Conference Information

ICPC 2027: International Conference on Program Comprehension

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Submission Date:
2026-11-05 Due in 23 days
Notification Date:
2027-01-14
Conference Date:
2027-04-25
Location:
Dublin, Ireland
Years:
CCF: B   ICORE: A   QUALIS: A2   Viewed: 60647   Tracked: 49   Attend: 8
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Conference Partner Index (CP-I)

82.3 / 100
Ranked #169 of 5,697 conferences · Top 3%

#22 of 247 in Software Engineering

Academic recognition (35%)
92
Submission selectivity (20%)
58
Editions held (20%)
96
Community attention (10%)
64
Public record completeness (15%)
85

Inputs used: Listed as CCF B, ICORE A, QUALIS A2 · Acceptance rate: 46.8% (mean of 5 editions on file) · Editions on record: 35 · Researchers following it here: 49 · Researchers who opened this page in the past 24 months: 34

Missing from the public record: Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 100% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-10-12

Call For Papers

ICPC 2027 (International Conference on Program Comprehension) is a CCF B / ICORE A / QUALIS A2 conference held in Dublin, Ireland on 2027-04-25. The paper submission deadline is 2026-11-05. Acceptance notifications are sent on 2027-01-14.

The 35th IEEE/ACM International Conference on Program Comprehension (ICPC) is the premier venue for work in the area of software program comprehension. It encompasses human activities for comprehending the software as well as methodologies and technologies for supporting such comprehension. The Research Track provides a quality forum for researchers and practitioners from academia, industry, and government to present and discuss new results in program comprehension. Topics of interest for all tracks include, but are not limited to: Comprehension challenges and opportunities in the era of large language models (LLMs) and AI-assisted programming, including (but not limited to) understanding LLM-generated code, hybrid human-AI codebases, and the impact of AI tools on traditional program comprehension processes and cognitive load; Empirical evaluations of program comprehension tools, techniques, and approaches; Human aspects in program comprehension, including collaborative software engineering practices, gender considerations, information processing strategies, the role of emotions, emotional awareness, and more; Cognitive theories for program comprehension accompanied by different empirical strategies, including experiments, surveys, and case studies; Topics at the intersection between program comprehension and programming education; Individual, collaborative, distributed, and global program comprehension; Novel visualization or summarization techniques and interfaces to support program comprehension, including searching, browsing, and analyzing; Comprehension of specific types of software systems, such as open-source and closed-source, mobile applications, spreadsheets, web-based systems, legacy systems, product lines, libraries, multi-threaded applications, and systems of systems; Comprehension in the context of diverse software process models and specific lifecycle activities, such as: maintenance, evolution, re-engineering, migration, security, auditing, and testing; Comprehension of software artifacts ranging from requirements documents to test cases and crash logs; from API documentation to models, meta-models and model transformation; and from Stack Overflow questions & answers to GitHub code review messages or video tutorials — all software artifacts and formal or informal documentation that software developers encounter when creating or evolving software; Comprehension and legal issues, such as due diligence, intellectual property and licensing, reverse engineering, and litigation; Issues and case studies in the transfer of program comprehension technology to industry; Automated tool support for program comprehension.
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Acceptance Ratio

Average acceptance rate: 53.1% over 10 years (2000–2009).

YearSubmittedAcceptedAccepted(%)
2009743648.6%
2008572747.4%
2007662639.4%
2006733446.6%
2005542851.9%
2004422150%
2003522751.9%
2002443170.5%
2001442863.6%
2000392461.5%

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