标题： 量化是决定性因素吗？ 来自大型代码模型的实证见解 显示英文标题

标题： Is Quantization a Deal-breaker? Empirical Insights from Large Code Models

摘要： 随着大型语言模型（LLMs）规模的不断扩大，不仅需要大量的计算资源，还由于其不断增加的碳足迹而引发了环境问题。模型量化作为一种有效的方法，可以在不显著影响性能的情况下减少LLMs的资源需求（例如，从16位降至4位）。尽管最近的研究已经将量化确立为优化大型代码模型（LCMs）的一种有前景的方法，LCMs是专为自动化软件工程设计的LLM的一个子集，但它们的发现仅提供了有限的实际意义见解。具体来说，当前的研究仅关注量化模型生成的代码的功能正确性，忽略了量化如何影响代码质量的关键方面，如可靠性、可维护性和安全性。为了弥补这一差距，我们的研究调查了量化对自动生成代码定性方面的影响。我们将感知激活的权重量化（AWQ）应用于两个广泛使用的代码模型CodeLlama和DeepSeekCoder，以生成Java和Python代码。使用最先进的静态分析工具，我们评估了软件质量指标和静态特征，包括循环复杂度、认知复杂度和代码行数。我们的研究结果表明，量化是一种稳健的技术，不仅保持了功能正确性，还保留了开发者所追求的关键定性代码属性，如可维护性和结构简单性。 显示英文摘要

摘要： The growing scale of large language models (LLMs) not only demands extensive computational resources but also raises environmental concerns due to their increasing carbon footprint. Model quantization emerges as an effective approach that can reduce the resource demands of LLMs by decreasing parameter precision without substantially affecting performance (e.g., 16 bit to 4 bit). While recent studies have established quantization as a promising approach for optimizing large code models (LCMs), a specialized subset of LLMs tailored for automated software engineering, their findings offer only limited insights into its practical implications. Specifically, current investigations focus only on the functional correctness of the code generated by quantized models, neglecting how quantization impacts critical aspects of code quality such as reliability, maintainability, and security. To bridge this gap, our study investigates the effects of quantization on the qualitative aspects of automatically generated code. We apply Activation-aware Weight Quantization (AWQ) to two widely used code models, CodeLlama and DeepSeekCoder, to generate Java and Python code. Using state-of-the-art static analysis tools, we evaluate software quality metrics and static features including cyclomatic complexity, cognitive complexity, and lines of code. Our findings reveal that quantization is a robust technique that not only preserves functional correctness, but also retains key qualitative code attributes sought after by developers, such as maintainability and structural simplicity.