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Our Success Stories

I already know Qualicen from their early years. Thanks to our close strategic cooperation, our Daimler analysis pipeline is now also included in Qualicen Scout. As a result, we were able to replace our proprietary solution with Qualicen Scout. Our specification authors use Qualicen's automatic analysis to review our requirement documents and thus benefit directly from the further developments of Qualicen Scout.

Dr. Frank Houdek Research and Development, Manager Teststrategie & Requirements Validation @ Mercedes Benz AG

Our Success Stories

Qualicen was and is an extremely reliable partner for us, delivering outstanding results. Working together, we successfully implemented pragmatic and effective requirements engineering. We developed training courses jointly with Qualicen, which were so well received that we rolled them out across three continents with great impact.

Dr. Christian von Holst Global Tractor Systems Engineering Lead @ John Deere

Our Success Stories

Qualicen helped us to bring more content-related exchange into our requirements engineering and business analysis community. With the help of their exciting lectures and interactive training courses Qualicen made our requirements engineering more effective and efficient.

Dr. Claudia Schindler Lead Business Analysis Community & Senior Solution Architect @ Munich RE

Our Success Stories

Qualicen excellently combines deep knowledge in the field of software development methods with novel processes and tools. Their special focus is on text analysis, which - as Qualicen impressively demonstrates - can be successfully used in many software engineering areas, for example as a support in creating and checking documents, for quality controls in requirements engineering as well as in test design.

Prof. Dr. Dr. h.c. Manfred Broy President of Centre for the Digitalization of Bavaria (ZD.B), Co-founder of Qualicen GmbH

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Courses

Scientifically grounded and at the same time fun and focussed on value. We receive this feedback from our clients concerning our courses. Would you also like to refresh your knowledge?

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Quality assurance rules

Drawing on insights from practice and academia, we have developed a multitude of rules and methods for optimal quality assurance of both requirements and test cases. Do you also want to improve your RE and test case quality? We are looking forward to help you!

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Test cases controlled 24/7

We are continously checking about 54,000 test cases from 63 projects and counting.

What’s going on at Qualicen?

MethOps, marrying Methodology and IT-Operations.

Dear friends and family, we are gathered today to witness and celebrate the union of MBSE-Methodology and IT-Operations in marriage....
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MethOps, marrying  Methodology and IT-Operations.

Into NLP 5 ~ Numerous Language Parts – POS Tagging

Last time we had a look at the task of text normalization as a way of simplifying matching and searching...
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Into NLP 5 ~ Numerous Language Parts – POS Tagging

Qualicen Snapshot – Edition 1/2021 [in German]

Liebe Freunde und Freundinnen, liebe Partner*innen von Qualicen, es ist soweit: die zweite Ausgabe unseres Snapshots - die erste im Jahr...
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Qualicen Snapshot – Edition 1/2021 [in German]

Mature Enough? Using Maturity Models to Assess and Improve Software Projects

It is not rare that projects approach us not as a consultant firm but more like a medical first-aid station....
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Into NLP 4 ~ Normal Language Perfection – Text Normalization

In my last article I talked about the benefits of tokenization regarding text processing: Essentially when we want to make...
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Into NLP 4 ~ Normal Language Perfection – Text Normalization

How to Reuse Test Steps and Test Cases in Azure DevOps

Do you know how many times you changed a test case in Azure DevOps and did not know that there...
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How to Reuse Test Steps and Test Cases in Azure DevOps

Into NLP 3 ~ Numerous Language Pieces – Tokenization

Previously we started our journey into the world of Natural Language Processing by learning the basics of Regular Expressions (RegEx)...
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Into NLP 2 – Fuzzy String Matching and the Edit Distance

NearLy Perfect In my last article I started with a dive into the wonderfull world of Regular Expressions. We’ve seen...
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Into NLP 2 – Fuzzy String Matching and the Edit Distance

Estimating is a risky business.

Hey! How long is it gonna take… You know what, I'm not even gonna finish that sentence. It is a...
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Estimating is a risky business.

Into NLP 1 – Regular Expressions

Into the Fire - A no less somewhat less nonsense introduction to NLP Natural Language Processing? - What is NLP?...
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Into NLP 1 – Regular Expressions

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