Test Trend Weekly
The Test trend weekly dataset provides a detailed weekly summary of testing activities and outcomes. This dataset is crucial for monitoring the progress and effectiveness of testing efforts, identifying trends, and making informed decisions to enhance software quality. It encompasses key metrics such as the number of tests executed, passed, failed, and skipped, along with defect detection rates and resolution times. By providing a thorough and timely snapshot of testing trends, this dataset aids teams in ensuring consistent and reliable test coverage while maintaining high standards of software quality.
The following are the components of this dataset:
| Attribute Name | Description |
|---|---|
| Calendar date | Gregorian calendar date displayed in the format ‘M/D/YYYY’ |
| Calendar week | Gregorian calendar week displaying the week number. For example, |
| W21, W22. | |
| Iteration end date | End date of the iteration |
| Iteration start date | Start date of the iteration |
| Lagging count of weeks | Count of defects for the current week and the preceding two |
| Last refresh date | Date of the most recent update or refresh of data in a dataset. It is in date format. |
| Planning level end date | End date of the planning level |
| Planning level start date | Start date of the planning level |
| Sys_source | Unique identifier for the source |
| Test | Name of the test |
| Test planning level | Planning level of the test |
| Test status source | Status of the test source |
| Work item | Unique identifier for the work item |
| Work item backlog group | Backlog group of the work item |
| Work item iteration | Iteration of the work item |
| Work item portfolio item | Portfolio item of the work item |
| Work item team | Team of the work item |
| Work item type | Type of the work item |