You may have noticed a couple of social media posts mentioning this Allevothon. This was an internal hackathon organized with our production teams and lead by a Dutch team of consultants, ICT Institute.
Our goal was to review the existing software development processes and find points where these can be improved to make our team work and deliver in a more agile way. We looked at processes, tools, stakeholders, links between teams, communication, a few historic bottlenecks and then created six mini teams that would gather and work to crack something they’ve had for a long time in their pipeline.
So, we had quite diverse teams:
- Daniel’s Team
- Dream Team
- Data Team
- Devops Team
- Team Fluffy
- Team Squike
The big project we are working on now is Whizzer, a project co-financed with a grant from Innovation Norway. As part of this grant, we have the privilege of working with a company based in Norway, Bakken and Baeck. A company with deep expertize in building algorithms and leveraging data Allevo automates as part of the Whizzer project. Because this is one of our first projects where our production teams work closely with an external team, we thought we’d run first this internal hackathon to prepare.
Here are the 6 mini-projects the teams worked on, in summary:
Mockaroo: Use mockaroo API for inserting random gen data in input boxes. Create a new repository with multiple test data examples that is useful for analysis, dev and test. Result: a demo app with input form, with random generated data inserted when an icon is clicked in the input box. This is useful for automation of tests ran on the features of Whizzer.
Altova MapForce: Automation of mappings based on XSDs, interface structure with BO and business rules. Result: A demo of Altova used on Allevo specific input and XSDs. This is specifically useful in accommodating a higher number of formats, such as bank statement formats, when implementing this functionality in Whizzer.
Test data for reports: Using toad options, generate test data for test reports and demos. Result: A structured set of test data (with description of what has been generated) and a script/demonstration that uses the data. Focusing on prospected customer requirements, this allows creating rich data that Whizzer can use to enable the algorithms built by Bakken & Baeck to learn and become better at predicting patterns.
Customer Data Collector: Tool that automatically collects anonymized data related to app configuration and processing of transactions. Data should be used to replicate/investigate an incident reported by customers on Allevo’s environment. Result: Demo of a script that collects anonymized data about app configuration. The idea is that the customer runs this script and the data is used in debug mode. This is useful for the runtime of Whizzer, in the future deployment setup.
Testlodge: Use a tool for creating or importing test scenarios that also offers the option to see the progress of test runs in real-time. Result: A real-time demo of a test run. Learning: this is not fit fot Allevo or the future setup of Whizzer, due to integration mechanisms with other tools used.
Automated unit testing: Use junit or cppunit for creating multiple unit tests on several important features and functions prone to bugs. Find a code coverage tool and apply to unit, component and integration tests. Result: Several interesting example unit tests and a script that automatically runs the tests. This is useful for regression testing in future developments of Whizzer.
The results of Allevothon are very useful for the future of the Whizzer project. Allevo now has a selection of tools and methodologies appropriate for use in the development lifecyle of Whizzer. These can be later used by the open source community.
One more thing Allevo plans to use is the experience of running this hackathon, the plan being to extend invitations for the next one to partners like Bakken & Baeck or a scientific community like Magurele Science Park.
Drop a note if you have suggestions for improvement and ideas for future hackathon events!
And a big set of congratulations to the amazing team at Allevo, who put such passion in coming up with results in a such short amount of time!