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Automated Programming

IN2367Cross-Cutting Elective Modules2 ECTSEnglishsummer semesterDepartment Computer Science
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You will learn current methods of automated program synthesis at the interface of Software Engineering, AI and machine learning. In the end you will know various specification approaches for functional, reactive and probabilistic programs as well as techniques to search for or generate programs that satisfy these specifications.

What you will be able to do

  • Fundamental understanding of the dimensions of automated program synthesis
  • Knowledge of different specification approaches (functional, reactive, probabilistic)
  • Familiarity with search and synthesis techniques (deductive, transformative, inductive, learning-based)
  • Overview of capabilities and limitations of current synthesis methods
  • Preparation for scientific work or application in specialized applications

What the module consists of

  • LectureConveying concepts and algorithms; lecture with slides
  • Practical exercisesApplication of the methods; some interactively in the lecture, others as independent study

Teaching method

  • Lecture with slidesIntroduction and explanation of the topics
  • Practical exercises (partly interactive)Consolidation and application of what has been learned; some tasks as independent study
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Official page in TUMonline · Details are not binding.