Assessing the Quality of the Steps to Reproduce in Bug Reports
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Abstract (arXiv)
A major problem with user-written bug reports, indicated by developers and documented by researchers, is the (lack of high) quality of the reported steps to reproduce the bugs. Low-quality steps to reproduce lead to excessive manual effort spent on bug triage and resolution. This paper proposes Euler, an approach that automatically identifies and assesses the quality of the steps to reproduce in a bug report, providing feedback to the reporters, which they can use to improve the bug report. The feedback provided by Euler was assessed by external evaluators and the results indicate that Euler correctly identified 98% of the existing steps to reproduce and 58% of the missing ones, while 73% of its quality annotations are correct.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jun 2019.
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Citing papers per year: 2024: 1; 2025: 5; 2026: 7.
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- 2025BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systemscited by 40
- 2025Agentic Bug Reproduction for Effective Automated Program Repair at Googlecited by 22
- 2026On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agentscited by 17
- 2026Evaluating and Improving Automated Repository-Level Rust Issue Resolution with LLM-based Agentscited by 8
- 2025Past, Present, and Future of Bug Tracking in the Generative AI Eracited by 4
- 2025Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generationcited by 3
- 2025Combining Language and App UI Analysis for the Automated Assessment of Bug Reproduction Stepscited by 2
- 2026ImproBR: Bug Report Improver Using LLMscited by 2
- 2026What Makes a Good Bug Report for an AI Agent?cited by 1
- 2026Writing Bug Reports for Software Repair Agents: What Information Matters Most?cited by 1
- 2024AURORA: Navigating UI Tarpits via Automated Neural Screen Understandingcited by 0
- 2026FeedAIde: Guiding App Users to Submit Rich Feedback Reports by Asking Context-Aware Follow-Up Questionscited by 0
- 2026How Do LLMs Read Bug Reports? An Empirical Study of Attention in LLMs for Automated Program Repair28 Jul 2026
- 2026Writing Bug Reports for Software Repair Agents: What Information Matters Most?10 Jul 2026
- 2026What Makes a Good Bug Report for an AI Agent?8 Jul 2026
- 2026ImproBR: Bug Report Improver Using LLMs28 Apr 2026
- 2026FeedAIde: Guiding App Users to Submit Rich Feedback Reports by Asking Context-Aware Follow-Up Questions4 Mar 2026
- 2026Evaluating and Improving Automated Repository-Level Rust Issue Resolution with LLM-based Agents26 Feb 2026
- 2026On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agents28 Jan 2026
- 2025Past, Present, and Future of Bug Tracking in the Generative AI Era9 Oct 2025
- 2025BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems21 May 2025
- 2025Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generation26 Apr 2025
- 2025Combining Language and App UI Analysis for the Automated Assessment of Bug Reproduction Steps6 Feb 2025
- 2025Agentic Bug Reproduction for Effective Automated Program Repair at Google3 Feb 2025
1 more
- 2025BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systemscited by 40
- 2025Agentic Bug Reproduction for Effective Automated Program Repair at Googlecited by 22
- 2026On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agentscited by 17
- 2026Evaluating and Improving Automated Repository-Level Rust Issue Resolution with LLM-based Agentscited by 8
- 2026What Makes a Good Bug Report for an AI Agent?cited by 1
- 2026Writing Bug Reports for Software Repair Agents: What Information Matters Most?cited by 1
- 2026Writing Bug Reports for Software Repair Agents: What Information Matters Most?10 Jul 2026
- 2026What Makes a Good Bug Report for an AI Agent?8 Jul 2026
- 2026Evaluating and Improving Automated Repository-Level Rust Issue Resolution with LLM-based Agents26 Feb 2026
- 2026On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agents28 Jan 2026
- 2025BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems21 May 2025
- 2025Agentic Bug Reproduction for Effective Automated Program Repair at Google3 Feb 2025
- 2025Past, Present, and Future of Bug Tracking in the Generative AI Eracited by 4
- 2025Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generationcited by 3
- 2025Combining Language and App UI Analysis for the Automated Assessment of Bug Reproduction Stepscited by 2
- 2026ImproBR: Bug Report Improver Using LLMscited by 2
- 2024AURORA: Navigating UI Tarpits via Automated Neural Screen Understandingcited by 0
- 2026FeedAIde: Guiding App Users to Submit Rich Feedback Reports by Asking Context-Aware Follow-Up Questionscited by 0
- 2026How Do LLMs Read Bug Reports? An Empirical Study of Attention in LLMs for Automated Program Repaircited by 0
- 2026How Do LLMs Read Bug Reports? An Empirical Study of Attention in LLMs for Automated Program Repair28 Jul 2026
- 2026ImproBR: Bug Report Improver Using LLMs28 Apr 2026
- 2026FeedAIde: Guiding App Users to Submit Rich Feedback Reports by Asking Context-Aware Follow-Up Questions4 Mar 2026
- 2025Past, Present, and Future of Bug Tracking in the Generative AI Era9 Oct 2025
- 2025Can We Enhance Bug Report Quality Using LLMs?: An Empirical Study of LLM-Based Bug Report Generation26 Apr 2025
- 2025Combining Language and App UI Analysis for the Automated Assessment of Bug Reproduction Steps6 Feb 2025
- 2024AURORA: Navigating UI Tarpits via Automated Neural Screen Understanding1 Apr 2024