Tutorial on
The Web API Lifecycle: Requirements Analysis, Testing, and Application Integration — A Case Study of AI Services APIs.
Instructors
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Martin Zimmermann
University of Applied Sciences and Arts Lucerne
Switzerland
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Short Bio
Martin Zimmermann served as the Vice Director of the newly established Department of Computer Science at the Lucerne University of Applied Sciences and Arts. From 1994 to 1998, he worked as a researcher at IBM European Networking Center and Deutsche Bank Group. Between 1998 and 2001, he held a professorship at the University of Applied Sciences Rapperswil in Switzerland. Zimmermann obtained an M.S. (Diplom) from the Karlsruhe Institute of Technology (KIT) and a Ph.D. from J.W. Goethe University Frankfurt in 1996. He has authored over 50 publications, including contributions to international book chapters, journals, and conference proceedings. His work has earned him several best paper awards, particularly for his contributions to visual programming and context-based mobile applications. His research interests encompass mobile devices, the development of cross-platform mobile applications, and visual programming, with a particular emphasis on user-centered, context-based solutions. A significant portion of his work focuses on enhancing the understanding, design, development, and performance of context-aware applications based on Web APIs.
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Gilbert Seilheime
Offenburg University of Applied Sciences
Germany
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Short Bio
Gilbert Seilheimer is the owner of the CONTIC agency and works as a research assistant at Offenburg University of Applied Sciences. As Business Service Owner in Campus IT, he is responsible for IT workstations and also manages the faculty's laboratory and IT systems at the Gengenbach campus. He teaches IT Fundamentals and Mobile Commerce and works as a self-employed web developer, specialising in HTML5, e-commerce and e-business solutions for prototypes and online platforms. His further areas of interest include augmented reality, the Internet of Things, artificial intelligence and smart factory technologies for mobile devices.
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Christian Merschroth
Offenburg University of Applied Sciences
Germany
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Short Bio
Christian Merschroth, M.Eng., works as an academic staff member and technical laboratory manager for Information Systems at Offenburg University of Applied Sciences. His work includes IT services, laboratory environments and the practical use of software, business information systems and data technologies in teaching. He has co-authored work on context-aware mobile services and contributes practical experience in the integration and operation of application environments.
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Abstract
Web Application Programming Interfaces (Web APIs) are the building blocks that enable rapid assembly of data and functionality across applications by eliminating the necessity to redevelop common functionalities from the ground up. The AI era has amplified their importance, providing access to text generation, speech and vision processing, etc. through scalable APIs.
This tutorial offers a concise, hands-on exploration of Web APIs with a dedicated focus on AI services. Attendees will learn how to discover providers, evaluate capabilities and costs, choose the right API for a given use case, and implement robust integration patterns. A practical case study will demonstrate end-to-end Web AI API selection and integration in both traditional web and mobile (including low-code) contexts. The session combines short theory segments with hands-on activities and a capstone prototype that demonstrates end-to-end API selection, integration, and monitoring.
Keywords
Web APIs, AI services, API Marketplace, Web API evaluation, Web API integration
Aims and Learning Objectives
- Map the Web API landscape: Generalist marketplaces vs. specialized providers, with a dedicated lens on AI services (e.g., NLP, generation, and speech).
- Learn evaluation criteria for Web APIs, including capabilities, latency, reliability, pricing, and data privacy considerations.
- Create a structured Web API selection workflow, and compare multiple providers for the same task (e.g., sentiment analysis, image captioning).
- Implement a practical AI-enabled prototype using multiple AI APIs, leveraging both traditional web apps and low-code environments.
This tutorial will provide an in-depth examination of Web API provides, with a dedicated lens on AI services. Additionally, participants will learn best practices for developing applications using Web APIs, including practical tips for building effective applications.
Target Audience
Researchers, practitioners
Prerequisite Knowledge of Audience
Basic programming experience (preferably in Python or JavaScript) and familiarity with REST/HTTP.
Optional: Basic exposure to cloud services, and Web API testing tools.
Detailed Outline
The tutorial is divided into four parts and will cover the following topics:
Part 1: Exploring Web API Providers Through Concrete Examples (AI services focus):
We will examine various Web API providers and specific examples of their APIs to gain a deeper understanding of their functionalities and typical use cases. Representative examples: a mix of marketplace APIs and specialized AI endpoints (e.g., chat/generation, sentiment analysis, image analysis, audio transcription).
Part 2: Evaluation and Selection of Web API Providers and AI APIs:
We will explore methods and criteria for assessing Web API providers and their APIs, developing tailored recommendations for selecting the most appropriate Web APIs for specific scenarios. We will focus on JSON (JavaScript Object Notation), the most widely used data format for Web APIs, with an emphasis on visualizing JSON data effectively.
Part 3: Integrating Web APIs into Applications :
We will also examine AI-assisted software development for Web API integration. Using explicit project context and API specifications, participants will use an AI coding assistant to generate and refine client code, JSON payloads and schemas, validation logic, error handling, and tests.
Part 4: Apply concepts in a realistic AI-focused case study (Practical Exercises):
In the practical part, we will collaboratively build a minimal prototype that combines multiple AI APIs , including both simple web applications and mobile applications developed using low-code environments.
Tutorial on
Collaborative Model-Driven Quantum Software Engineering: A Hands-On Tutorial with Qonstruct
Instructor
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Lavinia Stiliadou
University of Stuttgart, Institute of Architecture of Application Systems
Germany
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Short Bio
Lavinia Stiliadou is a research associate at the Institute of Architecture of Application Systems at the University of Stuttgart. She received her master's degree in computer science in 2023. Her research focuses on quantum software engineering.
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Abstract
Quantum software engineering remains a challenging discipline due to the interdisciplinary expertise required to design, implement, and deploy hybrid quantum-classical applications. Developers must navigate concepts from quantum computing, software architecture, cloud computing, and distributed systems while simultaneously addressing hardware heterogeneity and rapidly evolving execution platforms. Although low-code and visual development approaches have emerged to reduce this complexity, existing solutions are often restricted to specific domains such as quantum machine learning, remain tightly coupled to circuit-level modeling, or rely on proprietary ecosystems that limit extensibility and collaboration.
This tutorial introduces Qonstruct, an open-source platform for collaborative model-driven quantum software engineering. Qonstruct enables developers to model quantum applications using high-level domain abstractions rather than low-level quantum circuits, allowing them to focus on application logic instead of hardware-specific implementation details. Through model-driven transformations, visual specifications are automatically translated into standard-compliant quantum representations and executable orchestration workflows that support validation, deployment, and execution across heterogeneous quantum computers.
Keywords
Low-Code, Model-Driven Engineering, Quantum Computing
Aims and Learning Objectives
By completing this hands-on session, attendees will gain foundational knowledge on:
- Core fundamentals governing practical quantum software engineering.
- Building abstract quantum domain models visually using high-level low-code blocks.
- Automatically compiling visual artifacts into valid, standard-compliant OpenQASM intermediate representations or even quantum workflows.
- Orchestrating, deploying, and tracking compiled quantum job packages.
Target Audience
This session provides a practical roadmap for software engineers, systems designers, and cloud architects looking to acquire fundamental literacy in modeling, building, compiling, and deploying quantum software.
Prerequisite Knowledge of Audience
Attendees of this tutorial do not require a deep prerequisite background in quantum physics, advanced quantum mechanics, or low-level circuit hardware configurations.
Detailed Outline
20 min - Opening & Quantum Computing Software Fundamentals
30 min - Low-Code & Model-Driven Design & Navigating the Quantum Low-Code Modeler
40 min - Practical Session I: Collaborative Model-Driven Design & Execution
30 min - Coffee Break & Networking
45 min - Practical Session II: Algorithm Selection and Model Generation
15 min - Open Discussion, Evaluation & Q/A