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ICSE 2027: International Conference on Software Engineering

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截稿日期:
2026-06-23 已截稿
通知日期:
2026-10-20
会议日期:
2027-04-25
会议地点:
Dublin, Ireland
届数:
49
加入日历: Outlook / Apple 日历（.ics）
CCF: A   ICORE: A*   QUALIS: A1   浏览: 2420633   关注: 198   参加: 26
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会伴指数 (CP-I)

94.8 / 100
全站第 17 名 / 共 5,696 个会议 · 前 1%

软件工程 第 2 / 247

学术认可 (35%)
100
投稿选择性 (20%)
96
会议传承 (20%)
100
社区关注 (10%)
86
资料公开度 (15%)
80

用到的输入: 收录等级：CCF A, QUALIS A1 · 录用率：15.3%（有记录的 5 届的均值） · 有据可查的届次：49 · 在会伴关注它的研究者：198 人 · 过去 24 个月打开过本页的研究者：110 人

公开资料里还缺: 历届信息 (+3.0)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-14

征稿

ICSE 2027 (International Conference on Software Engineering) is a CCF A / ICORE A* / QUALIS A1 conference held in Dublin, Ireland on 2027-04-25. The paper submission deadline is 2026-06-23. Acceptance notifications are sent on 2026-10-20.

The International Conference on Software Engineering (ICSE) is the premier forum for presenting and discussing the most recent and significant technical research contributions in the field of Software Engineering. In the research track, we invite high-quality submissions of technical research papers describing original and unpublished results of software engineering research. ICSE 2027 will follow a single deadline structure. In other words, submissions will occur in one cycle. Further details in the section on Single Submission Cycle below. Research Areas ICSE welcomes submissions addressing topics across the full spectrum of Software Engineering, namely quantitative, qualitative, and mixed-methods research. Topics of interest include the following, grouped into nine research areas. Please note that these topics are by no means exhaustive. Each submission will need to indicate one of these nine areas as the chosen area. Optionally, the authors can consider adding an additional area. A paper may be moved from the chosen area(s) to another focus area at the discretion of the program chairs. Program chairs will ultimately assign a paper to an area chair, considering the authors’ selection, the paper’s content, and other factors such as (if applicable) possible conflicts of interest. AI for Software Engineering AI-enabled recommender systems for automated SE (e.g., code generation, program repair, AIOps, software composition analysis, etc.) Human-centered AI for SE (e.g., how software engineers can synergistically work with AI agents) Trustworthy AI for SE (e.g., how to provide guarantees, characterize limits, and prevent misuse of AI for SE) Sustainable AI for SE (e.g., how to reduce energy footprint for greener AI for SE) Collaborative AI for SE (e.g., how AI agents collaborate for automating SE) Automating SE tasks with LLM and other foundation models (e.g., large vision model) Efficacy measurement beyond traditional metrics (e.g., accuracy, BLEU, etc.) Prompt engineering for SE (e.g., novel prompt design) AI-assisted software design and model driven engineering (e.g., specification mining, program synthesis, software architectural design) Analytics Mining software repositories, including version control systems, issue tracking systems, software ecosystems, configurations, app stores, communication platforms, and novel software engineering data sources, to generate insights through various research methods Software visualization Data-driven user experience understanding and improvement Data driven decision making in software engineering Software metrics (and measurements) Architecture and Design Architecture and design measurement and assessment Software design methodologies, principles, and strategies Theory building for/of software design Architecture quality attributes, such as security, privacy, performance, reliability Modularity and reusability Design and architecture modeling and analysis Architecture recovery Dependency and complexity analysis Distributed architectures, such as microservice, SOA, cloud computing Patterns and anti-patterns Technical debt in design and architecture Architecture refactoring Adaptive architectures Architecture knowledge management Dependability and Security Formal methods and model checking (excluding solutions focusing solely on hardware) Reliability, availability, and safety Resilience and antifragility Confidentiality, integrity, privacy, and fairness Performance Design for dependability and security Vulnerability detection to enhance software security Dependability and security for embedded and cyber-physical systems Evolution Evolution and maintenance API design and evolution Release engineering and DevOps Software reuse Refactoring and program differencing Program comprehension Reverse engineering Environments and software development tools Traceability to understand evolution Human and Social Aspects Focusing on individuals (from program comprehension, workplace stress to job satisfaction and career progression) Focusing on teams (e.g., collocated, distributed, global, virtual; communication and collaboration within a team), communities (e.g., open source, communities of practice) and companies (organization, economics) Focusing on society (e.g., sustainability; diversity and inclusion) Focusing on programming languages, environments, and tools supporting individuals, teams, communities, and companies. Focusing on software development processes Requirements and Modeling Requirements engineering (incl. non-functional requirements) Theoretical requirement foundations Requirements and architecture Feedback, user and requirements management Requirements traceability and dependencies Modeling and model-driven engineering Variability and product lines Systems and software traceability Modeling languages, techniques, and tools Empirical studies on the application of model-based engineering Model-based monitoring and analysis Software Engineering for AI SE for AI models SE for systems with AI components SE for AI code, libraries, and datasets Engineering autonomic systems and self-healing systems Automated repair of AI models Testing and verification of AI-based systems Validation and user-based evaluation of AI-based systems Requirements engineering for AI-based systems Testing and Analysis Software testing Automated test generation techniques such as fuzzing, search-based approaches, and symbolic execution Testing and analysis of non-functional properties GUI testing Mobile application testing Program analysis Program synthesis (e.g., constraint based techniques) Program repair Debugging and fault localization Runtime analysis and/or error recovery Scope Since the authors will choose an area for their submission, the scope of each area becomes important. Some submissions may relate to multiple areas. In such cases, the authors should choose the area for which their paper brings the maximum new insights. Moreover, authors also have the choice of indicating an alternate area for each paper. Similarly, for certain papers, authors may have a question whether it belongs to any area, or is simply out of scope. For such cases, we recommend that the authors judge whether their paper brings new insights for software engineering. As an example, a formal methods paper with a focus on hardware verification may be deemed out of scope for ICSE. In general, papers that only peripherally concern software engineering and do not give new insights from the software engineering perspective would be less relevant to ICSE. Our goal, however, is to be descriptive rather than prescriptive, enabling authors to make their own decisions about relevance.
由 Dou Sun 最后更新于

录用率

平均录用率: 16.2% 18 年间 (1995–2012).

年份提交数录用数录用率(%)
20124088721.3%
20114416214.1%
20103805213.7%
20094055012.3%
20083715615.1%
20073344914.7%
2006395369.1%
20053134414.1%
20044365813.3%
20033244213%
20023034815.8%
20012684717.5%
20003354914.6%
19992695018.6%
19982094119.6%
19972195022.8%
19962135224.4%
19951552818.1%

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