Effort Estimation in Co-located and Globally Distributed Agile Software Development: A Comparative Study

摘要

Context: Agile methods are used both by both co-located and globally distributed teams. Recently separate studies have been conducted to understand how effort estimation is practiced in Agile Software Development (ASD) in co-located and distributed contexts. There is need to compare the findings of these studies. Objectives: The objective of this comparative study is to identify the similarities and differences in how effort estimation is practiced in co-located and globally distributed ASD. Method: We combined the data of the two surveys to conduct this comparative study. First survey was conducted to identify the state of the practice on effort estimation in co-located ASD, while the second one identified the same in globally distributed ASD context. Results: The main findings of this comparative study are: 1) Agile practitioners, both in co-located and distributed contexts, apply techniques that use experts' subjective assessment to estimate effort. 2) Story points are the most frequently used size metrics in both co-located and distributed agile contexts 3) Team's prior experience and skill level are leading cost drivers in both contexts. Distributed agile practitioners cited additional cost drivers related to the geographical distance between distributed teams. 4) In both co-located and distributed agile context, effort is estimated mainly at iteration and release planning levels 5) With regard to the accuracy of effort estimates, underestimation is the dominant for both co-located and distributed agile software development. Conclusions: Similar techniques and size metrics have been used to estimate effort by both co-located and distributed agile teams. The main difference is with regard to the factors that are considered as important cost drivers. Global barriers due to cultural, geographical and temporal differences are important cost and effort drivers for distributed ASD. These additional cost drivers should be considered when estimating effort of a distributed agile project to avoid gross underestimation.