Semantic-Aware Replicated Data Types for Improved Conflict Resolution in Near-Synchronous Code Collaboration

This dissertation addresses the limitations of convergence in near-synchronous code collaboration. Current techniques predominantly rely on string-based synchronization, which often results in conflict resolution that fails to address the underlying structural, syntactic, or semantic context of the code. This work proposes a semantic-aware approach that explores different levels of granularity in replicated data types (RDT) to overcome these limitations while enabling near-synchronous visualization of code evolution, enhancing interactive programming environments. The main contributions include: (1) a classification of conflict scenarios and intent-preserving code merging behavior, (2) a novel RDT approach exploring different granularity levels, (3) near-synchronous visualization of code semantics, and (4) extended RDT approaches utilizing nested replicated data types for improved conflict resolution in educational programming contexts.