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> Developed at IBM Research. CLDK is an actively evolving project — issues and contributions are welcome.
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## Cited By
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CLDK ([Krishna et al., 2024](https://arxiv.org/abs/2410.13007)) is used and cited in a growing body of research on program analysis and code LLMs:
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-**RECON: An LLM-Enhanced Backward Constraint Analysis Framework** — Bappah et al. (2026). [arXiv:2606.10264](https://arxiv.org/abs/2606.10264)
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-**Architecting Open, Accountable, and Trustworthy AI-IDEs** — Contreras, Guerra & de Lara (2026). *Automated Software Engineering*. [doi:10.1007/s10515-026-00608-x](https://doi.org/10.1007/s10515-026-00608-x)
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-**Resolving Java Code Repository Issues with iSWE Agent** — Ganhotra et al. (2026). [arXiv:2603.11356](https://arxiv.org/abs/2603.11356)
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-**HookLens: Visual Analytics for Understanding React Hooks Structures** — Hwang et al. (2026). *IEEE PacificVis*. [arXiv:2602.17891](https://arxiv.org/abs/2602.17891)
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-**PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysis** — Cui, Krishna & Jha et al. (2025). [arXiv:2512.22113](https://arxiv.org/abs/2512.22113)
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-**Examining Software Developers' Needs for Privacy Enforcing Techniques: A Survey** — Theophilou & Kapitsaki (2025). *ACM SAC*. [arXiv:2512.14756](https://arxiv.org/abs/2512.14756)
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-**LLM as an Execution Estimator: Recovering Missing Dependency for Practical Time-Travelling Debugging** — Pei, Wang & Zhang et al. (2025). [arXiv:2508.18721](https://arxiv.org/abs/2508.18721)
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-**Agentic Multi-Modal LLMs for Software Comprehension: Structuring Code Summarization with Business Process Awareness** — Tamilselvam & Saxena (2025). *IEEE SSE*. [doi:10.1109/SSE67621.2025.00024](https://doi.org/10.1109/SSE67621.2025.00024)
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-**Phaedrus: Predicting Dynamic Application Behavior with Lightweight Generative Models and LLMs** — Chatterjee, Jadhav & Pande (2024). *PACMPL (OOPSLA)*. [arXiv:2412.06994](https://arxiv.org/abs/2412.06994)
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<sub>List compiled from Semantic Scholar / OpenAlex citation data; please open a PR to add a missing paper.</sub>
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## Table of Contents
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-[Cited By](#cited-by)
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}
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```
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## Cited By
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CLDK ([Krishna et al., 2024](https://arxiv.org/abs/2410.13007)) is used and cited in a growing body of research on program analysis and code LLMs:
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-**RECON: An LLM-Enhanced Backward Constraint Analysis Framework** — Bappah et al. (2026). [arXiv:2606.10264](https://arxiv.org/abs/2606.10264)
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-**Architecting Open, Accountable, and Trustworthy AI-IDEs** — Contreras, Guerra & de Lara (2026). *Automated Software Engineering*. [doi:10.1007/s10515-026-00608-x](https://doi.org/10.1007/s10515-026-00608-x)
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-**Resolving Java Code Repository Issues with iSWE Agent** — Ganhotra et al. (2026). [arXiv:2603.11356](https://arxiv.org/abs/2603.11356)
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-**HookLens: Visual Analytics for Understanding React Hooks Structures** — Hwang et al. (2026). *IEEE PacificVis*. [arXiv:2602.17891](https://arxiv.org/abs/2602.17891)
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-**PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysis** — Cui, Krishna & Jha et al. (2025). [arXiv:2512.22113](https://arxiv.org/abs/2512.22113)
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-**Examining Software Developers' Needs for Privacy Enforcing Techniques: A Survey** — Theophilou & Kapitsaki (2025). *ACM SAC*. [arXiv:2512.14756](https://arxiv.org/abs/2512.14756)
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-**LLM as an Execution Estimator: Recovering Missing Dependency for Practical Time-Travelling Debugging** — Pei, Wang & Zhang et al. (2025). [arXiv:2508.18721](https://arxiv.org/abs/2508.18721)
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-**Agentic Multi-Modal LLMs for Software Comprehension: Structuring Code Summarization with Business Process Awareness** — Tamilselvam & Saxena (2025). *IEEE SSE*. [doi:10.1109/SSE67621.2025.00024](https://doi.org/10.1109/SSE67621.2025.00024)
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-**Phaedrus: Predicting Dynamic Application Behavior with Lightweight Generative Models and LLMs** — Chatterjee, Jadhav & Pande (2024). *PACMPL (OOPSLA)*. [arXiv:2412.06994](https://arxiv.org/abs/2412.06994)
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<sub>List compiled from Semantic Scholar / OpenAlex citation data; please open a PR to add a missing paper.</sub>
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Related publications:
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1. Pan, Rangeet, Myeongsoo Kim, Rahul Krishna, Raju Pavuluri, and Saurabh Sinha. "[Multi-language Unit Test Generation using LLMs.](https://arxiv.org/abs/2409.03093)" arXiv preprint arXiv:2409.03093 (2024).
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