Abstract It is relatively easy to generate and acquire much data from software engineering activi... more Abstract It is relatively easy to generate and acquire much data from software engineering activities. The challenge is to obtain meaning from the data that represents something true, rather than spurious. To increase knowledge and insight, more theories should be built and used.
ABSTRACT An important goal of most empirical software engineering experiments is the transfer of ... more ABSTRACT An important goal of most empirical software engineering experiments is the transfer of the research results to industrial applications. To convince industry about the validity and applicability of the results of controlled software engineering experiments, the tasks, subjects and the environments should be as realistic as practically possible. Such experiments are, however, more demanding and expensive than experiments involving students, small tasks and pen-and-paper environments. This chapter describes challenges of increasing the realism of controlled experiments and lessons learned from the experiments that have been conducted at Simula Research Laboratory.
Background: Limiting the amount of Work-In-Progress (WIP) is considered a fundamental principle i... more Background: Limiting the amount of Work-In-Progress (WIP) is considered a fundamental principle in Kanban software development. However, no published studies from real cases exist that indicate what an optimal WIP limit should be. Aims: The primary aim is to study the effect of WIP on the performance of a Kanban team. The secondary aim is to illustrate methodological challenges when attempting to identify an optimal or appropriate WIP limit. Method: A quantitative case study was conducted in a software company that provided information about more than 8,000 work items developed over four years by five teams. Relationships between WIP, lead time and productivity were analyzed. Results: WIP correlates with lead time; that is, lower WIP indicates shorter lead times, which is consistent with claims in the literature. However, WIP also correlates with productivity, which is inconsistent with the claim in the literature that a low WIP (still above a certain threshold) will improve productivity. The collected data set did not include sufficient information to measure aspects of quality. There are several threats to the way productivity was measured. Conclusions: Indicating an optimal WIP limit is difficult in the studied company because a changing WIP gives contrasting results on different team performance variables. Because the effect of WIP has not been quantitatively examined before, this study clearly needs to be replicated in other contexts. In addition, studies that include other team performance variables, such as various aspects of quality, are requested. The methodological challenges illustrated in this paper need to be addressed.
Abstract It is relatively easy to generate and acquire much data from software engineering activi... more Abstract It is relatively easy to generate and acquire much data from software engineering activities. The challenge is to obtain meaning from the data that represents something true, rather than spurious. To increase knowledge and insight, more theories should be built and used.
ABSTRACT An important goal of most empirical software engineering experiments is the transfer of ... more ABSTRACT An important goal of most empirical software engineering experiments is the transfer of the research results to industrial applications. To convince industry about the validity and applicability of the results of controlled software engineering experiments, the tasks, subjects and the environments should be as realistic as practically possible. Such experiments are, however, more demanding and expensive than experiments involving students, small tasks and pen-and-paper environments. This chapter describes challenges of increasing the realism of controlled experiments and lessons learned from the experiments that have been conducted at Simula Research Laboratory.
Background: Limiting the amount of Work-In-Progress (WIP) is considered a fundamental principle i... more Background: Limiting the amount of Work-In-Progress (WIP) is considered a fundamental principle in Kanban software development. However, no published studies from real cases exist that indicate what an optimal WIP limit should be. Aims: The primary aim is to study the effect of WIP on the performance of a Kanban team. The secondary aim is to illustrate methodological challenges when attempting to identify an optimal or appropriate WIP limit. Method: A quantitative case study was conducted in a software company that provided information about more than 8,000 work items developed over four years by five teams. Relationships between WIP, lead time and productivity were analyzed. Results: WIP correlates with lead time; that is, lower WIP indicates shorter lead times, which is consistent with claims in the literature. However, WIP also correlates with productivity, which is inconsistent with the claim in the literature that a low WIP (still above a certain threshold) will improve productivity. The collected data set did not include sufficient information to measure aspects of quality. There are several threats to the way productivity was measured. Conclusions: Indicating an optimal WIP limit is difficult in the studied company because a changing WIP gives contrasting results on different team performance variables. Because the effect of WIP has not been quantitatively examined before, this study clearly needs to be replicated in other contexts. In addition, studies that include other team performance variables, such as various aspects of quality, are requested. The methodological challenges illustrated in this paper need to be addressed.
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