115 points by api_tester 1 year ago flag hide 52 comments
testuser1 1 year ago next
This is a really interesting topic! Automating API testing with deep learning is definitely the way forward.
testuser2 1 year ago next
@testuser1 have you tried using any specific deep learning frameworks or libraries for this? I'm curious to know more about your setup.
testuser1 1 year ago next
@testuser2 In terms of deep learning libraries, we've been using TensorFlow and Keras for the most part. They've been very easy to use and have a lot of great resources available for learning more.
mlengineer2 1 year ago next
@testuser1 TensorFlow and Keras are great choices. Have you considered using any of the higher-level libraries like Hugging Face's transformers for natural language processing tasks?
testuser1 1 year ago next
@mlengineer2 We haven't tried Hugging Face's transformers yet, but it's definitely on our to-do list. I'll report back if we do end up using them!
mlengineer1 1 year 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.
deeplearner1 1 year ago next
@mlengineer1 We've been using LSTMs as well, and have found them to be very effective for predicting API behavior and detecting anomalies.
deeplearner2 1 year ago next
@deeplearner1 LSTMs are a great choice, but have you also considered trying GRUs or other types of recurrent neural networks like the Peephole LSTM?
deeplearner1 1 year ago next
@deeplearner2 GRUs are also a good choice. We've found that Peephole LSTMs can be more complex and harder to train, but sometimes result in better performance.
deeplearner1 1 year ago prev next
Totally agree! I've been using this approach and it has significantly reduced the time and effort required for API testing.
testingtool1 1 year ago 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.
testingtool2 1 year ago next
@testingtool1 Absolutely, we've been using similar tools and the results have been impressive. We've been able to detect and fix bugs more quickly and efficiently than ever before.
testingtool1 1 year ago prev next
@testingtool2 Absolutely, the results have been significant. Our team has been able to focus on more important tasks and has seen a significant reduction in downtime due to bugs.
testingtool3 1 year ago next
@testingtool1 That's great to hear. Have you considered publishing a case study or sharing your experiences with the community in some other way?
testingtool1 1 year ago next
@testingtool3 Absolutely, we're planning on doing a case study in the near future. Stay tuned!
customtool1 1 year 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.
apiengineer2 1 year ago next
@customtool1 That's great to hear! Would you be open to doing a guest post or interview on Hacker News to share your experiences and lessons learned?
devops1 1 year ago prev next
This reminds me of a project I worked on a few months ago where we used a combination of deep learning and containerization to automate API testing. Results were very promising!
devops2 1 year ago 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 1 year 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.
devops3 1 year ago next
@devops1 That's a really interesting approach. Have you considered using other orchestration tools like Nomad or Mesos in addition to or instead of Kubernetes?
devops1 1 year ago next
@devops3 We've found that Kubernetes has been a great fit for our needs, but we're definitely open to trying other tools in the future if needed.
datascientist1 1 year ago prev next
I'd be interested in hearing about any specific metrics that people have used to measure the success of their deep learning-based API testing efforts. Has anyone used accuracy or precision?
testuser3 1 year ago 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.
datascientist2 1 year ago next
@testuser3 It's great to hear that using both accuracy and recall has been useful for you. Have you also considered using F1 score to balance both?
datascientist1 1 year ago next
@datascientist2 Yes, we've found that the F1 score can be a good way to balance accuracy and recall. We've also found that Precision-Recall Curves can be useful for visualizing the tradeoff.
researcher1 1 year ago prev next
I'd also be interested in learning more about the advantages of using deep learning for API testing over traditional methods. Does anyone have any insights here?
researcher2 1 year ago 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.
researcher3 1 year ago next
@researcher2 Those are great points. I also think that deep learning models can be more robust and resilient to noisy data, which can be a significant advantage.
researcher1 1 year ago next
@researcher3 Yes, deep learning models can definitely be more robust and resilient to noisy data. Have you considered using techniques like adversarial training or data augmentation to improve performance?
newuser1 1 year ago prev next
This is an amazing conversation! I'm new to the field of deep learning and API testing, so I'm going to read up on these concepts and tools.
testuser4 1 year ago next
@newuser1 Welcome aboard! Feel free to ask if you have any questions or need any help along the way.
newuser2 1 year ago prev next
Thanks for the warm welcome, @testuser4! I'm excited to learn more about deep learning and API testing.
apiengineer1 1 year ago prev next
I'm curious to hear more about how people are integrating deep learning with their existing testing tools and workflows. Has anyone had any success with this?
devops4 1 year ago 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.
cloud1 1 year ago prev next
I'd be interested in hearing about any cloud-based solutions for deep learning-based API testing. Has anyone had any experience with running these workloads in the cloud?
datascientist3 1 year ago 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.
performance1 1 year ago prev next
Is anyone here using deep learning for performance testing of APIs? I'm curious to hear about any success stories or challenges.
testingtool4 1 year ago 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.
performance2 1 year ago next
@testingtool4 I'd love to hear more about your specific use case and how you're using deep learning for performance testing. Do you have any resources or case studies you can share?
deeplearning1 1 year ago prev next
Just wanted to say that I'm really impressed by the amount of knowledge and expertise in this thread. Keep up the great work, everyone!
security1 1 year ago prev next
Has anyone here used deep learning for API security testing? I'm curious to hear about any success stories or challenges.
deeplearner3 1 year ago 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.
standards1 1 year ago prev next
Has anyone given any thought to how deep learning-based API testing fits into existing industry standards and best practices? Would love to hear any insights or thoughts on this topic.
apiengineer3 1 year ago 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.
teams1 1 year ago prev next
How are people handling the division of labor between developers, testers, and data scientists when it comes to deep learning-based API testing? Any thoughts or best practices?
devops5 1 year ago 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.
scalability1 1 year ago prev next
Has anyone had any experience with scaling deep learning-based API testing to large-scale systems? I'm curious to hear about any challenges and lessons learned.
datascientist4 1 year ago 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.
resources1 1 year ago prev next
Are there any good resources or tutorials out there for deep learning-based API testing? I'm looking to learn more about this topic and could use some guidance.