Auto-assignments of Jira issues using ML/Deep learning

It has been a while that i haven’t blogged, i was busy doing some stuffs and learning some new skills. So here i’am back with this short blog post and this time it’s about building an AI (Somme buzz word :p) and more precisely a Deep Learning Model for auto-assignments of Jira issues !

I will not cover ML/Deep Learning or AI here , it’s a very big topic. I just wanted to share some code sample using Python (Anaconda,Tensorflow,Sklearn,Keras/etc) that can be useful maybe for someone . The code example are not working as is , they have to be adjusted for specific needs (Example assigning a Ticket to a Team, Group(Custom fields) or a specific user/etc) . So it’s not just a click and run but some Engineering need to be done first.

The code sample is based on a bag-of-words approach for building and MLP Model. It also contain code snippet for Decision Tree, SVM and Naive Bayes Classifier.

Show me the code :

jira_model_classif_train.py : Building an MLP Model, the code also contain code sample for testing DescisionTree, SVM and Naive Bayes Classifier) . Grid Search is used for Model Tuning (HPO).

jira_model_classif_inference.py : Using the Build model for Auto-assignments of Issue , ( The changelog can also be used for more filtering, example excluding ticket already treated)

That’s it 😀 Have Fun !

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