Empirical evaluation of the effects of experience on code quality and programmer productivity: an exploratory study

Abstract

Context There is a widespread belief in both SE and other branches of science that experience helps professionals to improve their performance. However, cases have been reported where experience not only does not have a positive influence but sometimes even degrades the performance of professionals. Aim Determine whether years of experience influence programmer performance. Method We have analysed 10 quasi-experiments executed both in academia with graduate and postgraduate students and in industry with professionals. The experimental task was to apply ITLD on two experimental problems and then measure external code quality and programmer productivity. Results Programming experience gained in industry does not appear to have any effect whatsoever on quality and productivity. Overall programming experience gained in academia does tend to have a positive influence on programmer performance. These two findings may be related to the fact that, as opposed to deliberate practice, routine practice does not appear to lead to improved performance. Experience in the use of productivity tools, such as testing frameworks and IDE also has positive effects. Conclusion Years of experience are a poor predictor of programmer performance. Academic background and specialized knowledge of task-related aspects appear to be rather good predictors.

Comparing techniques for aggregating interrelated replications in software engineering

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“…Measuring programming expertise is still more of an art than a science, with no validated general instruments, and only early evidence of what programming expertise is and scant evidence of which factors correlate with it. However, recent prior work suggests that the best predictors of productivity and program quality are granular measurements related to a task, not years of experience [16], and so we grounded our measures of expertise in the task domain we selected: front-end web development in JavaScript. Therefore, our inclusion criteria for study participation were robust knowledge of JavaScript semantics and robust knowledge of front-end web development APIs.…”

“…The field has studied tools to make developers more productive (e.g., [33]), it has long investigated measures of individual developer productivity (e.g. [60]), it has tried to predict productivity from numerous factors (e.g., [16]), and it has contextualized productivity among the larger set of skills that developers must have to be great engineers (e.g., [43]). At the heart of all of these efforts is the goal of understanding what factors make developers productive.…”

ICSSP 2018—Special issue introduction

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