Evaluating Pair Programming with Respect to System Complexity and Programmer Expertise
By Erik Arisholm, Hans Gallis, Tore Dybå, Dag I.K. Sjøberg. IEEE Transactions on Software Engineering, 2007
297 citations recorded by the source corpus.
A total of 295 junior, intermediate, and senior professional Java consultants (99 individuals and 98 pairs) from 29 international consultancy companies in Norway, Sweden, and the UK were hired for one day to participate in a controlled experiment on pair programming. The subjects used professional Java tools to perform several change tasks on two alternative Java systems with different degrees of complexity. The results of this experiment do not support the hypotheses that pair programming in general reduces the time required to solve the tasks correctly or increases the proportion of correct solutions. On the other hand, there is a significant 84 percent increase in effort to perform the tasks correctly. However, on the more complex system, the pair programmers had a 48 percent increase in the proportion of correct solutions but no significant differences in the time taken to solve the tasks correctly. For the simpler system, there was a 20 percent decrease in time taken but no significant differences in correctness. However, the moderating effect of system complexity depends on the programmer expertise of the subjects. The observed benefits of pair programming in terms of correctness on the complex system apply mainly to juniors, whereas the reductions in duration to perform the tasks correctly on the simple system apply mainly to intermediates and seniors. It is possible that the benefits of pair programming will exceed the results obtained in this experiment for larger, more complex tasks and if the pair programmers have a chance to work together over a longer period of time
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/cff91bd3b225518b0607fe2f3e8128677120e086
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Information Systems
- Tore Dybå
- Dag I.K. Sjøberg
- Tony Gorschek
- Magne Jørgensen
- Martin Ivarsson
- Alberto Bacchelli
- Magiel Bruntink
- Marco di Biase
Citations in the corpus
- The Future of Empirical Methods in Software Engineering Research (2007, methodology): “Hiring more than 100 consultants for one full day [4] may cost more than $100,000.”
- A method for evaluating rigor and industrial relevance of technology evaluations (2011, background): “The expertise or skill of subjects used in the evaluation is also likely to influence the results (Wohlin et al. 2000; Arisholm and Sjoberg 2004; Arisholm et al. 2007; Sjøberg et al. 2007).”
- A Security Perspective on Code Review: The Case of Chromium (2016, background): “The effectiveness of the more lightweight process has been a topic of research, comparing it to other quality-improving processes such as testing and pair programming [3], [20], [21].”