Software release planning with time-dependent value functions and flexible release dates
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 planning is of key importance for incremental software product development. In conjunction with the value and the effort needed to implement features, decisions need to be made as to which features are offered in which releases. The value of features can vary over time depending on market conditions, competition, contractual constraints, and other concerns. Release dates and the specific features placed in releases need to be determined in a way that maximizes the overall value related to the investments made. The main contributions of the paper are (i) the formulation of value-driven release planning where we allow time time-dependent value functions to express the value of features potentially assigned to releases, (ii) time-dependent functions expressing the resource capacities needed for implementing features, (iii) a solution method using genetic algorithms to determine release plans allowing variation of the release dates within a pre-defined interval of feasibility, and (iv) providing a proof-of-concept for the proposed approach by running a case study.
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 | 0.001 |
| 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 | 0.001 |
| 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