[1]

Bugden W, Alahmar A. 2022. The safety and performance of prominent programming languages. International Journal of Software Engineering and Knowledge Engineering 32:713−744

doi: 10.1142/s0218194022500231
[2]

Köster J. 2016. Rust-Bio: a fast and safe bioinformatics library. Bioinformatics 32:444−446

doi: 10.1093/bioinformatics/btv573
[3]

Huey JD, Abdennur N. 2024. Bigtools: a high-performance BigWig and BigBed library in Rust. Bioinformatics 40:btae350

doi: 10.1093/bioinformatics/btae350
[4]

Wiewiórka M, Khamutou P, Zbysiński M, Gambin T. 2025. polars-bio—fast, scalable, and out-of-core operations on large genomic interval datasets. Bioinformatics 41:btaf640

doi: 10.1093/bioinformatics/btaf640
[5]

Wei W, Gui S, Yang J, Garrison E, Yan J, et al. 2025. wgatools: an ultrafast toolkit for manipulating whole-genome alignments. Bioinformatics 41:btaf132

doi: 10.1093/bioinformatics/btaf132
[6]

Buffalo V. 2024. GRanges: a Rust library for genomic range data. bioRxiv 1−5

doi: 10.1101/2024.05.24.595786
[7]

Hou X, Zhao Y, Liu Y, Yang Z, Wang K, et al. 2024. Large language models for software engineering: a systematic literature review. ACM Transactions on Software Engineering and Methodology 33:1−79

doi: 10.1145/3695988
[8]

Zhou X, Liang P, Zhang B, Li Z, Ahmad A, et al. 2025. Exploring the problems, their causes and solutions of AI pair programming: a study on GitHub and Stack Overflow. Journal of Systems and Software 219:112204

doi: 10.1016/j.jss.2024.112204
[9]

Zhang B, Liang P, Zhou X, Ahmad A, Waseem M. 2023. Practices and challenges of using GitHub Copilot: an empirical study. arXiv Preprint: 2303.08733

doi: 10.48550/arXiv.2303.08733
[10]

Imai S. 2022. Is GitHub copilot a substitute for human pair-programming? An empirical study. Proceedings of the 44th International Conference on Software Engineering: Companion Proceedings, Pittsburgh, PA, USA, 22−27 May, 2022. New York, USA: ACM. pp. 319−321 doi: 10.1145/3510454.3522684
[11]

Li R, Wang B, Li T, Saxena P, Kundu A. 2025. Translating C to Rust: lessons from a user study. Proceedings 2025 Network and Distributed System Security Symposium, San Diego, CA, USA, 24−28 February 2025. USA: Internet Society. pp. 1−18 doi: 10.14722/ndss.2025.241407
[12]

Open2C, Abdennur N, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A, et al. 2024. Pairtools: from sequencing data to chromosome contacts. PLoS Computational Biology 20:e1012164

doi: 10.1371/journal.pcbi.1012164
[13]

Durand NC, Shamim MS, Machol I, Rao SSP, Huntley MH, et al. 2016. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Systems 3:95−98

doi: 10.1016/j.cels.2016.07.002
[14]

Servant N, Varoquaux N, Lajoie BR, Viara E, Chen CJ, et al. 2015. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biology 16:259

doi: 10.1186/s13059-015-0831-x
[15]

Grüning B, Chilton J, Köster J, Dale R, Soranzo N, et al. 2018. Practical computational reproducibility in the life sciences. Cell Systems 6:631−635

doi: 10.1016/j.cels.2018.03.014
[16]

Nanthaamornphong A, Carver JC. 2017. Test-Driven Development in scientific software: a survey. Software Quality Journal 25:343−372

doi: 10.1007/s11219-015-9292-4
[17]

Shetty M, Jain N, Godbole A, Seshia SA, Sen K. 2024. Syzygy: dual code-test C to (safe) Rust translation using LLMs and dynamic analysis. arXiv Preprint: 2412.14234

doi: 10.48550/arXiv.2412.14234
[18]

Maddila C, Tait A, Chang C, Cheng D, Ahmad N, et al. 2026. Agentic program repair from test failures at scale: a neuro-symbolic approach with static analysis and test execution feedback. IEEE Transactions on Software Engineering 52:2446−2462

doi: 10.1109/TSE.2026.3696849
[19]

Palavalli MA, Santolucito M. 2024. Using a feedback loop for LLM-based infrastructure as code generation. arXiv Preprint: 2411.19043

doi: 10.48550/arXiv.2411.19043
[20]

Naqvi S, Baqar M, Ali Mohammad N. 2026. The rise of agentic testing: multi-agent systems for robust software quality assurance. arXiv Preprint: 2601.02454

doi: 10.48550/arXiv.2601.02454
[21]

Koch C. 2026. Agentic Agile-V: from vibe coding to verified engineering in software and hardware development. arXiv Preprint: 2605.20456

doi: 10.48550/arXiv.2605.20456
[22]

Li H. 2011. Tabix: fast retrieval of sequence features from generic TAB-delimited files. Bioinformatics 27:718−719

doi: 10.1093/bioinformatics/btq671
[23]

Zhou J, Zhang B, Li G, Chen X, Li H, et al. 2024. An AI agent for fully automated multi-omic analyses. Advanced Science 11:2407094

doi: 10.1002/advs.202407094
[24]

Fa D, Čuljak M, Pandža B, Čupić M. 2026. BioAgent Bench: an AI agent evaluation suite for bioinformatics. arXiv Preprint: 2601.21800

doi: 10.48550/arXiv.2601.21800