Code Generation and Optimization

Aims

Code Generation and Optimization (CGO) provides a unique international forum for researchers, practitioners, and developers working on code generation, and on optimization of the code and its performance. CGO covers wide range of methods, from static to dynamic methods, and from pure-software methods to architectural specific solutions. By publishing quality refereed papers on the applications of code generation and optimization, CGO provides a vibrant link between the practitioners and developers in the industry, and the research community.  CGO welcomes original research articles, review papers, case studies, tool demonstrations, and industrial practice reports. The journal encourages interdisciplinary research and places particular emphasis on innovative applications of code generation and optimization in emerging fields. Our goal is to provide a high-quality, open, and collaborative platform for researchers to share their work and drive the frontier of this domain.

Scope

1. Code Generation
• Automated code generation techniques and tools;
• Domain-specific language (DSL) code generation;
• Intermediate representation (IR) design and optimization;
• Compiler code generation techniques and algorithms;
• Just-in-time (JIT) compilation and dynamic code generation;
• Code generation for multi-target architectures.

2. Code Optimization
• Static and dynamic code optimization techniques;
• Parallel and distributed code optimization;
• Compiler optimization algorithms and frameworks;
• Performance analysis and optimization;
• Energy efficiency and green computing;
• Machine learning-driven code optimization.

3. Programming Languages and Compilers
• Programming language design and implementation;
• Compiler front-end and back-end optimization;
• Novel compiler architectures and technologies;
• Automated toolchains and compiler infrastructure;
• Compiler techniques for emerging hardware.

4. Program Analysis and Transformation
• Program analysis techniques and tools;
• Automated program transformation and refactoring;
• Static and dynamic program analysis;
• Abstract interpretation and formal methods;
• Program synthesis and automated programming.

5. Performance Engineering
• Code optimization in high-performance computing
• Code optimization for embedded and real-time systems
• Code optimization for heterogeneous computing and accelerators (e.g., GPUs, FPGAs)
• Performance optimization for big data and AI applications

6. Interdisciplinary Applications and Emerging Fields
• Code generation and optimization in quantum computing
• Automated code generation and optimization in machine learning
• Code optimization for security and privacy preservation
• Code generation and optimization in industrial automation and the Internet of Things (IoT)