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For the highest software quality & efficient releases
Quality Assurance & Software Testing
No digital project without Quality Assurance! Systematic Software Testing ist quite literally the quality gate for your e-commerce applications and IT processes. With our QA services, we bring speed, efficiency and predictability to release management – data-driven, automated and AI-supported.
Avoid mistakes & reduce costs: That's why Quality Assurance & Software Testing!
Quality assurance in software projects is an integral part of a holistic development approach and continuous optimization. Quality assurance encompasses all measures that ensure that your digital applications function technically flawlessly and fulfill key quality features.
Software quality assurance focuses on four core requirements:
Smooth functionality
Performance & velocity
User friendliness (usability)
Standard conformity & compatibility
The rule of ten for error costs
With each development stage, the costs of an undetected error increase by a factor of 10, meaning that the later a software error is detected, the more expensive it will be for you to rectify it.
Head of AI, QA & DevOps, valantic
Without QA testing, errors in the code or individual functions can remain undetected. If these are not noticed during the development process, the costs for rectifying errors increase by a factor of 10 with each development stage - also known as the rule of ten for error costs.
Michael Blum
From Software Testing to advantage
How Quality Assurance generates business value
Systematic QA testing is a prerequisite for the success of your software projects – with far-reaching effects and benefits for your business processes:
Reduce costs
Proactive software testing avoids error costs, reduces optimization and maintenance costs in the long term and thus keeps the total cost of ownership (TCO) low.
Increase efficiency
Automated QA tests reduce manual effort, eliminate inefficiencies in the test process and support effective release management.
Increase operational safety
QA ensures the stability, availability and functionality of your applications. Avoid performance bottlenecks, critical restrictions or even system failures!
Accelerate releases
A forward-looking test strategy brings predictability, reliability and speed to the development process. The result: adherence to deadlines right up to go-live and a short time to market.
Improve usability
QA testing ensures that your software, systems and services meet user expectations, function error-free and are reliably available – even when accessed simultaneously.
Data-based optimization
Holistically integrated QA strategies promote a culture of continuous improvement based on quantifiable KPIs and metrics. QA monitoring provides real-time insights for data-based decisions.
Secure competitive advantages
Smooth processes and user-friendliness determine clicks, conversions and therefore your turnover. Those who meet rising customer expectations can exploit competitive advantages.
Adhere to compliance
In addition to technical quality standards, compliance QA also takes into account legal regulations (e.g. GDPR and EAA) in order to avoid reputational damage and legal risks.
Strengthen brand
High-quality products and services are cornerstones for a reputable image, credibility and your reputation. Strengthen trust in your brand for lasting customer loyalty!
Quality Assurance with AI How AI optimizes software tests
No longer an insider tip for data-driven, automated software testing: Artificial intelligence (AI) significantly increases the effectiveness and efficiency of quality assurance. From test planning and test management to the prediction of vulnerabilities and intelligent QA reporting – this is how AI supports software testing:
Generative test case creation
Automatic creation and continuous updating of test cases from user stories, real usage scenarios and historical data - including conversion into automated test sequences with GenAI
Predictive risk scoring
Machine learning models for identifying high-risk changes and potential vulnerabilities - for proactive error prevention even before the test or production phase
Automatic error detection
Real-time monitoring of KPIs and behavioral deviations in test and production environments - to detect anomalies, defects and process errors that can be overlooked in traditional methods
AI-supported test optimization
Intelligent prioritization of relevant tests based on change histories, risk forecasts and past results - for efficient test execution and error prevention in QA workflows
Data-driven QA workflows
Automated evaluation of test results, metrics and reports - including data-based optimization suggestions for test strategy, coverage and continuous quality improvement
Unsure how to automate your QA processes with AI and make them measurably more efficient?
Tip: AI Workflow Bot for intelligent process management
An AI agent that networks teams, data and processes company-wide, makes knowledge accessible in natural language and automates recurring tasks: That’s the valantic AI Workflow Bot!
More about the AI Workflow Bot in the blog
More about the AI Workflow Bot in the blog
Building blocks of quality assurance
What does Software Testing involve?
All software quality assurance measures start with a clear test strategy. This usually follows the structure of a pyramid with five test levels.
By monitoring central KPIs and performance metrics, we ensure that your tests run smoothly at all development stages and that all software components ultimately function as defined.
The classic test levels of holistic QA:
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1
Static code analysis
Static code analyses detect errors, security vulnerabilities and potential problems in the code during development before it is executed.
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2
Unit tests & integration tests
Unit and integration tests focus on individual components (units) of the code to ensure that they function correctly. Unit tests should be carried out repeatedly during development.
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3
(Automated) E2E tests
For end-to-end tests, valantic’s comprehensive QA expertise comes into play: We check your application or IT systems holistically for functionality, configuration and freedom from errors – partially or fully automated, depending on the requirements and test type.
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4
Load & performance testing
In load and performance tests, we test your software or the overall architecture in various stress and load situations to uncover load limits and possible bottlenecks, e.g. in the event of many simultaneous accesses and traffic peaks.
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5
Manual & explorative tests
In manual and explorative software tests, we analyze the real user experience and focus on aspects that cannot be tested automatically or only to a limited extent, e.g. usability and accessibility.
Case studies, checklists, content highlights
Know-how & best practices for Quality Assurance
Blog
One chat, all answers: How the AI Workflow Bot connects knowledge & processes
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Blog
Performance Check: Quality assurance for long-term composable commerce success
Success stories
ESA improves its online store with automated E2E tests
QA checklist for Composable Commerce
Test management for consistently high performance
FAQ: Frequently asked questions about Quality Assurance & Software Testing
Quality assurance is always required when the functionality, performance and stability of software need to be ensured – in other words, in the development of every application and in all processes that are crucial to your business success. More specifically, software tests are recommended for quality assurance:
- before software releases and updates to avoid errors, inconsistencies and malfunctions
- for complex systems or integrations where many components interact with each other
- in agile software projects, development environments and test processes
- for security-critical, business-relevant or data-intensive applications (e.g. e-commerce, financial sector, healthcare industry)
- for system scaling and a growing number of users to ensure stability and performance
- for performance optimization measures
High release quality is ensured through systematic testing in the development process. Following on from this, ongoing QA testing enables data-based optimization and contributes to the continuous improvement of software quality.
QA measures have a direct and indirect impact on software quality because they:
- reduce the likelihood of undetected errors, bugs or other limitations
- minimize the risk of performance bottlenecks, data loss, inconsistencies, malfunctions or system failures
- ensure that the software meets key quality standards (e.g. functionality, user-friendliness, compatibility)
- ensure system and data security through enhanced security mechanisms
- ensure that both the application and the development process comply with applicable compliance guidelines
- rationalize development and release cycles through the implementation of CI/CD principles
- provide planning security for releases and rapid market launch
Test coverage can be improved through a dedicated test process and automation for recurring and critical scenarios, among other things. In addition, risk assessments and test data analyses help to regularly check all relevant functionalities and identify gaps at an early stage.
Quality Assurance? Absolutely!
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