| dc.contributor.author | Lamprou, Evangelos | |
| dc.contributor.author | Kalhauge, Christian | |
| dc.contributor.author | Rinard, Martin | |
| dc.contributor.author | Vasilakis, Nikos | |
| dc.date.accessioned | 2025-12-04T20:12:15Z | |
| dc.date.available | 2025-12-04T20:12:15Z | |
| dc.date.issued | 2025-10-13 | |
| dc.identifier.isbn | 979-8-4007-2205-9 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/164203 | |
| dc.description | PACMI ’25, October 13-16, 2025, Seoul, Republic of Korea | en_US |
| dc.description.abstract | Large language models (LLMs) are achieving state-of-the-art results across a wide variety of software transformation tasks---including translating across languages and lifting opaque software components to high-level languages. Unfortunately, their results are often subtly incorrect, insecure, or underperformant---affecting the widespread deployment of these LLM-driven techniques in settings that go beyond the narrow scope of academic papers. This paper posits that such widespread deployment crucially depends on developing appropriate model guardrails for safeguarding the results of the transformation process. Such guardrails can be supported by component exoskeletons, tunable partial specifications extracted mostly automatically from the original, pre-transformed component. Exoskeletons serve as component projections that supplement, and often go through, the entire transformation process, confirming that the new, transformed component meets the original specifications. They show promise on several real-world scenarios and unearth exciting research directions. | en_US |
| dc.publisher | ACM|Practical Adoption Challenges of ML for Systems | en_US |
| dc.relation.isversionof | https://doi.org/10.1145/3766882.3767171 | en_US |
| dc.rights | Creative Commons Attribution | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Association for Computing Machinery | en_US |
| dc.title | Guarding LLM-aided Software Transformation Tasks via Component Exoskeletons | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Evangelos Lamprou, Christian Gram Kalhauge, Martin C. Rinard, and Nikos Vasilakis. 2025. Guarding LLM-aided Software Transformation Tasks via Component Exoskeletons. In Proceedings of the 4th Workshop on Practical Adoption Challenges of ML for Systems (PACMI '25). Association for Computing Machinery, New York, NY, USA, 13–18. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.identifier.mitlicense | PUBLISHER_POLICY | |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
| dc.date.updated | 2025-11-01T07:57:33Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The author(s) | |
| dspace.date.submission | 2025-11-01T07:57:33Z | |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |