the continuous integration process. We also show preliminary results indicating that BuildBot may be more noticeable to the developers and contribute to a fun and lighthearted atmosphere. We argue that by increasing awareness of the state of the software build, BuildBot can assist in the self-supervision of agile software engineering teams and can help the team achieve its goals in a more engaging and sociable manner.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it