Gengyi Sun

dblp:376/7813 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution
build systems
0.912025
The Cost of Downgrading Build Systems : A Case Study of Kubernetes · ASE 2025

Methods — techniques the papers use, named apart from their topics

empirical measurement · 1.7case study · 1.7
YearPublicationVenuePosition
2025 The Cost of Downgrading Build Systems : A Case Study of Kubernetes
abstract
Since developers invoke the build system frequently, its performance can impact productivity. Modern artifact-based build tools accelerate builds, yet prior work shows that teams may abandon them for alternatives that are easier to maintain. While prior work shows why downgrades are performed, the implications of downgrades remain largely unexplored.In this paper, we describe a case study of the Kubernetes project, focusing on its downgrade from an artifact-based build tool (Bazel) to a language-specific solution (Go Build). We reproduce and analyze the full and incremental builds of change sets during the downgrade period. On the one hand, we find that Bazel builds are faster than Go Build, completing full builds in 23.06-38.66 % less time and incremental builds in up to 75.19 % less time. On the other hand, Bazel builds impose a larger memory footprint than Go Build of 81.42–351.07 % and 118.71-218.22 % for full and incremental builds, respectively. Bazel builds also impose a greater CPU load at parallelism settings above eight for full builds and above one for incremental builds. We estimate that downgrading from Bazel can increase CI resource costs by up to 76 %. We explore whether our observations generalize by replicating our Kubernetes study on four other projects that also downgraded from Bazel to older build tools. We observe that while build time penalties decrease, Bazel consistently consumes more memory. We conclude that abandoning artifact-based build tools, despite perceived maintainability benefits, tends to incur considerable performance costs for large projects. Our observations may help stakeholders to balance trade-offs in build tool adoption.
Gareema Ranjan, Mahmoud Alfadel, Gengyi Sun, Shane McIntosh
ASE3