Analysis of Modern Release Engineering Topics : – A Large-Scale Study using StackOverflow –
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
Release engineers are continuously required to de-liver high-quality software products to the end-user. As a result, modern software companies are proposing new changes in their delivery process that adapt to new technologies such as continuous deployment and Infrastructure-as-Code. However, developers and release engineers still find these practices challenging, and resort to question and answer websites such as StackOverflow to find answers. This paper presents the results of our empirical study on release engineering questions in StackOverflow, to understand the modern release engineering topics of interest and their difficulty. Using topic modeling techniques, we find that (i) developers discuss on a broader range of 38 release engineering topics covering all the six phases of modern release engineering, (ii) the topics Merge Conflict, Branching & Remote Upstream are more popular, while topics Code review, Web deployment, MobileApp Debugging & Deployment, Continuous Deployment are less popular yet more complicated, (iii)-Particularly, the release engineering topic "security" is both popular and difficult according to data collected from StackOverflow.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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