PyCharm Experts in Germany

AI Readiness - Part 3: Creating an e-book on the use of AI in software testing

• Designed and created an e-book on the sensible and safe use of AI in software testing from the perspective of an experienced test expert.
• Used generative AI (ChatGPT, Perplexity Pro) as a sparring partner for structuring, wording suggestions and creating variations, with all content finally reviewed and approved using my own expertise.
• Developed practical insights into the opportunities and risks of AI in testing, with a special focus on collaboration between testers and AI instead of “tester vs. AI”.
• Title: “11 starke Gründe: Dream-Team statt Rivalen - Tester und KI sind gemeinsam unschlagbar”
• Subtitle: “Wie Mensch und Maschine im Softwaretest das perfekte Team bilden – und warum reines KI-Testing riskant ist.”
• Planned use of the e-book as a basis for workshops, customer meetings or internal training.
• Technology: Generative AI, ChatGPT, Perplexity Pro, Microsoft Word, Adobe Acrobat, many years of hands-on professional testing experience, common sense.

Project: Defect Generation on Test-Bench Images of Metal Surfaces Environment: Automated Visual Inspection (AVI), Metallurgy & Manufacturing

• Objective & Implementation: Designed, architected, and trained Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g., cracks, inclusions, scale) on rough metal surfaces under real test-bench lighting conditions for privacy-compliant and efficient dataset expansion (data augmentation).
• Technical Design: Implemented robust Generative AI and computer vision pipelines in Python and PyTorch. Used semantic segmentation approaches for mask-controlled defect synthesis and subsequent evaluation with EfficientDet object detection models.
• Business Impact: Massive dataset upscaling (10x) without time-consuming and costly physical test-bench runs, while significantly improving the detection performance of automated inspection systems.

Technologies & Skills Used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision

• Implementation of a full-stack application with Angular as frontend framework and Java as backend language
• Use of the Swagger OpenAPI specification for REST communication between frontend and backend applications
• Control of a card printer via the Nexus Card SDK framework
• Design and implementation of card management software with web interface and JavaFX module for printer monitoring
• Use of Cucumber tests for test automation and creation of test artifacts for testing outside the development environment
• Use of Wireshark for network investigations to analyze the API of a third-party product and to check the REST API of the self-developed software

• Portfolio development & customer acquisition
• Portfolio development (RAG, NLP fine-tuning, process automation with n8n) and active customer acquisition
• Positioning: GDPR-compliant, locally hosted AI solutions for SMEs

• Developing a model-based AI where natural language is interpreted as formal relations.
• Natural language terms are not considered rigid but fluid and can be negotiated in a context so meaning resolves by iteratively specifying.
• Develops all kinds of model solutions.
• Backed by natural language and data annotation.
• Requirements to code and other solutions.

• Adding/creating test specifications
• Performing regression tests
• Performing release tests
• Analyzing Jira tickets
• Identifying software defects and fixing them with C#

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

• Designing the audit logging framework
• Implementing APIs for developers to integrate in their codebase
• Implementing ingestion pipeline, database query layer and UI for browsing the audit events
• Improving stability and reliability of the backend system

• Developed a React and TypeScript dashboard with reusable UI components and API-driven data visualization.
• Implemented dynamic data rendering, state management, and performance-focused frontend architecture.
• Integrated Python-based backend services for processing and visualizing SEO analytics.

Creation of workflows for generating the data basis for the article import of a web shop: combining data from several sources, analyzing the requirements, designing the process with Jupyter Notebooks and Knime. Also creating code for automation in Python using Polars and Pandas.

Processing the source data, filtering and merging the source files and creating the needed intermediate products, creating the upload files, plausibility checks, quality checks.

Technologies used: PyCharm, Python, Jupyter Notebooks, SQL, Knime. Pandas, Polars

• AI-assisted creation of test cases and test data
• Creation of test cases based on requirements
• Execution of manual tests
• Defect documentation, retesting and tracking

Technologies & Tools: SCRUM, Jira, Confluence, Zephyr Scale

• Fixing issues in the program logic

• Covering the changes with unit tests

• Analyzing and documenting the data structure of the various applications

• Analyzing and documenting the parameters for configuring the applications

• Analyzing and documenting the measures required to ensure the operation of the applications

• Analyzing and designing the separation of the individual database structures

• Analyzing and estimating the effort for planned extensions

• Analyzing, maintaining and documenting a heterogeneous legacy system landscape for a print media service provider

• Technology: C#, VB.NET, C, Python, Microsoft SQL Server, Visual Studio 2010, JetBrains Rider, Visual Studio Code, arc42, Draw.io, Jira, GitLab

• Automation of the database major / minor releases for the TKeasy project

• Concept for database major / minor release automation

• Assessment of the current state

• Evaluation of Redgate Flyway functionalities

• Concept development

• Products: Redgate Flyway, GitHub, Quest, Erwin Data Modeller, Oracle, Atlassian Jira, Atlassian Confluence

• Knowledge: Docker, Continuous Delivery, Continuous Integration, Redgate Flyway, Major Releases, Minor Releases

• Conducted research and development in the field of large-scale 3D reconstruction