Declaration patterns in dependency management : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Manawatū, New Zealand
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2020
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Massey University
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Abstract
Dependency management has become an important topic within the field of software engineering, where large-scale projects use an increasing number of dependencies to quickly integrate advanced functionality into projects. To take advantage of agile principles - with their fast release cycles - it has become common to delegate the task of dependency management to package managers, whose responsibilities it is to find and download a specified version of the dependency at build time. The principles of Semantic Versioning allow developers to specify version declarations that allow package managers to choose from not just one, but a range of versions, giving rise to the automatic updating of dependencies - a convenient but potentially risky option due to backwards incompatibility issues in some updates. In this thesis, we examine the types of declarations used and their effects on software quality. We find a large variation in practices between software ecosystems, with some opting for conservative, fixed declaration styles, others that prefer Semantic Versioning style ranges, and a few that use higher risk open range styles. We then delve into the consequences of these declaration choices by considering how they affect technical lag, a software quality indicator, finding that declaration styles can have a significant effect on lag. In order to avoid technical lag, in all but the most extreme cases (using open ranges), it is necessary to update declarations periodically. In the case of fixed declarations, updates must be made with every change to the dependency - an ongoing challenge and time outlay for developers. We considered this case to find how regularly developers that use fixed declarations update lagging declarations, finding that developers rarely keep up with changes. The datasets used for these works consisted of large-scale, open-source projects. A developer survey has also been included to contextualise the quantitative results, allowing insight into the intentions of developers who make these declaration choices, and to gain insight on how applicable these findings might be to closed-source projects.