Software Engineering for Smart Data Analytics & Smart Data Analytics for Software Engineering

User Tools

Site Tools

General Information

  • Course number: MA-INF 3303 (semianr) + MA-INF 3306 (lab)
  • Credit points: 4 for the seminar + 91) for the lab.
  • Hours per week: 2 for the seminar + 6 for the lab
  • Prerequisites: ALP course or equivalent knowledge of logic programming.


We will use a logic-based software analysis and transformation framework to implement various classical program analyses in a model-based setting. You will learn about

  • Program analysis techniques (control flow analysis, data flow analysis, …)
  • Model-driven software engineering (models and metamodels, declarative model analysis and transformation)
  • Agile software development practices (pair programming, refactoring, agile planning, …)

Course Structure

The course consists of

  • a Seminar Phase in which we will get to know each other and lay the conceptual foundations for the practical part
  • a Lab Phase in which we will implement various program / model analysis algorithms using a declarative model-driven tool and agile software development techniques.

The course will be conducted in parallel with the project group “ Modellbasierte Softwareanalyse” (MoSA). Where appropriate, you will work together with the participants from the parallel course. Taking advantage of shared knowledge and added man-power, we will be able to tackle more interesting and challenging problems.

Place and Time

Both, seminar and lab, will take place in the b-it building , room 1.32 and 1.31.

For time information see the pages for the Seminar Phase and Lab Phase.

Mailing List

  • agile participants spring lists iai uni bonn de (fill spaces with “- - @ . . - .”)

Teaching Staff

Who E-mail Tel Office
gk Günter Kniesel gk cs uni-bonn de (0228) 73-4511 A107
dsp Daniel Speicher dsp cs uni-bonn de (0228) 73-4315 A109
jn Jan Nonnen nonnen cs uni-bonn de (0228) 73-4519 A123
Remember: According to the regulations effective since summer 2010, you need a 9 credit points lab in your area of specialization.
teaching/labs/ese/2010/start.txt · Last modified: 2018/05/09 01:59 (external edit)

SEWiki, © 2024