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Advanced Software Engineering

Module name (EN):
Name of module in study programme. It should be precise and clear.
Advanced Software Engineering
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Computer Science, Master, regulation 01.10.2018
Module code: DFI-ASE
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2PA (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
6
Semester: 2
Mandatory course: yes
Language of instruction:
German
Assessment:
Oral examination, 30 minutes (50%)
 
Project work (50%) with:
Presentation: 40 minutes
Term paper: 20–30 DIN-A4-pages

[updated 25.08.2026]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

DFI-ASE Computer Science, Master, regulation 01.10.2018 , semester 2, mandatory course
PIM-ASE Applied Informatics, Master, regulation 01.10.2026 , semester 2, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 180 hours (equivalent to 6 ECTS credits).
There are therefore 135 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr.-Ing. Martin Burger
Lecturer: Prof. Dr.-Ing. Martin Burger

[updated 04.05.2026]
Learning outcomes:
- Students will approach software development as an empirical process, using iterative experimentation and feedback loops to validate hypotheses and minimize risks in complex, dynamic environments.
 
- They will analyze value streams in software development to maximize throughput and eliminate wait times by reducing batch sizes and limiting parallel work.
 
- They will design software architectures and deployment mechanisms that decouple deployment from release, ensuring that changes can be reliably deployed to production at any time.
 
- Students will evaluate the systemic interactions between organizational structure, software architecture, and development processes to identify bottlenecks in the overall system.
 
- They will derive quality and business-related metrics to objectively measure the effectiveness of development and to drive continuous improvement processes based on data.
 
- They will develop strategies for scaling and team organization that promote autonomy while minimizing coordination efforts, without compromising the coherence of the overall system.

[updated 25.08.2026]
Module content:
This module focuses on the engineering design of software systems and organizations.  It explains how the application of scientific principles and technical excellence can ensure the consistent delivery of high-quality software with high throughput, even in complex environment
 
1. Engineering foundations and empiricism
 
- Software development as a learning process: Design as a hypothesis
- Dealing with complexity: The Cynefin Framework and Systemic Thinking
- Modularity, cohesion, and separation of concerns as drivers of adaptability
- The scientific method in software development:  Iteration, feedback, validation
 
2. Flow and lean product development
 
- The economics of software development: The cost of delay and opportunity costs
- Queuing Theory and Little’s Law
- Management of work in progress (WIP), batch sizes, and lead times
- Identifying and eliminating waste in value streams (Value Stream Mapping)
 
3. Architecture for continuous delivery
 
- The deployment pipeline as a central component of software development
- Patterns for decoupling deployment and release (feature toggles, blue-green deployments, canary releases)
- Testability and test automation as drivers of architecture
- Infrastructure as code and configuration management
 
4. Organizational design and scaling
 
- Conway’s Law and the Inverse Conway Maneuver
- Interaction topologies for teams (e.g., Stream-Aligned, Platform, Enabling Teams)
- Principles of scaling: Descaling and decoupling instead of bureaucratic coordination
- Leadership in autonomous systems: Mission command vs. Command and control
 
5. Metrics and control
 
- Distinguishing between vanity metrics (e.g., velocity) and outcome metrics
- Measuring software delivery performance (lead time, deployment frequency, MTTR, change failure rate)
- Use of telemetry and monitoring to gather operational feedback

[updated 25.08.2026]
Teaching methods/Media:
Learning management system, blackboard, whiteboard, projector, presentation slides, videos, workshop format, serious games

[updated 25.08.2026]
Recommended or required reading:
Farley, D. (2021). Modern Software Engineering: Doing What Works to Build Better Software Faster. Pearson Education.
 
Forsgren, N., Humble, J., Kim, G. (2018). Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations. IT Revolution Press.
 
Kim, G., Humble, J., Debois, P., Willis, J., Forsgren, N. (2021). The DevOps Handbook: How to Create World-Class Agility, Reliability, & Security in Technology Organizations. IT Revolution Press.
 
Larson, W. (2019). An Elegant Puzzle: Systems of Engineering Management. Stripe Matter Incorporated.
 
Meadows, D. (2008). Thinking in Systems: International Bestseller. Chelsea Green Publishing.
 
Poppendieck, M., Poppendieck, T. (2006). Implementing Lean Software Development: From Concept to Cash. Pearson Education.
 
Reinertsen, D. G. (2009). The Principles of Product Development Flow: Second Generation Lean Product Development. Celeritas.
 
Reupke-Sieroux, S., Roock, S., Wolf, H. (2025). Agile Leadership: Führungsmodelle, Führungsstile und das richtige Handwerkszeug für die agile Arbeitswelt. dpunkt.verlag.
 
Skelton, M., Pais, M. (2025). Team Topologies, 2nd Edition. IT Revolution Press.

[updated 25.08.2026]
 
[Wed Sep  9 17:37:46 CEST 2026, CKEY=pase, BKEY=dim, CID=DFI-ASE, LANGUAGE=en, DATE=09.09.2026]