Imagine you are developing a new product and you are in a crunch period
where every day and resource you have must be used wisely. You also
want to make sure the product is released with the highest quality and
defect free. Throughout the development, defects have found, but also
resolved. You do not have enough time or resources to do a full test
pass and need to choose your regression suite effectively. How do you
do this? What metrics are you using to determine where there is a
higher probability to find those last few remaining bugs? Hourglass Bug
Predictor is designed to not only aid in these types of scenarios, but
to address quality assessment throughout the development lifecycle. By
using Hourglass Bug Predictor, you can efficiently allocate time and QA
resources to the right areas of the product to test to ensure you are
cost-effective and maintain a high quality bar.
Hourglass Bug Predictor is a Command Line Tool that integrates with Jira
and uses Machine Learning to predict the future quality of your
products in development. It will predict how many bugs you should expect
in the next seven days, from the time the software is run. It will
query your Jira tracking system for Bugs under a specified Jira
“Project”. Based on the data it finds in your Jira Management System
(Atlassian), it will train a Machine Learning Model and the predict the
number of bugs you should expect to find in the following week of your
development. For example, it will tell you/predict that there will be 5
bugs in the next week or some other prediction value. The prediction
takes into account the fields of your Jira Bugs both for training as
well as prediction. The prediction feature vector also takes historical
timelines and grouping of your bug data and respective attributes.
An example output would be: Bug Prediction Count for next 7 days for
input parameters:0.5
