Pair Programming Research: Contrasting Results on Effort

Table of Links

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

6.2 Effort

This measure is not present in all of the experiments previously discussed, so we compute it (doubling the time duration of pairs) only in the cases where data is available.

\ According to Nosek data [24] we observe a decrease in effort of 29% in favor of solo programming. Conversely, data of Lui and Chan [19] indicate a decrease of 4% in favor of pairs. Finally, Arisholm et al. [1] Report an increase in effort of 84% (against of pairs).

\ In contrast, the results reported in this paper infer a significant (at a=0.1) 30% decrease in effort (in favor of solos), and an effect size d=0.64. Our results, again, reinforce those calculated in [24].

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:::info 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.

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:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.

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