VSEST 29110 Tool: Using ChatGPT to Evaluate the Implementation of the ISO/IEC 29110 Work Products
The global software industry is predominantly composed of micro, small, and medium-sized enterprises (MSMEs), highlighting the need for software quality management to ensure the proper functioning and quality of the software. This research focuses on the evaluation of the implementation of the ISO/I...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10646341/ |
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| Summary: | The global software industry is predominantly composed of micro, small, and medium-sized enterprises (MSMEs), highlighting the need for software quality management to ensure the proper functioning and quality of the software. This research focuses on the evaluation of the implementation of the ISO/IEC 29110 standard work products, which is a standard tailored by the ISO/IEC specifically for MSMEs, which improves the software development process by implementing two processes in its basic profile: Project Management (PM) and Software Implementation (SI). Despite this standard being tailored specifically for this type of enterprise, implementing ISO/IEC 29110 faces several challenges, such as a lack of knowledge and difficulties in adequately implementing the work products regarding the compliance of standard criteria, among others. To address these challenges, we introduce VSEST 29110, a web tool designed to evaluate the ISO/IEC 29110 standard implementation work products by leveraging Artificial Intelligence (AI) technologies, specifically the ChatGPT model, provide detailed feedback on compliance with standard criteria, offer suggestions for improvement based on ChatGPT analysis and streamline the implementation process for MSMEs. To achieve this, our research incorporates a systematic literature review and validation through a case study by document analysis, demonstrating VSEST 29110’s effectiveness in enhancing compliance and providing comprehensive feedback compared to auditor recommendations, which impacts 69.33% on average. |
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| ISSN: | 2169-3536 |