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JournalQ1· SCImago 2025

ACM Transactions on Software Engineering and Methodology

ISSN 1049-331X

• Q1Quartile
• 1.00SJR
• 95h-index
• 15papers summarised

About this journal

ACM Transactions on Software Engineering and Methodology is a Q1 journal by SCImago Journal Rank (2025 data), with an SJR of 1.00 and an h-index of 95. Most of its papers in the Pofolia pool fall under Software. Pofolia holds AI summaries of 15 paper(s) from this journal; the most cited is “Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions” (167 citations).

The quartile (Q1–Q4) is the journal's percentile position within its subject area by SCImago Journal Rank; Q1 is the top 25%. What is a Q1 journal? · What is the h-index?

Most-cited papers in Software →

Papers we summarise from this journal

• Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions2026 · 167 citations
• Large Language Models for Cyber Security: A Systematic Literature Review2025 · 139 citations
• MOS: Towards Effective Smart Contract Vulnerability Detection through Mixture-of-Experts Tuning of Large Language Models2026 · 4 citations
• An Empirical Study of False Negatives and Positives of Static Code Analyzers From the Perspective of Historical Issues2026 · 2 citations
• Agent READMEs: An Empirical Study of Context Files for Agentic Coding2026 · 2 citations
• Agentic Refactoring: An Empirical Study of AI Coding Agents2026 · 1 citations
• TestART: Improving LLM-based Unit Test ing via Co-evolution of A utomated Generation and R epair I t eration2026 · 1 citations
• On the Effectiveness of Training Data Optimization for LLM-based Code Generation: An Empirical Study2026 · 1 citations
• Beyond Accuracy: Behavioral Dynamics of Agentic Multi-Hunk Repair2026 · 0 citations
• Feature-Aware Test Generation for Deep Learning Models2026 · 0 citations
• LLMs for Model-driven Engineering: A Systematic Literature Review2026 · 0 citations
• LLMSA-MC: Bridging LLM Reasoning and Static Analysis for Detecting Missing-Check Bugs in Linux Kernels2026 · 0 citations
• “Wait, My Tool Can’t Do That?” A Fine-Grained Capability Study of Modern Static Taint Analyzers2026 · 0 citations
• Bug Whisperer: Unleashing LLMs to Craft Context-Aware Tests Guided by Path Constraints and Bug Clues2026 · 0 citations
• Neural Program Modeling Learning Program-Specific Models that Predict Execution Features from Input Features and vice versa2026 · 0 citations

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