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Rapid, using a range of connectors and accelerators to create models of fast-changing systems and auto-generate test cases from them.
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Rigorous, with powerful coverage algorithms to test complex systems exhaustively, or focus on new and critical functionality.
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Risk-based, leveraging test history and granular generation techniques to focus testing based on time and risk factors.
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Reactive to changing requirements, automatically maintaining test cases, data, and automated tests as the central models change.
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Collaborative, deriving tests directly from requirements models and user stories, keeping the business and IT aligned.
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Simple and easy-to-use, with intuitive BPMN-style modeling, a drag-and-drop approach, and a comprehensive range of accelerators.
8X Faster Test Creation At Eljin Productions
Learn How Models Drive Rigorous Testing at Eljin
Discover the benefits Eljin Productions achieved when using Test Modeller to successfully launch a business-critical payments platform using model-based test generation and synthetic test data generation.
Rigorously test complex systems within an iteration
Test Modeller quickly captures complex systems as easy-to-maintain flowchart models, automatically generating a rigorous set of test cases, data, and automated tests.
Automated Test Case Design
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Manual Test Case Design
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1. Agile Requirements Modelling: Existing test cases and user stories are automatically converted to accurate flowchart models, with full dependency mapping across components. |
1. User Stories Perpetuate Defects Fragmentary user stories and incomplete requirements are written in ambiguous natural language, without mapping between components. |
2. Optimised Test Cases Rigorously Test with Fewer Tests:
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2. Over-Testing Leaves the Majority of Systems Exposed: Testers slowly and manually convert user stories to low-coverage test cases that focus repeatedly on "happy path" scenarios. The majority of a complex system's logic is left exposed to defects that are detected late, at a greater cost to fix. |
3. End-to-End Test Automation: The same model can be used to generate the test data and automated tests needed to execute the optimised test cases, at the same time as they are created. |
3. Slow and Manual Test Execution: Test data must be manually found or made for each test case, while the tests are slowly converted into automated test scripts, or are executed manually. This is slow and resource-intensive. |
4. Teams and Information is Kept Aligned Across Delivery Pipelines: The VIP workflow engine populates existing ALM and project management tools with the optimised test artifacts, using high-performance Robotic Process Automation to keep information aligned across DevOps pipelines. |
4. Miscommunication and Poor Alignment of Tools and Teams: Test teams repetitively input the same test steps and test metadata into fields across the numerous tools in use at their organisation. Miscommunications arise and more time is spent on process than development. |
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