mlsanityData to 7 Oct 2026

Towards Structured, State-Aware, and Execution-Grounded Reasoning for Software Engineering Agents

arXiv 2602.04640 ↗First posted 4 Feb 2026cs.SE cs.AIcited by 2

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Software Engineering (SE) agents have shown promising abilities in supporting various SE tasks. Current SE agents remain fundamentally reactive, making decisions mainly based on conversation history and the most recent response. However, this reactive design provides no explicit structure or persistent state within the agent's memory, making long-horizon reasoning challenging. As a result, SE agents struggle to maintain a coherent understanding across reasoning steps, adapt their hypotheses as new evidence emerges, or incorporate execution feedback into the mental reasoning model of the system state. In this position paper, we argue that, to further advance SE agents, we need to move beyond reactive behavior toward a structured, state-aware, and execution-grounded reasoning. We outline how explicit structure, persistent and evolving state, and the integration of execution-grounded feedback can help SE agents perform more coherent and reliable reasoning in long-horizon tasks. We also provide an initial roadmap for developing next-generation SE agents that can more effectively perform real-world tasks.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 9 of its 22 references that are in the map. First posted on arXiv 4 Feb 2026.

Builds on

9 of 22 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025Understanding Software Engineering Agents: A Study of Thought-Action-Result Trajectories23 Jun
  2. 2025TRAIL: Trace Reasoning and Agentic Issue Localization13 May
  3. 2024An Empirical Study on LLM-based Agents for Automated Bug Fixing15 Nov
  4. 2024Exploring LLM-based Agents for Root Cause Analysis7 Mar

Other references · 5

  1. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  2. 2025A-MEM: Agentic Memory for LLM Agentscited by 1,000
  3. 2024AutoCodeRover: Autonomous Program Improvementcited by 272
  4. 2025Agent-SAMA: State-Aware Mobile Assistantcited by 12
  5. 2024Order Matters! An Empirical Study on Large Language Models' Input Order Bias in Software Fault Localizationcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Structurally Aligned Subtask-Level Memory for Software Engineering Agents
  2. 2026SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Context
  3. 2025From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents
  4. 2026Agentic Software: How AI Agents Are Restructuring the Software Paradigm
  5. 2026Argus: A General-Purpose Agentic Reasoning Runtime for Long-Horizon Tasks
  6. 2025TOM-SWE: User Mental Modeling For Software Engineering Agents
  7. 2026AgentForge: Execution-Grounded Multi-Agent LLM Framework for Autonomous Software Engineering
  8. 2026Model-Based Agentic Software Engineering