CodeR3: A GenAI-Powered Workflow Repair and Revival Ecosystem
- URL: http://arxiv.org/abs/2511.19510v1
- Date: Mon, 24 Nov 2025 01:06:45 GMT
- Title: CodeR3: A GenAI-Powered Workflow Repair and Revival Ecosystem
- Authors: Asif Zaman, Kallol Naha, Khalid Belhajjame, Hasan M. Jamil,
- Abstract summary: We present a novel legacy Reuse workflow migration system, called CodeR$3$ (stands for Code Repair, Revival and Reuse)<n>We use generative AI to analyze the characteristics of decayed, reproduce them into modern workflow technologies like Snakemake and VisFlow.<n>Our system additionally integrates stepwise workflow analysis, automated service substitution, visualization, and human-in-the-loop validation.
- Score: 0.5249805590164902
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Scientific workflows encode valuable domain expertise and computational methodologies. Yet studies consistently show that a significant proportion of published workflows suffer from decay over time. This problem is particularly acute for legacy workflow systems like Taverna, where discontinued services, obsolete dependencies, and system retirement render previously functional workflows unusable. We present a novel legacy workflow migration system, called CodeR$^3$ (stands for Code Repair, Revival and Reuse), that leverages generative AI to analyze the characteristics of decayed workflows, reproduce them into modern workflow technologies like Snakemake and VisFlow. Our system additionally integrates stepwise workflow analysis visualization, automated service substitution, and human-in-the-loop validation. Through several case studies of Taverna workflow revival, we demonstrate the feasibility of this approach while identifying key challenges that require human oversight. Our findings reveal that automation significantly reduces manual effort in workflow parsing and service identification. However, critical tasks such as service substitution and data validation still require domain expertise. Our result will be a crowdsourcing platform that enables the community to collaboratively revive decayed workflows and validate the functionality and correctness of revived workflows. This work contributes a framework for workflow revival that balances automation efficiency with necessary human judgment.
Related papers
- Learning to Compose for Cross-domain Agentic Workflow Generation [56.630382886594184]
We create an open-source LLM for cross-domain workflow generation.<n>We learn a compact set of reusable workflow capabilities across diverse domains.<n>Our 1-pass generator surpasses SOTA refinement baselines that consume 20 iterations.
arXiv Detail & Related papers (2026-02-11T18:27:22Z) - EmboCoach-Bench: Benchmarking AI Agents on Developing Embodied Robots [68.29056647487519]
Embodied AI is fueled by high-fidelity simulation and large-scale data collection.<n>However, this scaling capability remains bottlenecked by a reliance on labor-intensive manual oversight.<n>We introduce textscEmboCoach-Bench, a benchmark evaluating the capacity of LLM agents to autonomously engineer embodied policies.
arXiv Detail & Related papers (2026-01-29T11:33:49Z) - Automation and Reuse Practices in GitHub Actions Workflows: A Practitioner's Perspective [41.512965779724354]
GitHub supports workflow automation through GitHub Actions.<n>We surveyed 419 practitioners to elucidate good and bad workflow development practices.<n>We observe a tendency to focus automation efforts on core CI/CD tasks, with less emphasis on crucial areas like security analysis and performance monitoring.
arXiv Detail & Related papers (2026-01-16T13:54:54Z) - SEW: Self-Evolving Agentic Workflows for Automated Code Generation [24.16770109875788]
We propose textbfSelf-textbfEvolving textbfWork (textbfSEW), a novel framework that automatically generates and optimises multi-agentflow.<n>Our SEW can automatically design agentic and optimise them through self-evolution, bringing up to 33% improvement on LiveCodeBench.
arXiv Detail & Related papers (2025-05-24T11:12:14Z) - Flow: Modularized Agentic Workflow Automation [53.073598156915615]
Multi-agent frameworks powered by large language models (LLMs) have demonstrated great success in automated planning and task execution.<n>However, the effective adjustment of agentic during execution has not been well studied.<n>In this paper, we define an activity-on-vertex (AOV) graph, which allows continuous workflow refinement by agents.<n>Our proposed multi-agent framework achieves efficient concurrent execution of subtasks, effective goal achievement, and enhanced error tolerance.
arXiv Detail & Related papers (2025-01-14T04:35:37Z) - AFlow: Automating Agentic Workflow Generation [36.61172223528231]
Large language models (LLMs) have demonstrated remarkable potential in solving complex tasks across diverse domains.<n>We introduce AFlow, an automated framework that efficiently explores this space using Monte Carlo Tree Search.<n> Empirical evaluations across six benchmark datasets demonstrate AFlow's efficacy, yielding a 5.7% average improvement over state-of-the-art baselines.
arXiv Detail & Related papers (2024-10-14T17:40:40Z) - Benchmarking Agentic Workflow Generation [80.74757493266057]
We introduce WorfBench, a unified workflow generation benchmark with multi-faceted scenarios and intricate graph workflow structures.<n>We also present WorfEval, a systemic evaluation protocol utilizing subsequence and subgraph matching algorithms.<n>We observe that the generated can enhance downstream tasks, enabling them to achieve superior performance with less time during inference.
arXiv Detail & Related papers (2024-10-10T12:41:19Z) - WorkflowHub: a registry for computational workflows [0.34864924310198164]
As both combined records of analysis and descriptions of processing steps should be reusable, reusable, and available.
Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity.
Hub provides a unified registry for all computational registries that links to community repositories.
The registry has a global reach, with hundreds of research organisations involved, and more than 700 registered.
arXiv Detail & Related papers (2024-10-09T14:36:27Z) - Agent Workflow Memory [71.81385627556398]
We introduce Agent Memory, a method for inducing commonly reused routines.
AWM substantially improves the baseline results by 24.6% and 51.1% relative success rate.
Online AWM robustly generalizes in cross-task, website, and domain evaluations.
arXiv Detail & Related papers (2024-09-11T17:21:00Z) - The Hidden Costs of Automation: An Empirical Study on GitHub Actions Workflow Maintenance [45.53834452021771]
GitHub Actions (GA) is an orchestration platform that streamlines the automatic execution of engineering tasks.
Human intervention is necessary to correct defects, update dependencies, or existing workflow files.
arXiv Detail & Related papers (2024-09-04T01:33:16Z) - Reusability Challenges of Scientific Workflows: A Case Study for Galaxy [56.78572674167333]
This study examined the reusability of existing and exposed several challenges.
The challenges preventing reusability include tool upgrading, tool support, design flaws, incomplete, failure to load a workflow, etc.
arXiv Detail & Related papers (2023-09-13T20:17:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.