Being a tester solving real time problems during project execution is always a challenge. It always gives me immense pleasure to create solutions for such challenges and move on to next challenge. While working with my colleague for a document scaling solution
over SharePoint ...a question always frustrated me...how to test document scaling? Immediately 2 things came to my mind....it has to be either Manual/Automated.
Problem Statement: To test document scaling solution which extracts entities from the document by using Pingar API it stores data in metadata properties of Sharepoint and as well as in
document related columns.
Luckily i had the complete list of terms which are expected to be extracted out of any document. This solved a big task of grilling down towards NLP.
Creating documents manually is some boring task for everyone out there and i know though you may nod your head...deep down documentation makes you sick.
Here is a small utility code i came up , it extracts the list of available entities from any XML (Generic structure) and outputs documents with test data in different file formats. Right now it only supports
PDF, DOC, DOCX, TXT, RTF.
The output document contains some randomly generated alphabets along with the XML entities popping up between frequently. Since same XML entities are repeated randomly, I could also test the ranking feature without any worries. Document DOES NOT contain
garbage text & special characters.
You never know how such small utilities can be helpful and re-usable. In the era of Social networking where people
spend most of the time either with collaboration tools (like SharePoint) or Personal Information Management Tools (like Outlook). SharePoint is widely used as a collaboration and document management tool in enterprise. With tools like Attini, even social
network (blogs, news, quick updates) has become a part of SharePoint infrastructure.
Check the FAQ's document for more clarifications.
Any Bugs are most welcome...i would love to solve bugs too rather than just finding one.
I would like to thank my colleague Akhilesh for helping me in finding bugs at starting stages.