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A potentially out-of-date publication list (Google Scholar and dblp are your friends). Clicking the title of any publication should lead to an author copy of the publication. If not, feel free to contact me for a copy.

Overview

Publications

Projects

Photography

Publications

  1. Pârțachi, P.-P., & Sugiyama, M., Bringing Structure to Naturalness: On the Naturalness of ASTs., In Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE ’24): Companion Proceedings. ACM, April 2024. Bib; DOI; PDF

  2. Pârțachi, P.-P., White, D. R., & Barr, E. T., Aide-mémoire: Improving a Project’s Collective Memory via Pull Request–Issue Links. In ACM Transactions on Software Engineering and Methodology, ACM, May 2022. GitHub Link; Bib; DOI; PDF

  3. Pârțachi, P.-P., Treude, C., Dash, S. K., & Barr, E. T., POSIT: Simultaneously Tagging Natural and Programming Languages. In 42nd International Conference on Software Engineering (ICSE ’20). Seoul, Republic of Korea: ACM, May 2020. Project Page; Bib; DOI; PDF

  4. Pârțachi, P.-P., Dash, S. K., Allamanis, M., & Barr, E. T., Flexeme: Untangling Commits Using Lexical Flows. In 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, (ESEC/FSE 2020). Sacramento, California, United States; ACM, November 2020 Project Page; Bib; DOI; PDF

Thesis

  1. Pârțachi, Profir-Petru; (2020) Improving Software Project Health Using Machine Learning. Doctoral thesis (Ph.D), UCL (University College London). UCL Discovery; LaTeX Repo; Bib; URI; PDF

Japan

  1. Ramadhanty, S., Pârțachi, P.-P., & Kobayashi, T., Evaluating Transformer-Based Embeddings for Software Change Recommendation: From General Models to Specialized Models. In The 222nd Group Meeting of IPSJ SIGSE, Tokyo, March 2026. Technical Report of IPSJ, Vol. 2026-SE-222, No. 3, pp. 1–8. Link

  2. Lin, Q., Pârțachi, P.-P., & Kobayashi, T., Structure-Aware Enhanced LLMs via Knowledge Graphs for Microservice Architecture Documentation. In The 222nd Group Meeting of IPSJ SIGSE, Tokyo, March 2026. Technical Report of IPSJ, Vol. 2026-SE-222, No. 20, pp. 1–8. Link

  3. Ueno, Y., Pârțachi, P.-P., & Kobayashi, T., Universal ASTを用いたハンク間関係の言語横断学習に基づく複合コミット分割. In IEICE ソフトウェアサイエンス研究専門委員会 2026年3月研究会. IEICE 信学技報 SS2025-47, Vol. 125, No. 376, pp. 103–108, 長崎, March 2026.

  4. Ueno, Y., Pârțachi, P.-P., & Kobayashi, T., 複合コミット自動分割における言語を横断した抽象構文木の作成の提案. In 日本ソフトウェア科学会 第32回ソフトウェア工学の基礎ワークショップ (FOSE2025) ポスター, 愛媛, November 2025.

  5. Ramadhanty, S., Pârțachi, P.-P., & Kobayashi, T., The Enhancement of Software Change Recommendations using Context-Aware Representations. In 学生国際英語ポスターセッション, IPSJ/SIGSE ソフトウェアエンジニアリングシンポジウム2025, 東京, September 2025.

  6. Ueno, Y., Pârțachi, P.-P., & Kobayashi, T., Curating Merged Pull Requests as a Dataset for Commit Untangling Tasks. In 学生国際英語ポスターセッション, IPSJ/SIGSE ソフトウェアエンジニアリングシンポジウム2025, 東京, September 2025.