During the course of this project students will realize a practical assignment beginning with a coarse-grained requirements definition culminating in a final prototypical realization. The exact definition of your project assignment will be done together with your advisor and depends on the chosen topic, the topic's complexity, and the size of your team (if you are working in one).

After a positive attendance of the course, students are able to

• implement and execute short programs,
• translate programming tasks given in natural language into excecutable source code,
• apply practices and use tools for the implementation of programs,
• implement described algorithms.

• Introduction, Basics, Overview
• Data Models, Database Systems, Data Independence
• The Relational Model (Basics, Design)
• Relational Query Languages
• Relational Algebra
• SQL
• Conceptual Modelling
• UML2
• Object Diagram
• Class Diagram
• Dependency Theory and Relational Design Theory (Dependencies, Normal Forms)

• Number representation
• floating point arithmetic
• Basic concepts of information and coding theory
• logic in computer science
• Propositional logic, Boolean algebra, minimization methods
• Predicate logic as a specification language
• Finite automata, including Moore and Mealy automata
• Regular expressions and context-free grammars
  
• combinational circuits 
• Realizations of automata
  
• Petri nets

This course discusses in detail all phases of modern software development for large systems, including requirements elicitaton, design, implementation and validation. Specifically, the course covers:

• Modern software development models;
• Functional and non-functional requirements and their elicitation;
• Modeling and specification of software systems;
• System implementation aspects, such as design patterns, delta debugging, CI/CD, and code reviews;
• Software validation techniques, such as structural, functional, system, and user-acceptance testing.

Reliability issues in modern software often result in significant financial losses or system downtime, thereby affecting millions of users. This course discusses in detail fundamental techniques for ensuring the reliability of large, complex software systems. Such techniques are heavily used in practice and range from static program analysis and verification to automated test generation. The course, in particular, focuses on applications of these techniques to different, popular domains, such as smart contracts and machine-learning models.

In the course, the fundamental aspects of the following topics, among others, will be discussed:

- Introduction to the engineering of mobile applications
- Introduction to the security mechanisms of mobile operating systems
- Reverse engineering of applications
- Static and dynamic analysis of applications
- Analysis of network traffic
- Detection of vulnerabilities.

• Basics and definitions.

• Information systems, their applications, and their architecture

• The role of conceptual modeling in the (model-driven) engineering of information systems

• Conceptual domain model versus conceptual database model.

• Ontology-guided creation of conceptual models

• Stepwise transformation of conceptual domain models, via conceptual information (systems) models, towards implementation platforms, such as relational database management systems, business rule engines, ERP systems, and low-code platforms.

Working on a larger project from conception to practical implementation, individually or in a group. Students improve their communication and presentation skills. They learn to develop new methods based on familiar ones and to assess the consequences of professional decisions.

During the course of this project students will realize a practical assignment beginning with a coarse-grained requirements definition culminating in a final prototypical realization. The exact definition of your project assignment will be done together with your advisor and depends on the chosen topic, the topic's complexity, and the size of your team (if you are working in one).