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Why systematic quality engineering is crucial for industrial software projects
Reliable software is not a matter of chance. It is the result of a consistent approach to quality that is embedded in development processes right from the start. Quality engineering encompasses all measures designed to ensure that software products meet the defined requirements, operate stably and can be developed reliably throughout their entire life cycle.
ITQ supports companies in the mechanical and plant engineering sector in systematically integrating quality assurance into their software development processes. This begins with the structuring of requirements and test cases, extends to the selection of suitable test environments and tools, and continues through to the automation of tests and integration with CI/CD pipelines. The aim is to achieve reproducible, scalable software quality, not just at the end of a project, but continuously throughout the entire development process.
Quality engineering poses a particular challenge in industrial software development: software and hardware are closely interlinked, test environments must be capable of simulating machine behaviour, and faults that are only discovered on the actual machine result in considerable time and cost overruns. ITQ possesses the necessary expertise in control software, embedded systems and agile development processes to implement quality assurance effectively at all levels.
Modern quality engineering approaches combine manual and automated testing, structured test case management, simulation and virtual commissioning to form an integrated quality system. Through continuous integration and automated reporting, software quality becomes transparent, measurable and can be assured on an ongoing basis.
Your benefits at a glance:
- A transparent and measurable overview of software quality
- Early detection of errors through automated testing at all stages of development
- Reduced testing effort on the actual machine
- A clear and documented test case structure
- Shorter feedback cycles through continuous integration
- Consistent software quality, even with frequent changes and enhancements
- Systematic validation of refactoring and software optimisations
Finding the right solution together
Your personal contact for software engineering will be happy to advise you on your specific enquiry.
Get in touch now for a no-obligation consultation.
Kilian Messmer
ITQ Branch Manager, North Rhine-Westphalia
„The automation of regression tests is the foundation for reliable further development. Only when every change is automatically tested can a team deliver quickly and reliably.“
Quality engineering does not happen at the end – it must be ensured right from the start
In many companies, quality assurance in software projects is carried out at a late stage and is often unsystematic. Tests are carried out manually, are incomplete or are poorly documented. Errors are frequently only discovered once the system is running on the actual machine or during commissioning. This results in a considerable investment of time and money in analysis, correction and rework.
At the same time, the complexity and pace of change in industrial software projects are increasing. Control software, embedded systems and networked components must work together reliably. Without structured quality assurance, there is a growing risk that changes will cause unintended side effects and that system stability will suffer in the long term.
This is where systematic quality engineering comes into play: test cases are recorded in a structured manner, distributed across appropriate test levels and gradually automated. Simulations and virtual commissioning enable early-stage testing without the need for physical hardware. CI/CD mechanisms ensure that every change is automatically tested – and that quality is not left to chance.
Systematically embed quality assurance
Typical challenges within a company:
- Manual, incomplete or undocumented tests
- Errors are only detected on the actual machine
- Lack of test automation and CI/CD integration
- Unclear testing responsibilities and a lack of test case structure
- Significant regression testing effort required for changes and enhancements
- Quality engineering of the highest standard
Services relating to quality engineering and test automation
An overview of our services
- Analysis of existing testing activities, testing gaps and quality processes
- Introduction of structured testing methods and test case management
- Development of unit, integration and system tests for control and embedded software
- Setting up test environments, simulations and virtual commissioning set-ups
- Integration of test processes into CI/CD pipelines and automated reporting
Technological expertise
- Test automation for PLC, embedded and networked software systems
- Unit and integration tests in accordance with IEC 61131-3 and C/C++
- Simulation environments and virtual commissioning (VIBN)
- CI/CD integration: Jenkins, GitLab CI, Azure DevOps and similar platforms
- Software quality analysis: ISO 25010, TIOBE metrics and code review processes
- Test management tools and structured test case documentation
- From analysis to recommendation
Procedure for implementing Quality Engineering
Project phases
Analysis of testing activities
Definition of the test concept
Setting up test environments
Introduction to test automation
Continuous quality measurement
Quality Engineering in Practice
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Further ITQ solutions
The services described form part of ITQ’s comprehensive service portfolio. ITQ combines technological expertise, a methodical approach and a deep understanding of processes to deliver sustainable solutions throughout the entire life cycle.
- Questions / Answers
FAQs – Quality Engineering
What is meant by ‘quality engineering’ in software development?
Why are manual tests not sufficient in industrial software projects?
Manual testing is time-consuming, prone to errors and cannot be repeated consistently when changes are made frequently. Automated testing provides rapid feedback on every change and ensures software quality in the long term, even as complexity increases.