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Automated risk identification using NLP in cloud based development environments | SpringerLink
Source: link.springer.com
Article summary:
1. Automated risk identification is essential to ensure privacy, security and quality aspects of software in cloud environments.
2. Natural Language Processing techniques such as LSI and deep learning can be used to automate the risk identification process.
3. Existing frameworks for risk assessment are not comprehensive and need to be improved with automated vulnerability check and evaluation systems for continuous integration of new deployments.
Article analysis:
The article provides a comprehensive overview of the current state of automated risk identification using NLP in cloud based development environments, discussing existing tools, frameworks, and approaches that have been used in the past. The article is well-researched, citing multiple sources from reputable journals and organizations such as IEEE, ISO/Guide 73:2009, ETSI 2015, etc., which adds credibility to its claims.
However, there are some potential biases present in the article that should be noted. For example, the article does not explore any counterarguments or alternative approaches to automated risk identification other than those discussed in the paper itself. Additionally, while the article does mention potential risks associated with automated risk identification processes (such as errors due to manual analysis), it does not provide any evidence or data to support these claims. Furthermore, while the article does discuss existing tools and frameworks for risk assessment, it does not provide any detailed information about how these tools work or how they could be improved upon.
In conclusion, while this article provides a comprehensive overview of automated risk identification using NLP in cloud based development environments, there are some potential biases present that should be noted when evaluating its trustworthiness and reliability.