将DevSecOps与生成式AI结合，显著提升软件交付效率与安全性
The Enhancement of Software Delivery Performance through Enterprise DevSecOps and Generative Artificial Intelligence in Chinese Technology Firms
- 融合DevSecOps与生成式AI，实现编码自动化与安全嵌入
- 研发效率提升，代码管理更优，软件质量与安全水平显著提高
- 适合关注软件交付优化的技术企业与DevOps实践者
本研究探讨了在科技企业中集成DevSecOps与生成式人工智能（GAI）对软件交付绩效的影响。采用定性研究方法，通过半结构化访谈和案例分析，考察了成功实施该模式的企业。研究发现，研发效率显著提升，源代码管理得到改善，软件质量和安全性明显增强。GAI实现了编码任务的自动化与预测分析，而DevSecOps确保安全措施贯穿开发全流程。尽管结果积极，但受限于样本量小和研究的定性性质，结论的普适性存在局限。本文为DevSecOps与GAI的实际应用提供了宝贵见解，凸显其在变革软件交付流程中的潜力。未来研究可开展量化评估，比较不同行业的实施效果。
原文摘要 · Abstract (English)
This study investigates the impact of integrating DevSecOps and Generative Artificial Intelligence (GAI) on software delivery performance within technology firms. Utilizing a qualitative research methodology, the research involved semi-structured interviews with industry practitioners and analysis of case studies from organizations that have successfully implemented these methodologies. The findings reveal significant enhancements in research and development (R&D) efficiency, improved source code management, and heightened software quality and security. The integration of GAI facilitated automation of coding tasks and predictive analytics, while DevSecOps ensured that security measures were embedded throughout the development lifecycle. Despite the promising results, the study identifies gaps related to the generalizability of the findings due to the limited sample size and the qualitative nature of the research. This paper contributes valuable insights into the practical implementation of DevSecOps and GAI, highlighting their potential to transform software delivery processes in technology firms. Future research directions include quantitative assessments of the impact on specific business outcomes and comparative studies across different industries.
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