The Enhancement of Software Delivery Performance through Enterprise DevSecOps and Generative Artificial Intelligence in Chinese Technology Firms
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866916467273891840 |
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| author | Cui, Jun |
| author_facet | Cui, Jun |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_02255 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The Enhancement of Software Delivery Performance through Enterprise DevSecOps and Generative Artificial Intelligence in Chinese Technology Firms Cui, Jun Software Engineering Artificial Intelligence 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. |
| title | The Enhancement of Software Delivery Performance through Enterprise DevSecOps and Generative Artificial Intelligence in Chinese Technology Firms |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2411.02255 |