Analyzing and Evaluating the Behavior of Git Diff and Merge
July 16, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Niels Glodny
arXiv ID
2507.22071
Category
cs.SE: Software Engineering
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Despite being widely used, the algorithms that enable collaboration with Git are not well understood. The diff and merge algorithms are particularly interesting, as they could be applied in other contexts. In this thesis, I document the main functionalities of Git: how diffs are computed, how they are used to run merges, and how merges enable more complex operations. In the process, I show multiple unexpected behaviors in Git, including the following: The histogram diff algorithm has pathological cases where a single-line change can cause the entire rest of the file to be marked as changed. The default merge strategy (ort) can result in merges requiring exponential time in the number of commits in the history. Merges and rebases are not commutative, and even when merges do not result in a conflict, the result is not specified but depends on the diff algorithm used. And finally, sometimes when two sides of a merge add different lines at the same position, the result is not a conflict, but a merge containing both changes after each other, in arbitrary order.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted