SOFTWARE RISK TAXONOMY CREATION BASED ON THE COMPREHENSIVE DEVELOPMENT PROCESSES
Software risks are always a crucially important topic for research because the software development process is quite expensive. The competition is high enough to ignore it. Although the "golden" era for startup projects is slowly ending, the latest achievements in generative AI show that n...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ivan Franko National University of Lviv
2024-09-01
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| Series: | Електроніка та інформаційні технології |
| Subjects: | |
| Online Access: | http://publications.lnu.edu.ua/collections/index.php/electronics/article/view/4470 |
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| Summary: | Software risks are always a crucially important topic for research because the software development process is quite expensive. The competition is high enough to ignore it. Although the "golden" era for startup projects is slowly ending, the latest achievements in generative AI show that now is the time to "take risks" and capture the software market using this technology. Therefore, it is necessary to analyse already known risks and identify new risks associated with business models and market conditions with generative AI capacity.
The article analyses the already existing taxonomies of software risks, their advantages and disadvantages, the software development life cycle stages, and risk management activities in the conditions of different software development models. Using the proposed taxonomy, the noticed activities and processes are linked in one taxonomy, which allows easy identification of risks based on known software requirements and vice versa.
The created taxonomy has been validated by some subject domain experts who work at big IT companies. ChatGPT4 is one of the experts counting on the LLM capability to resolve the summarisation and text classification tasks. The practical results of the risk taxonomy are crucially important because we avoid LLM hallucinations and enable a taxonomy-driven approach to prompt engineering for risk management. |
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| ISSN: | 2224-087X 2224-0888 |