CRAgingReport - Maqsusi Digital Industries Software

Explore top Polarion custom use cases showcasing real-world business transformation and process innovation for customers.

By Maqsusi Digital Industries Software
For Siemens Polarion ALM.

The Change Request Aging Report is a dynamic and interactive report built within Polarion ALM, designed to analyze and visualize the age and status of change requests (CRs) across various projects or parameters. It leverages multiple Velocity scripts to aggregate, process, and display data efficiently within a single live report.
Each Velocity script block performs an independent function — querying data, processing it, and formatting it for visual presentation. These scripts utilize Polarion’s TrackerService and QueryService APIs to fetch live CR information directly from the repository.
Optimize queries to minimize processing time.
Use caching or shared variables for repeated data.
Maintain clear naming conventions in all Velocity variables.
Avoid heavy client-side rendering; balance between Velocity and JS logic.

The user opens the live report, triggering initialization of project context and Polarion APIs.
Velocity scripts execute queries via TrackerService, QueryService, and Transaction API.
Each .vm file retrieves Change Request data and applies filters (status, severity, date range, etc.).
Data is grouped, processed, and rendered dynamically using HTML tables and Highcharts visualizations.
The combined outputs form an interactive dashboard with drill-down links for detailed CR insights.

Provides a single-pane dashboard for complete Change Request tracking and analysis.
Enables quick identification of bottlenecks through aging, trend, and severity visualizations.
Interactive drill-down improves traceability and auditability of change workflows.
Facilitates data-driven decision-making for project managers and quality leads.
Reduces manual reporting effort by auto-generating visual metrics from live project data.

Add dynamic filters (date, status, owner) and export options (PDF/Excel) for custom analysis.
Integrate trend prediction using historical CR closure rates (machine learning integration).
Enable role-based dashboard views with configurable email or alert notifications.
Implement caching and REST-based data fetching for faster performance and scalability.
Extend multilingual, accessibility, and e-signature compliance for global usability.

Samples

Maqsusi Digital Industries Software

Kranthi Kumar

2506

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