Social Life of Code: Modeling Evolution through Code Embedding and Opinion Dynamics
Yulong He, Nikita Verbin, Sergey Kovalchuk

TL;DR
This paper introduces a novel framework combining code embeddings and opinion dynamics to analyze software evolution and developer collaboration patterns in open-source projects.
Contribution
It integrates semantic code embeddings with opinion dynamics theory to quantitatively model and analyze collaborative development processes.
Findings
Reveals implicit collaboration patterns and knowledge-sharing mechanisms.
Demonstrates the framework's ability to identify behavioral trends in GitHub repositories.
Provides insights into developer influence and consensus formation.
Abstract
Software repositories provide a detailed record of software evolution by capturing developer interactions through code-related activities such as pull requests and modifications. To better understand the underlying dynamics of codebase evolution, we introduce a novel approach that integrates semantic code embeddings with opinion dynamics theory, offering a quantitative framework to analyze collaborative development processes. Our approach begins by encoding code snippets into high-dimensional vector representations using state-of-the-art code embedding models, preserving both syntactic and semantic features. These embeddings are then processed using Principal Component Analysis (PCA) for dimensionality reduction, with data normalized to ensure comparability. We model temporal evolution using the Expressed-Private Opinion (EPO) model to derive trust matrices and track opinion…
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