THE ECONOMICS OF SOFTWARE DEVELOPMENT BY PAIR PROGRAMMERS
Bibliographic record
Abstract
Evidence suggests that pair programmers – two programmers working collaboratively on the same design, algorithm, code, or test – perform substantially better than the two would working alone. Improved quality, teamwork, communication, knowledge management, and morale have been among the reported benefits of pair programming. This paper presents a comparative economic evaluation that strengthens the case for pair programming. The evaluation builds on the quantitative results of an empirical study conducted at the University of Utah. The evaluation is performed by interpreting these findings in the context of two different, idealized models of value realization. In the first model, consistent with the traditional waterfall process of software development, code produced by a development team is deployed in a single increment; its value is not realized until the full project completion. In the second model, consistent with agile software development processes such as Extreme Programming, code is produced and delivered in small increments; thus its value is realized in an equally incremental fashion. Under both models, our analysis demonstrates a distinct economic advantage of pair programmers over solo programmers. Based on these preliminary results, we recommend that organizations engaged in software development consider adopting pair programming as a practice that could improve their bottom line. To be able to perform quantitative analyses, several simplifying assumptions had to be made regarding alternative models of software development, the costs and benefits associated with such models, and how these costs and benefits are recognized. The implications of these assumptions are addressed in the paper.
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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) | 0.000 | 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 | 0.001 | 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 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".