Collaborative Software Requirements Engineering Exercises in a Distributed Virtual Team Environment
Bibliographic record
Abstract
Round-the-clock work cycle, low cost of software development, and access to specialized skills have prompted many companies in the USA, Canada, and Europe to outsource some or part of their software development work to off-shore centers in countries such as India. While design, development, and testing phases that are traditionally off-shored require less interaction between clients and the off-shore consultants, phases such as requirements engineering require close co-ordination and interaction. The clients and consultants in such off-shored projects often work in a virtual team environment. In this research, our endeavor is to understand the complex issues in such a virtual project environment during the requirements definition phase of the software development cycle. In particular, we conducted an exploratory research study, involving 24 virtual teams based in Canada and India, working collaboratively on defining business requirements for software projects, over a period of 5 weeks. The study indicates that trust between the teams and well-defined task structure positively influence the performance, satisfaction, and learning level of such distributed virtual teams.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.019 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".