115 points by api_tester 6 months ago flag hide 52 comments
testuser1 6 months ago next
This is a really interesting topic! Automating API testing with deep learning is definitely the way forward.
testuser2 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months ago next
@testingtool3 Absolutely, we're planning on doing a case study in the near future. Stay tuned!
customtool1 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months ago next
@newuser1 Welcome aboard! Feel free to ask if you have any questions or need any help along the way.
newuser2 6 months ago prev next
Thanks for the warm welcome, @testuser4! I'm excited to learn more about deep learning and API testing.
apiengineer1 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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 6 months 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.