Recent experiments demonstrated the effectiveness of pair programming in terms of quality and productivity. Growing interest towards global software development is fostering the design of suitable methods and tools for distributing software processes, at any level of detail, from entire subprocesses up to a single activity. Consequently, people placed in different locations could also share programming tasks and related practices, such as pair programming. Unfortunately, distribution might seriously compromise the success of pair programming, due to communication and collaboration issues. We have performed an experiment in order to investigate the impact of distribution on pair programming when performing maintenance tasks. An interesting conjecture stems from the experiment: under certain conditions, distributed pair's components tend to dismiss from each other, stopping the collaborative work. This can be a very expensive risk factor to keep into account when planning tasks of distributed pair programming.

How distribution affects the success of pair programming

GERARDO CANFORA;CIMITILE A;DI LUCCA G;CORRADO AARON VISAGGIO
2006-01-01

Abstract

Recent experiments demonstrated the effectiveness of pair programming in terms of quality and productivity. Growing interest towards global software development is fostering the design of suitable methods and tools for distributing software processes, at any level of detail, from entire subprocesses up to a single activity. Consequently, people placed in different locations could also share programming tasks and related practices, such as pair programming. Unfortunately, distribution might seriously compromise the success of pair programming, due to communication and collaboration issues. We have performed an experiment in order to investigate the impact of distribution on pair programming when performing maintenance tasks. An interesting conjecture stems from the experiment: under certain conditions, distributed pair's components tend to dismiss from each other, stopping the collaborative work. This can be a very expensive risk factor to keep into account when planning tasks of distributed pair programming.
2006
Pair programming, distributed software processes, experimental software engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/4135
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