Publication Type

Journal Article

Version

acceptedVersion

Publication Date

10-2018

Abstract

During software development and maintenance, developers spend a considerable amount of time on program comprehension activities. Previous studies show that program comprehension takes up as much as half of a developer's time. However, most of these studies are performed in a controlled setting, or with a small number of participants, and investigate the program comprehension activities only within the IDEs. However, developers' program comprehension activities go well beyond their IDE interactions. In this paper, we extend our ActivitySpace framework to collect and analyze Human-Computer Interaction (HCI) data across many applications (not just the IDEs). We follow Minelli et al.'s approach to assign developers' activities into four categories: navigation, editing, comprehension, and other. We then measure the comprehension time by calculating the time that developers spend on program comprehension, e.g. inspecting console and breakpoints in IDE, or reading and understanding tutorials in web browsers. Using this approach, we can perform a more realistic investigation of program comprehension activities, through a field study of program comprehension in practice across a total of seven real projects, on 78 professional developers, and amounting to 3,148 working hours. Our study leverages interaction data that is collected across many applications by the developers. Our study finds that on average developers spend ∼58% of their time on program comprehension activities, and that they frequently use web browsers and document editors to perform program comprehension activities. We also investigate the impact of programming language, developers' experience, and project phase on the time that is spent on program comprehension, and we find senior developers spend significantly less percentages of time on program comprehension than junior developers. Our study also highlights the importance of several research directions needed to reduce program comprehension time, e.g., building automatic detection and improvement of low quality code and documentation, construction of software-engineering-specific search engines, designing better IDEs that help developers navigate code and browse information more efficiently, etc.

Keywords

Program Comprehension, Field Study, Inference Model

Discipline

Programming Languages and Compilers | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

IEEE Transactions on Software Engineering

Volume

44

Issue

19

First Page

951

Last Page

976

ISSN

0098-5589

Identifier

10.1109/TSE.2017.2734091

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/TSE.2017.2734091

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