Driven by advancements in areas such as artificial intelligence, distributed systems, autonomous intelligent systems, and cyber-physical systems, complex computer systems increasingly shape every aspect of human life, from manufacturing and communications to healthcare, defense, transportation, and energy, the demand for advanced methodologies and tools is growing. These systems are often distributed across heterogeneous networks, leveraging vast amounts of data alongside emerging artificial intelligence (AI) and machine learning techniques. Recent trends, including the rise of large language models (LLMs) and embodied intelligence, have introduced additional challenges and opportunities in the engineering of such systems. The complexity of modern systems arises from dynamic operating environments, diverse functional requirements, and conflicting needs such as performance, scalability, security, dependability, and adaptability. These challenges are compounded by factors like real-time behavior, fault tolerance, robustness, and long-term sustainability, making the engineering of these systems a multidisciplinary effort.

The 29th International Conference on Engineering of Complex Computer Systems (ICECCS 2025) is a well-established event that has been held around the world for over 29 years. It aims to bring together experts from industry, academia, and government to exchange ideas on the engineering of intricate systems. ICECCS 2025 will be held on 2-4 July 2025 in Hangzhou, China. We encourage contributions that tackle both theoretical and practical challenges, from long-term research agendas to near-term industry needs.

ICECCS is a CCF-C conference by the China Computer Federation (CCF) and a B-ranked international conference by the Computing Research and Education Association of Australasia (CORE) 2023 ranking.

Topics of Interest

We welcome submissions in a wide range of topics related to complex computer systems, including but not limited to:
Requirements, Modeling and Formal Methods

Requirements analysis and specification
Model-driven development
Model checking
SAT/SMT solvers for software analysis and testing

Complex Systems Design and Architecture

Modeling, designing, and managing complex computer systems
Software and system architecture for large-scale systems
Engineering adaptive and resilient systems with dynamic requirements
Cross-discipline integration and system-level optimization techniques
Integration of emerging technologies (e.g., quantum computing, blockchain) into complex system design

Software Engineering

Verification and validation
Reverse engineering and refactoring
Human Machine Interaction
Agile methods
Software supply chain of complex systems

Simulation, Testing, and Validation

Advanced simulation techniques for complex systems
Digital twins and virtual testing environments for complex systems
Simulation-driven development and validation methodologies for complex systems
Simulation-based testing for complex systems
Benchmarking and Test Suites

Security, Reliability and Dependability

Safety-critical and fault-tolerant architectures
Formal methods
Security and privacy of complex systems
Privacy-preserving AI
Fairness

Large Language Models (LLMs) and AI-driven Systems

Safety, security, reliability, and robustness of LLMs and AI systems
Integration of LLMs within complex systems
Applications of LLMs to complex systems
Scalability, performance, and efficiency optimization for AI-driven systems
Trustworthiness and explainability of AI and LLMs in critical applications
Engineering AI-based systems for human-AI collaboration and interaction
AI4SE and SE4AI
LLM-based Agents

Embodied Intelligence and Autonomous Intelligent Systems

Design and validation of autonomous systems, such as robotics and autonomous driving
Perception, decision-making, and planning modules in autonomous systems
Simulation-based testing and validation of autonomous systems
Robustness, fault tolerance, and safety challenges in autonomous operations
Interoperability and coordination between autonomous systems in distributed environments
AI and ML techniques for autonomous systems

Real-World Complex Systems

Modern Operating Systems
Ubiquitous computing, context awareness, sensor networks
Cyber-physical systems and Internet of Things (IoT)
Autonomous driving systems and robotic systems
Blockchain, protocols, smart contracts, and transactions
Industrial case studies

Different kinds of contributions are sought, including novel research, lessons learned, experience reports, and discussions of practical problems faced by industry and user domains. The ultimate goal is to build a rich and comprehensive conference program that can fit the interests and needs of different classes of attendees: professionals, researchers, managers, and students. A program goal is to organize several sessions that include both academic and industrial papers on a given topic and culminate panels to discuss relationships between industrial and academic research.