Solo vs. Pair Programming: A Data-Driven Comparison
文章讨论了配对编程与单独编程在软件开发中的效果对比实验。通过拉丁方设计和统计分析(如ANOVA和Scheffé检验),研究发现配对编程在持续时间上更优(减少28%),而单独编程在努力方面表现更好(减少30%)。 2025-8-20 16:0:4 Author: hackernoon.com(查看原文) 阅读量:9 收藏

Abstract and 1. Introduction

2. Experiment Definition

3. Experiment Design and Conduct

3.1 Latin Square Designs

3.2 Subjects, Tasks and Objects

3.3 Conduct

3.4 Measures

4. Data Analysis

4.1 Model Assumptions

4.2 Analysis of Variance (ANOVA)

4.3 Treatment Comparisons

4.4 Effect Size and Power Analysis

5. Experiment Limitations and 5.1 Threats to the Conclusion Validity

5.2 Threats to Internal Validity

5.3 Threats to Construct Validity

5.4 Threats to External Validity

6. Discussion and 6.1 Duration

6.2 Effort

7. Conclusions and Further Work, and References

4.3 Treatment Comparisons

Taking this alpha level (a=0.1) into account, we perform a treatment comparison test (also referred as contrast test) for each measure. Table 8 shows the treatment means, standard error and replications for duration measure whereas Table 9 shows the same information for effort.

Table 8: Treatment means, standard error and replications for duration

Table 9: Treatment means, standard error and replications for effort

There are several tests for performing treatment comparisons. These tests help us to analyze pairs of means to assess possible differences between means. Using Scheffé test [21] for treatment comparisons, Table 10 shows the treatment comparison with respect to duration.

Table 10: Comparison with respect to duration

As shown in Table 10, there is a significant difference (at a=0.1) of 36 minutes in favor of pair programming (28% decrease in time). At a confidence interval of 95% this difference ranges between 6 and 66 minutes (4% to 51% decrease in time).

Table 11 shows the treatment comparison with respect to effort. As we see, there is a significant difference (at a=0.1) of 56 minutes in favor of solo programming (30% decrease in effort). At a confidence interval of 95% this difference ranges between 8 and 104 minutes (4% to 55% decrease in effort).

Table 11: Comparison with respect to effort

Authors:

(1) Omar S. Gómez, full time professor of Software Engineering at Mathematics Faculty of the Autonomous University of Yucatan (UADY);

(2) José L. Batún, full time professor of Statistics at Mathematics Faculty of the Autonomous University of Yucatan (UADY);

(3) Raúl A. Aguilar, Faculty of Mathematics, Autonomous University of Yucatan Merida, Yucatan 97119, Mexico.



文章来源: https://hackernoon.com/solo-vs-pair-programming-a-data-driven-comparison?source=rss
如有侵权请联系:admin#unsafe.sh