2. Highlights in MES Quality Commander® (MQC)

2.1. MES Quality Commander® (MQC) v.6.2

New Distribution Visualization including Milestones and Overall Quality/Availability

The new distribution visualization now shows the milestones as vertical lines. This eases the temporal recognition of the quality or availability distribution over time.

All revisions before a milestone can be collapsed. The new distribution visualization then shows the last revision before that milestone. Collapsing revisions provides a streamlined trend (quality or availability) especially for long running projects with many revisions.

With the improved distribution visualization it is possible to switch between a bin view, which shows the distribution of e.g. the computed quality according to categories like “good,” “acceptable,” and “bad” per revision, and an overall quality or availability view per revision.

As part of the bin view, the new distribution visualization shows the overall quality or availability as an additional trend line.

The new quality distribution visualization reflects the current scope of quality assessment, which can be absolute, available or relative quality. By default the absolute quality is shown.

The reimplementation of the bin distribution visualization facilitates improved formatting of labels, axes, and more consistent marking and tooltips.

For more information refer to section Distribution Charts.

Automatic Data Update of Projects on MQC Server

MQC projects stored within the library of an MQC Server can be periodically updated to automatically fetch the latest data changes. This ensures that all projects are always up to date upon opening, without the need to run an import in the client.

The serverside automatic update can be enabled or disabled in the project without changing any configuration in the server.

Serverside updates are only executed if new or changed data was detected.

For more information refer to section Settings.

2.2. Highlights History

2.2.1. MES Quality Commander® (MQC) v.6.1

Artifacts and Quality in flexible structures

Typical development projects are often structured in various ways, i.e. by product architectures, by product platforms, even by roles and responsibilities. As a result, the artifact and quality model structures in MQC now support multiple flexible levels and freely configurable naming.

Appropriate filtering and marking now allow you to focus on many specific aspects of artifacts or quality properties, in addition to a general overview.

For more information refer to section Quality Model Configuration and Project Structure Configuration.

Selectable scope for visual quality assessment

The scope of quality assessment that is shown in different visualizations includes all quality properties by default (=absolute quality). However, it is now possible to adjust that scope by e.g. ignoring all missing quality properties (=available quality) or by adapting the assessment in relation to defined target values (=relative quality). This allows a more differentiated view on project quality at any time during project runtime.

For more information refer to subsection Quality pages.

Faster Data Import from Git

Now faster data import works for Git repositories as well. MQC detects new commits and imports only data contained in these commits. New data can therefore be imported into an existing project much faster.

In case some hidden changes were made in your Git repository, you can force refresh reading the data from the Git repository (which may take quite some time).

Use of commit time as report time is now a configuration of the Git data source, which can be found inside the data source configuration dialog.

Predefined User Roles on MQC Server

The MQC server solution automatically comes with two user groups: MQC Editor and MQC User.

MQC Editors are able to create and configure (new) MQC projects and MQC Users are able to load and view existing projects, but not create or edit them.

For more information refer to section Server.

2.2.2. MES Quality Commander® (MQC) v.6.0

Multiple Quality Models

Your overall quality model can be configured out of multiple (smaller) quality models. This improves the handling, maintenance, and especially the extension of the quality model definition.

We recommend defining each data source in its own quality model. The quality models we provide with MQC follow this recommendation.

Even if there is no quality model defined, MQC recognizes the data sources used and loads the provided initial quality models.

For more information refer to section Quality Model Configuration.

Faster File Import and Transformations

Now MQC detects new data files and imports only the new data. In this way, importing new data into an already existing project happens much faster.

The time needed for calculations and transformation of the data is now reduced by half. This was achieved through improvements in the data flow and reducing the internal memory consumption.

As a result of the improved data handling MQC is more responsive and gives you more intermediate status updates of running calculations.

The adapter framework is faster now and was modified to reduce complexity. The GUI now focuses on showing only the standard adapters by default. However, the full set of adapters is still available with MQC.

Project Creation with Complete Configuration

We added an advanced mode to project creation, in which all necessary configurations for your project i.e. Project Structure, Quality Models, Settings, Adapters, etc. can be configured before creating the project. This facilitates a fast and comprehensive setup process.

For more information refer to section Creating an MQC project.

2.2.3. MES Quality Commander® (MQC) v.5.3

New Project Creation with Interactive Configuration

MQC streamlined the new project creation. When you select “Create new project” a dialog asks for the location of your data (source) and the revision granularity. After confirming the dialog the project will be set up.

With the new dialog less steps are needed to set up your project and you can provide data earlier. The overall setup process is quicker, because you can import your data directly during the setup.

Multiple Git Repositories as one Data Source

If you have a high number of similar Git repositories containing your data, you can now configure these as one data source.

One Git configuration (branches, commits, time range, etc.) can be used for a list of Git repositories with a similar structure (e.g. when each artifact is contained in its own repository).

This considerably reduces the configuration effort for Git data sources.

For detailed information refer to section Git.

Direct Access to MQC Showcase

The MQC Showcase project is now shipped with MQC and can be accessed with one click from the landing page in the web player or the client.

The MQC Showcase is a ready to use MQC project where you get the full MQC experience and try out the features for yourself.

For more information refer to section Quick Start Guide.

2.2.4. MES Quality Commander® (MQC) v.5.2

Visualization and Aggregation by Artifact Structure Levels

To get a better overview of larger projects (hundreds of artifacts) the visualized elements can be switched from artifacts to higher levels of the artifact structure (i.e. StructureElement, StructureGroup, and StructureRoot). Instead of showing hundreds of artifacts, switching to higher levels of the artifact structure improves the visualization, so that you can recognize the StructureElements or the StructureGroups. At the same time this higher level visualization directly shows the aggregation of the respective qualitative values of the StructureElements or the StructureGroups. Together with a well-defined artifact structure you get a comprehensive view of your project on the different levels answering questions like what is the quality of this component or this ECU. At the same time you can see the elements in comparison to each of the other elements on the same level.

This structural level visualization works on all quality pages and the data availability page for artifact structure, quality model structure, and data structure. You can select a level in the hierarchy of the structure, defined by the Project Structure or the Quality Model, in the dropdown above the respective KPI visualization.

Different main visualizations (status matrix, heat map, and trend chart) respect the structural level selection in the KPIs and show the same aggregated view.

If you are on one of the higher structural levels you can expand/collapse the underlying elements to see more details. The selection ‘Groups - Artifacts’ shows groups in the KPI, which you can expand down to the artifact level. The main visualization on the right-hand side shows the artifact level. This allows you to quickly and easily mark the higher structural levels while viewing the detailed level on the main visualization.

Sorting and search in visualization

Sorting and searching were added to the KPI visualizations for Artifacts, Quality Properties, and Measures.

Now you can sort these KPIs using a dropdown. Different sorting options are quality ascending/descending, name ascending/descending, availability ascending/descending, and propagation ascending/descending.

Use the search function to reduce the amount of tiles shown and to display the relevant tiles.

Improvements for Annotations

Annotations are more prominently displayed in the main visualization on the Quality Status page. An “A”-Indicator highlights annotated quality points. The Tooltip for an annotated quality point shows the title, description, and the change of quality, if defined.

The Annotation UI dialog was further improved and streamlined. In addition to the grouped viewing mode, a flat viewing mode was added to meet different preferences. Now it is possible to see a list of all the annotations.

The Import and Export features were replaced by a more advanced toolbar. With this new toolbar it is possible to load, reload and save from/to the file system or a network drive. The Load dialog supports either the loading of a file (while keeping a reference to the data) or the uploading of a file, which allows the use of local files on the web player. Saving replaces a referenced file, saves as a new file or downloads as a file. All these allow web player users to save the file locally.

Adding a new annotation comes with more preselected fields based on the current marking, either in the artifact KPI, quality properties KPI, bin distribution or the main visualization. Additionally to quality properties and artifacts, the quality, bins, and revision start and end dates will be prefilled now.

It is now possible to define annotations without a change of quality or bin target, so that you can only enter a comment.

The transformations for annotations have been improved. When adding, modifying or deleting annotations only the necessary transformations will run, significantly reducing the execution time.

For more information refer to section Annotation Configuration.

Tool Adapter for RTRT HTML Report and RTRT Quality Model

The HTML report of Rational Test RealTime (RTRT) by IBM is supported. Together with the QAC adapter, MQC supports code based projects now.

The adapter reads the test case status and the available code coverage metrics.

The RTRT quality model contains all the read measures and quality properties for code coverage and test case compliance.

For more information refer to section Rational Test RealTime (RTRT).

2.2.5. MES Quality Commander® (MQC) v.5.1

Annotations for Quality Properties (Beta)

MQC added the possibility to adapt quality values in a direct and documented way. These annotations adapt quality property values per artifact.

Annotations can change the quality bin (i.e. from bad to acceptable) or the quality value directly (i.e. from 74% to 93%).

A user interface aides the creation and update of single or multiple annotations.

Each annotation contains a title (short) and a description (long) to document the reasons for the change in quality. It also contains the author of the annotation, the creation date, and the (last) modification date.

The validity of an annotation can be defined for a specific time frame (by date).

For more information refer to section Annotation Configuration.

Multiple Human Readable Reports per Data File

The connection between data source files (i.e. XML files) and accompanying human readable reports (i.e. HTML files) was extended to handle multiple human readable reports per data source file. For example, in this way the adapters support separate MiL and SiL HTML reports for one XML file containing combined test results for MiL and SiL.

For more information refer to section Data Origins.

Extension of TPT Adapter

The TPT tool adapter for the TPT HTML overview report supports handling multiple variants of the overall result visualization.

For more information refer to section PikeTec TPT.

Propagated Derived Measures

Derived measures that use propagated base measures are propagated now as well. This makes the information in the Data Availability more consistent.

For more information regarding propagation refer to section Data Propagation.

2.2.6. MES Quality Commander® (MQC) v.5.0

Git as Source for Data (Beta)

MQC can use Git as a direct source for data files. By configuring the Git server, user, and repository now all commits are available as a source for data files.

Filters are available for commits, tags, author, directories, and files. These filters can be include or exclude. Simple text pattern up to full regular expressions can be used for defining the filters.

An option in settings allows the user to use the commit date and time of data files instead of the date inside the report file. The report date and time is set as default.

Employing the current functionality all data files can be directly taken from the version control system. In addition, the analysis by MQC can be constrained to a defined set of commits, directories, files depending on the project and what is needed.

MQC detects updates in the Git repository. The user is notified to refresh the data. If configured, the refresh happens automatically.

For more information refer to section Git.

Calculation and Visualization of Quality Differences

MQC now directly calculates and visualizes the changes/differences in quality and availability between revisions. The comparison base can be selected and separate Diff pages are available to visualize quality and availability changes/differences.

Diffs can be calculated in comparison to the previous revision or previous milestone. It is also possible to compare all revisions with a specific revision.

Separate Diff pages are available with difference specific visualization adaptions. These pages use percentage points to make the kind of changes clear. There is differentiation between positive (+) and negative (-) changes/differences. The titles of the visualizations describe the nature of the visualized data.

A Diff page is shown for a specific page (e.g. Quality Status page), when choosing “Show Diff View” in the Action Panel. Diff pages can also be managed via the “Manage Pages” menu.

The difference calculations and visualizations depend on the filter panel selection.

For more information refer to section Quality Diff and Availability Diff.

Quality Bin Configuration

The quality bins used on quality pages of MQC can be configured by name, color, and the used quality boundaries/thresholds. The number of bins is flexible. In this way a project might use specific names instead of good/acceptable/bad and the respective colors green/yellow/red.

An optional new sheet to define the parameters of bins is available in the Quality Model configuration. These parameters are used throughout all quality pages. The previously used configuration is still the default configuration in MQC.

For more information refer to section Quality Model and Quality Bin Configuration.

2.2.7. MES Quality Commander® (MQC) v.4.5

Configurable Dashboard

The dashboard can be used to get a quick project overview. Configurable tiles show you exactly the information you need for a first yet thorough impression. Tiles can be added removed, resized, and moved around using drag and drop.

The configuration of the dashboard is saved as part of the project.

For more information refer to section Dashboard Customization.

Fuzzy Rules for Action Calculation

The calculation of action priorities depending on quality properties can now be done with the help of fuzzy rules. This provides flexibility in defining more complex non-linear relations between actions and quality properties. The fuzzy rules are implemented by the Fuzzy markup Language (FML) ISO standard.

The definition of linear dependencies in the quality model and the fuzzy definition can be used at the same time and can even be mixed.

For more information see section Definition of Actions.

A Sankey diagram on the Action List page shows the dependencies between quality properties and derived actions (see Action List Page).

Additional/extended Tool Adapters

  • Tool adapter for TPT XML report and TPT Quality Model extended

  • Tool adapter for Simulink Check (Model Advisor) HTML report added

  • Tool adapter for Simulink Design Verifier HTML report added

For more information refer to chapter Data Source Adapters.

2.2.8. MES Quality Commander® (MQC) v.4.4

Action List (Beta)

MQC now recommends actions to improve quality by solving deficits in a project. Each action is related to a particular artifact with a priority from ‘Very High’ to ‘Very Low’ according to the corresponding quality value. The list of actions is then sorted according to the priorities, which helps the user to easily identify the most urgent actions to be taken next.

A new Action List page is provided which gives an overview about the actions for the current or a selected revision. Filtering and marking may be used to focus on details like particular artifacts.

For more information refer to chapter Actions.

Data Origins (Imported Data and Report Files)

MQC provides access to human-readable reports, for example in HTML or PDF format, if available. The underlying data reports, whether originally imported and/or human-readable, can be opened directly through MQC.

Using the new entry Show Data Origin in the MQC Action panel, makes it easy to crosscheck the original file source for a particular piece of data.

For more information refer to chapter Data Origins.

2.2.9. MES Quality Commander® (MQC) v.4.3

Tool Adapter API to Allow Custom Adapter Implementation

Tool Adapters can be added when working with MQC using the new API. In this way the import capabilities of MQC can be easily extended.

Adapters can be written in C# and (Iron)Python.

Examples for adapters reading XML, HTML, Excel, and CSV/TXT are available including all currently available tool adapters.

For more information refer to chapter Custom Adapters.

Tool Adapters for MXSuite, CTC++, and QAC Added

Code coverage data from CTC++ can be imported from XML and HTML reports. In addition to the code coverage data (statement/decision/… coverage) the number of source lines and measurement points are read as well.

Static analysis data from QAC can be imported from XML and HTML reports.

Test result data from MXSuite can be imported using MXSuite XML reports.

For more information refer to chapter Data Sources.

Significant Performance Improvement of Data Transformation Flow

The data transformations are now executed in a specific order, which is controlled and triggered in such a way as to prevent duplicate transformations. This improvement reduces the time needed for the transformations by up to half.

2.2.10. MES Quality Commander® (MQC) v.4.2

Significant Import Time and Memory Reduction for Huge Data

The import of huge sets of data files and complete directories of files is much faster now. In addition, the memory consumption was reduced considerably.

The mechanism of monitoring for file and directory changes was reworked to detect changes safe and with less computing resources. Due to the adapted caching mechanism the reimport of changed files is much faster now as well.

User Experience

The marking in the bin distribution is more intuitive now. Revisions on status pages can be selected with just one click. Similarly, a quality bin on trend pages can be selected for all revisions with one click.

The extension of marking when combining marking on bin distribution and in KPIs is more intuitive now.

The showing of the KPIs and the calculations inside the KPIs are fully dynamic now and reflect the marking on the other visualization of the page.

Artifact and revision marking on quality or data pages is directly reflected on other quality and data pages.

A full description of these mechanisms can be found in Marking.

Availability of MQC Server and MQC Web Viewer/Editor

The MQC Server is now available for on-premise installation and setup. Now you can have a secure library of your analysis including access to your local network (and data).

With this availability of the internal library you can easily create a shared analysis (and some tasks can run regularly on the server, i.e. to update an analysis with new data)

Together with the MQC Server, the MQC Web Viewer/Editor is now available. It provides the functionality of the client directly in a browser while the analysis is opened/running on the MQC Server.

2.2.11. MES Quality Commander® (MQC) v.4.1

Improved Configuration Dialogs

MQC settings dialogs have been redesigned for better usability, and are available in MQC editor as well as MQC web viewer.

For more information refer to chapter Menu with Actions and Configuration.

Fine grained configuration of Context Categories

Context categories define the relations between artifacts and data sources, measurements, and base measures. They help to define and focus on the artifact-relevant data from the available data pool.

For more information refer to chapter Context Categories.

2.2.12. MES Quality Commander® (MQC) v.4.0

Report generation project status

The new status report in html format documents all details of an MQC project, including graphics and context-specific tables to structure the information. The structure and extent of the report is configurable.

For more information refer to chapter Status Report.

Configure expected data via context categories

Improved tool adapter for Polyspace (The Mathworks)

For more information refer to section MathWorks Polyspace.

Extended tool adapter for TPT (Piketec)

For more information refer to section PikeTec TPT.

2.2.13. MES Quality Commander® (MQC) v.3.5

From quality to data details

Via the context menu, selected quality properties or artifacts link to detailed data specific to the selection.

For more information refer to section Data Details Drill Down.

Introducing artifact weights for quality aggregation

The artifact weights, as well as the weights for quality values can be visualized in a hierarchical heat map, where the impact of an artifact and a quality value scales with the size of a colored tile.

For more information refer to section Artifact Weights.

Additional tool pages for MES M-XRAY and MES Test Manager

2.2.14. MES Quality Commander® (MQC) v.3.4

Target value configuration for measures and quality properties

For each measure or quality property one or multiple target values (thresholds, expectations) can be defined per project milestone.

For more information refer to chapter Target Values.

Introducing quality property weights for quality aggregation

For each quality property a weight can be defined to be used in the aggregation of quality properties to sub-characteristics in the structure of the quality model.

For more information refer to chapter Quality Property Weights.

Tool adapter for Polyspace (The Mathworks)