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Web Application

The Probato Web application is responsible for centralizing, organizing, and exposing the data collected during automated test executions.

It acts as an observability point for the automation process, enabling result analysis, historical tracking, and visualization of quality metrics.

Like the other components of the project, the Web application is an evolving proposal, open to adjustments as new needs emerge.

Web application objective

The main objective of the Web application is to address a recurring problem in test automation:

  • Results scattered across logs, isolated reports, or pipelines
  • Evidence that is difficult to locate
  • Limited visibility beyond the technical team

The application centralizes this information, making it accessible and understandable for different audiences.

Distribution and execution

The Web application is distributed as a Docker image, allowing execution in:

  • Local environments
  • Dedicated servers
  • Continuous integration environments (CI/CD)

This approach simplifies adoption and integration with different infrastructures.

Collected data

During test execution, the Web application can store information such as:

  • Project and test suite identification
  • Scenarios, preconditions, and postconditions
  • Executed steps and performed actions
  • Execution results
  • Evidence (screenshots and videos)
  • Test data used
  • Executed SQL scripts
  • Browsers, operating system, and screen resolution
  • Execution date, time, and duration

The set of stored data is not fixed and may evolve as new needs arise.

Visualization and analysis

Through the Web interface, it is possible to:

  • View individual executions
  • Browse test history
  • Analyze recurring failures
  • Access evidence associated with executions

The proposal is to facilitate technical investigations and stability analysis over time.

Metrics and indicators

The Web application allows visualization of quality metrics such as:

  • Success and failure rates
  • Stability trends over time
  • Failure frequency by scenario or feature
  • Impact of changes between versions

These metrics represent an initial model, open to evolution and community contribution.

Progressive usage

Although the application offers advanced features, its usage can be progressive:

  • Simple executions may generate only basic results
  • More mature environments can explore detailed metrics and history

This avoids unnecessary complexity in early stages.

Pipeline integration

The Web application does not replace CI/CD pipelines.

It acts as a complement, consolidating information generated by automated executions performed across different environments.

This integration enables continuous history and comparison between executions.

Target audience

The Web application serves different audiences:

  • Developers, for technical analysis
  • QA and Quality Engineering, for execution monitoring
  • Managers and stakeholders, for a consolidated view of quality

Each audience accesses the same data set, with different levels of interpretation.

Evolution and collaboration

The data model, metrics, and visualizations are not definitive.

The evolution of the Web application depends on:

  • Community feedback
  • New use cases
  • Discussions about metrics and indicators

Collaboration is essential to ensure the application remains useful across different contexts.

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