Award Date

May 2016

Degree Type


Degree Name

Master of Science in Computer Science


Computer Science

First Committee Member

Andreas Stefik

Second Committee Member

Jan B. Pedersen

Third Committee Member

Kazem Tagvha

Fourth Committee Member

Matthew Bernacki

Number of Pages



Lambda functions have become prevalent in mainstream programming languages, as they are increasingly introduced to widely used object oriented programming languages such as Java and C++. Some in the scientific literature argue that this feature increases programmer productivity, ease of reading, and makes parallel programming easier. Others are less convinced, citing concerns that the use of lambdas makes debugging harder. This thesis describes the design, execution and results of an experiment to test the impact of using lambda functions compared to the iterator design pattern for iteration tasks, as a first step

in evaluating these claims. The approach is a randomized controlled trial, which focuses on the percentage of tasks completed, number of compiler errors, the percentage of time to fix such errors, and the amount of time it takes to complete programming tasks correctly. The overall goal is to investigate, if lambda functions have an impact on the ability of developers to complete tasks, or the amount of time taken to complete them. Additionally, it is tested if developers introduce more errors while using lambda functions and if fixing errors takes them more time. Lastly, the impact of experience level on productivity is evaluated by comparing the performance of participants from different levels of experience with one-another. Participants were assigned one of five levels based on their progress in the computer science major. The five levels were freshman, sophomore, junior, senior and professional. The professional level was assigned to individuals out of school with 5 or more years of professional experience.

Results show that the impact of using lambdas, as opposed to iterators, on the number of tasks completed was significant. The impact on time to completion, number of errors introduced during the experiment and times spent fixing errors were also found to be significant. The analysis of the difference between the different levels of experience also shows a significant difference. The percentage of time spent on fixing compilation errors was 56.37% for the lambda group while it was 44.2% for the control group with 3.5% of the variance being explained by the group difference. 45.7% of the variance in the sample was explained by the difference between the level of education. Therefore, this study suggests that earlier findings that student results are comparable with the results of professional developers are to be considered carefully.


controlled experiment; human factors; lambda functions; learning


Computer Sciences