Temporal Discounting in Software Engineering: A Replication Study

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Abstract

Background: Many decisions made in Software Engineering practices are intertemporal choices: trade-offs in time between closer options with potential short-term benefit and future options with potential long-term benefit. However, how software professionals make intertemporal decisions is not well understood. Aim: This paper investigates how shifting time frames influence preferences in software projects in relation to purposefully selected background factors. Method: We investigate temporal discounting by replicating a questionnaire-based observational study. The replication uses a changed-population and -experimenter design to increase the internal and external validity of the original results. Results: The results of this study confirm the occurrence of temporal discounting in samples of both professional and student participants from different countries and demonstrate strong variance in discounting between study participants. We found that professional experience influenced discounting. Participants with broader professional experience exhibited less discounting than those with narrower experience. Conclusions: The results provide strong empirical support for the relevance and importance of temporal discounting in SE and the urgency of targeted interdisciplinary research to explore the underlying mechanisms and their theoretical and practical implications. The results suggest that technical debt management could be improved by increasing the breadth of experience available for critical decisions with long-term impact. In addition, the present study provides a methodological basis for replicating temporal discounting studies in software engineering.

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Area under the curve as a measure of discounting.

J. Myerson, L. Green, M Warusawitharana (2001)

We describe a novel approach to the measurement of discounting based on calculating the area under the empirical discounting function. This approach avoids some of the problems associated with measures based on estimates of the parameters of theoretical discounting functions. The area measure may be easily calculated for both individual and group data collected using any of a variety of current delay and probability discounting procedures. The present approach is not intended as a substitute for theoretical discounting models. It is useful, however, to have a simple, univariate measure of discounting that is not tied to any specific theoretical framework.