Lattix 2023.1
New Parasoft*, Improved MagicDraw* and Microsoft Project* Integrations and More in Lattix 2021
Lattix has packed this release with new modules, integrations, and enhancements to the Lattix Suite. Our focus on expanding our Solutions continues with the addition of Systems Engineering and Project Planning.
Check out the details below.
* Registered trademarks of Parasoft, Dassault Systems, and Microsoft Corporation, respectively.
Lattix 2021 adds support for the popular Parasoft C/C++ testing solution. The combined solution is:
- The best package to automate ISO 26262 compliance with the combination of architecture information, static analysis and dynamic test and coverage data
- Allows you to prioritize regression testing using Lattix impact analysis to run unit and integration tests most likely to be affected first. To find issues earlier
- Using Lattix Architectural metrics, you can improve your test coverage by identifying the most important files
Software delivery pipeline automation coupled with Lattix expert services provides embedded safety-critical software development organizations a stable, scalable, and comprehensive DevOps workflow. This collaboration seamlessly enables teams to manage software architecture, software quality, and drive testing to comply with safety-critical standards.
Heat Map
Aggregate code coverage, static analysis and architecture findings into one holistic view of code quality. See all the critical quality data through the perspective of the architecture in the HeatMap, which is automatically produced and presented in the Gitlab Merge Request. This enables critical decisions to be made regarding whether to merge defective code coming in from a feature branch.
Impact Analysis
Perform impact analysis on a defect, to see what files and packages are affected by a fault in the software.
Changed Based Testing
Perform Change Based Testing by analyzing the impact of code changes and re triggering only those unit and integration level tests affected by the changes.
Control and Data Coupling Analysis
Perform Control and Data Coupling Analysis using a unique approach combining architecture information from Lattix with dynamica test and coverage data from Parasoft C/C++ test.
Accessible from your browser, the extended team can view projects with snapshots of each build and compare trends of changes, architecture issues, metrics, and a variety of other data…without needing to learn how to use Lattix Architect.
With Lattix 2021, we have made substantial performance improvements to Lattix Web. We enhanced Lattix Web capabilities in handling projects with duplicate and merged atoms. Overall, these features will improve your experience with Lattix Web.
Lattix Web also includes the Heat Map so that users can see data from the Parasoft static analysis and testing mapped to the architecture for prioritizing remediation efforts.
A SysML model of architecture is commonly considered the core of most digital engineering transformations, and yet the power of a well-defined architecture is often not fully exploited. Analysis of architecture using design structure matrices (DSM) in the early phases can help visualize all of the relationships in your model, identify undesirable cycles, and quantify inter-component coupling and ideal component cohesion.
Compare As-Modeled to As-Implemented for Validation and Compliance
With the UML/SysML and software language analysis modules combined into one project, Lattix enables mapping of the code to the model and vice-versa to discover and control structural mismatches.
In this example, the tagged code and model elements are missing in the model or the implementation.
In Agile and DevOps environments, architectural analysis can be automated so that every time an architect checks in a new version of their model or a developer checks in new code, the results of the analysis are immediately available so that remediation can be made before becoming technical debt.
The challenge with conventional planning tools is the inability to deal with planned and unplanned iterations, which lead to delays and higher costs. DSM analysis enables optimal sequencing of activities which involve iterations, identifying opportunities to restructure processes to leverage planned cycles and minimize the impact unplanned rework.
