Structured ETL and Data-Preparation Pipeline Descriptions for LLM Workflow Generation Studies
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2026
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| _version_ | 1866902177297989632 |
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| author | Alidu, Abubakari Ciavotta, Michele Flavio, De Paoli |
| author_facet | Alidu, Abubakari Ciavotta, Michele Flavio, De Paoli |
| contents | <p class="text-size-chat leading-[calc(var(--codex-chat-font-size)+8px)] extension:leading-normal my-2">This dataset contains 60 structured natural-language pipeline descriptions for studying LLM-based workflow code generation, bounded self-repair, and pipeline design. The corpus includes 40 main-study ETL/data-preparation pipeline descriptions and 20 held-out validation pipeline descriptions. The descriptions cover repository-derived and synthetic workflow scenarios across common orchestration patterns, including linear pipelines, fan-out/fan-in, branch/merge, sensor-gated workflows, staged ETL, and fan-out-only designs.</p> <p class="text-size-chat leading-[calc(var(--codex-chat-font-size)+8px)] extension:leading-normal my-2">The dataset is intended to support research on executable workflow generation, pipeline-design reasoning, orchestration-aware code generation, and evaluation of LLM repair behavior for data-processing workflows. Each description specifies the pipeline purpose, control-flow dependencies, data artifacts, external systems, pipeline steps, and scheduling information.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20377524 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Structured ETL and Data-Preparation Pipeline Descriptions for LLM Workflow Generation Studies Alidu, Abubakari Ciavotta, Michele Flavio, De Paoli ETL pipelines data preparation workflow generation pipeline design large language models LLMs workflow orchestration Computer and Information Sciences Software Engineering Data Engineering; Artificial Intelligence Information Systems <p class="text-size-chat leading-[calc(var(--codex-chat-font-size)+8px)] extension:leading-normal my-2">This dataset contains 60 structured natural-language pipeline descriptions for studying LLM-based workflow code generation, bounded self-repair, and pipeline design. The corpus includes 40 main-study ETL/data-preparation pipeline descriptions and 20 held-out validation pipeline descriptions. The descriptions cover repository-derived and synthetic workflow scenarios across common orchestration patterns, including linear pipelines, fan-out/fan-in, branch/merge, sensor-gated workflows, staged ETL, and fan-out-only designs.</p> <p class="text-size-chat leading-[calc(var(--codex-chat-font-size)+8px)] extension:leading-normal my-2">The dataset is intended to support research on executable workflow generation, pipeline-design reasoning, orchestration-aware code generation, and evaluation of LLM repair behavior for data-processing workflows. Each description specifies the pipeline purpose, control-flow dependencies, data artifacts, external systems, pipeline steps, and scheduling information.</p> |
| title | Structured ETL and Data-Preparation Pipeline Descriptions for LLM Workflow Generation Studies |
| topic | ETL pipelines data preparation workflow generation pipeline design large language models LLMs workflow orchestration Computer and Information Sciences Software Engineering Data Engineering; Artificial Intelligence Information Systems |
| url | https://doi.org/10.5281/zenodo.20377524 |