# Doc2OracLL: Investigating the Impact of Documentation on LLM-based Test Oracle Generation

arXiv: https://arxiv.org/abs/2412.09360 · HTML: https://mlsanity.com/paper/2412.09360/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Dec 2024.

## Built on by (most cited first, 10 of 10)

- [Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing](https://mlsanity.com/paper/2506.16136/) (2025)
- [Beyond Postconditions: Can Large Language Models infer Formal Contracts for Automatic Software Verification?](https://mlsanity.com/paper/2510.12702/) (2025)
- [Understanding LLM-Driven Test Oracle Generation](https://mlsanity.com/paper/2601.05542/) (2026)
- [LogicHunter: Testing LLM Agent Frameworks with an Agentic Oracle](https://mlsanity.com/paper/2607.06195/) (2026)
- [Multi-Agent Coordinated Rename Refactoring](https://mlsanity.com/paper/2601.00482/) (2026)
- [FLARE: Agentic Coverage-Guided Fuzzing for LLM-Based Multi-Agent Systems](https://mlsanity.com/paper/2604.05289/) (2026)
- [Multi-Large Language Model Orchestrated Severity Assessment of Clinical Records (MOSAIC)](https://mlsanity.com/paper/2607.05032/) (2026)
- [Code-MUE: Measuring Code LLMs' Uncertainty through Execution-based Semantic Interaction Graphs](https://mlsanity.com/paper/2607.12273/) (2026)
- [Do Coverage and Mutation Scores of LLM-Generated Test Suites Correlate with Their Effectiveness? (Replicability Study)](https://mlsanity.com/paper/2607.22880/) (2026)
- [Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests](https://mlsanity.com/paper/2607.22883/) (2026)

## Abstract (arXiv)

Code documentation is a critical aspect of software development, serving as a bridge between human understanding and machine-readable code. Beyond assisting developers in understanding and maintaining code, documentation also plays a critical role in automating various software engineering tasks, such as test oracle generation (TOG). In Java, Javadoc comments provide structured, natural language documentation embedded directly in the source code, typically detailing functionality, usage, parameters, return values, and exceptions. While prior research has utilized Javadoc comments in test oracle generation (TOG), there has not been a thorough investigation into their impact when combined with other contextual information, nor into identifying the most relevant components for generating correct and strong test oracles, or understanding their role in detecting real bugs. In this study, we dive deep into investigating the impact of Javadoc comments on TOG.