Standalone Application
1. Overview:
The goal is to compare and evaluate how well various versions of the mo-validation-core Library perform based on that It can be improved with the release of new versions of the library.
2. Description:
We give the terms validate, context, and both with the aid of three scenarios. The context feature in validate is always zero regardless of the main feature, the context feature in context is always one regardless of the main feature, and In both the number of contexts and the number of main features are proportional. In order to determine how much the current version has improved over the previous one, We compute the time of the new version of the mo-validation-core Library for each scenario with unique input and compare it to the previous version. For storing output we create a CSV file in which we store the input data with their required respective execution time. Below is an example of all three scenarios with sample input data.
3. Flow Diagram
On Git lab whenever a new version of the mo-validation-core Library is released, then the Validationassets-performance-client will trigger, and the pipeline is created This causes the pipeline to run all scenarios and produce an output CSV file in which we store the input data along with the corresponding execution times.
4. Performance Table
5. Performance Graph
Similarly for contextLoader Library we did the same thing
1. Overview:
By comparing and analysing the execution time for various versions of the library and then optimising the code that is affecting the performance of the library, the objective is to increase the performance of the context-loader library.
2. Description:
To analyse the performance of a library with different feature types(Topology, Address, etc), we take features having Low, Medium, and High dense context around them (a chart is shown below to summarise the output context for each).
Then trigger the context-loader performance client with every new release of the context-loader library and invoke the library with 500,1000,2000,3000 features for L, M, and H dense context.
To determine how much the current version has improved over the previous one, We compute the time of the new version of the mo-validation-core Library for each scenario with unique input and compare it to the previous version. For storing output we create a CSV file in which we store the input data with their required respective execution time
