Programme And Module Handbook
 
Course Details in 2027/28 Session


If you find any data displayed on this website that should be amended, please contact the Curriculum Management Team.

Module Title LM Intelligent Software Engineering (Extended)
SchoolComputer Science
Department Computer Science
Module Code 06 40095
Module Lead Dr Jens Christian Clausen
Level Masters Level
Credits 20
Semester Semester 2
Pre-requisites
Co-requisites
Restrictions None
Contact Hours Lecture-33 hours
Practical Classes and workshops-22 hours
Guided independent study-145 hours
Total: 200 hours
Exclusions
Description Both Artificial Intelligence (AI) and Software Engineering (SE) are increasingly important areas in Computer Science, but they are rarely taught together. This module covers the unique synergy between AI and SE, which, combined in automated AI software engineering research and practice, have had a considerable and continuing impact. The topic consists of two major pillars: \"AI for SE\", where AI algorithms have been tailored to automatically solve various tasks in software engineering (e.g., code defect prediction, bug report analysis, and configuration performance tuning etc); and \"SE for AI\", in which software engineering methodologies have been applied to build better AI-powered software systems. The module discusses specific concepts, methodologies and their algorithmic features and implementations for solving particular automated SE tasks and for engineering AI software systems.
Learning Outcomes By the end of the module students should be able to:
  • 20.1
  • Describe the various formalisations of automated SE tasks and their characteristics.
  • 20.2
  • Describe the AI methods that can be applied to solve those SE tasks.
  • 20.3
  • Describe SE concepts and methodologies that can be used to build AI software systems.
  • 20.4
  • Understand and compare the potential resolutions for both AI for SE and SE for AI.
  • 20.5
  • Demonstrate the capacity to independently study, understand, and critically evaluate advanced materials or research articles in the subject areas covered by this module.
Assessment
Assessment Methods & Exceptions Assessment:

Assessment:
Continuous Assessment (100%)

Reassessment:

100% CA over the Summer Period
Other
Reading List