Software Engineering 1

by Arkadiusz Chrobot published 2019/09/29 21:04:00 GMT+1, last modified 2024-12-16T08:35:54+01:00
Learning materials for the Software Engineering 1 course.

Be warned, that published here lecture notes were not reviewed and despite my best efforts may contain some errors!

Lectures

Grading Rules

Formal Description of The Software Engineering 1 Course

  1. Introduction --- handout
  2. Project Management --- handout
  3. Requirement Engineering --- handout
  4. Software Architecture --- handout
  5. Validation And Verification --- handout
  6. Dynamic Testing, Part One --- handout
  7. Dynamic Testing, Part Two --- handout

Literature and other resources

Literature:

  1. Ian Sommerville, “Software Engineering”, Pearson Higher Education Inc., London, 2015
  2. Pierre Bourque, Richard E. Fairley, “SWEBOK v3.0 Guide to the Software Engineering Body of Knowledge”, IEEE Computer Society, USA, 2014
  3. Sungdeok Cha, Richard N. Taylor, Kyochul Kang, “Handbook of Software Engineering”, Springer Nature Switzerland AG, Cham, 2019
  4. Gerald O'Regan, “Concise Guide to Software Engineering”, Springer International Publishing AG, Cham, Switzerland, 2017
  5. David Thomas, Andrew Hunt, “The Pragmatic Programmer: Your Journey to Mastery, 20th Anniversary Edition”, Pearson Education Inc., Upper Saddle River, 2020
  6. Len Bass, Paul Clements, Rick Kazman, “Software Architecture in Practice”, Pearson Education Inc., Upper Saddle River, 2022
  7. David Farley, “Modern Software Engineering: Doing What Works to Build Better Software Faster”, Pearson Education Inc., London, 2022
  8. Robert C. Martin, “Clean Architecture: A Craftsman's Guide to Software Architecture and Design”, Pearson Education Inc., Upper Saddle River, 2018
  9. Robert C. Martin, “Clean Code: A Handbook of Agile Software Craftsmanship”, Pearson Education Inc., Upper Saddle River, 2009

Source Code:

Internet Resources:

  1. Home Page of Ian Sommerville
  2. SWEBOK v3.0 Guide to the Software Engineering Body of Knowledge
  3. Designing State Machines (Lecture Notes from MIT)