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TDDD27 Advanced Web Programming (6 ECTS)

Vt2

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Video recordings from the lecture: Part 1:
Part 2:
Part 3:
Part 4:

  • 1/4 Course fixed for 2025, no major changes from 2024

Have Questions? Click "Getting help" in the menu to the left.

TDDD27 VT2 2025 progress steps.

  • Find partner, decide to work alone.
  • Register on webreg for grading
  • Create and a gitlab.liu.se repo for the project. Use the prefix TDDD27_2025.
    • Add eribe22, sahsa74 and andla63 as Reporters, with Expiration date 2026-12-31.
  • Register your gitlab.liu.se-repo in this form. Submit the https:// link to your repo. This is super important, this is how we organize the work
  • Search youtube for TDDD27 for screencasts for inspiration. Remember that previous years may not be entirelly representative of this years goals since things change and some things gets easier.
  • Determine frameworks for your project (see Tech Requirements).
  • Determine your project idea.
  • Add a project specification in the Readme.md of your gitlab.liu.se repo by the deadline.
  • Work hard and smart ... start early becasue it takes time to learn the frameworks.
  • Focus in the front-end first. They are genreally much more complicated.
  • Participate in half-time status report seminars. [Book time in webreg].
  • Submit your individual oral screencast with code demonstration. Here you have 10-12 minutes to show your project and to demonstrate that you have achived the learning goals of the course and to what degree. Put the links on your gitlab.liu.se repo.
  • Also record a project screencast showing the project (as a team). Put the links on your gitlab.liu.se repo.
  • Make the final commit on the project.

Deadlines

  • Register on webreg April 11
  • Create Project April 11
  • Functional and technological specification on repo in readme.md. April 11
  • Project status seminar. May 6, 7, 13, 14 (book on webreg)
  • Individual oral code screencast. June 6 (screencast link on gitrepo)
  • Project screencast. June 6 (screencast link on gitrepo)
  • Final source code upload. June 6
  • Late submissions after summer: email examiner on the 22:th of August that you have everything on your repo and provide also the repo URL.

About the course

This course has a focus on state-of-the art large-scale web development. It's an A-level project course with focus on deep understanding of technology in the web area. A particular focus is placed on modern and advanced client-side framworks.

Fundamental understanding of web-programming is assumed, as is having a high level of general programming skill. Projects are performed by individuals or by teams of two/three. We examine knowledge, not products, and use the oral examination, screencasts and gitlab code repos code and commits for examination. We read code and we want well-designed code, relevant commit-comments and valuable version control messages ... but not documentation.

Changes from 2024

  • no real changes
  • Project volume still important
  • Projects with many details, worked through designs still important
    ... boiler-plate projects will still not pass the course (see Tech Requirements)

Gitlab.liu.se only

Code must be version managed on gitlab.liu.se. Full version history and all branches should be on gitlab.liu.se. A big push of code at the end of the course is suspicious. Furthermore, use freequent commiting and write relevant commit comments. We want to see all experimentation branches and all commits, not just main. A vivid, frequent commits, many branched with merged main git-repo with a lot of details about what happens. The course staffa are all active and senior web developers and we know it gets messy below the surface.

AI in the course.

LLMs as a learning tool and producing boiler-plate code is ok i TDDD27, just like working with stackoverflow, copy-pasting code from tutorials, picking stuff from MIT-projects on GITHUB etc.... all other engeneering techniques. Make use of AI to learn faster, but make sure to learning. Using AI, but prentending its your work is cheating.

As a concequence of LLMs, your projects need to be bigger, more unique, and have more details to be approved since the world is now diffrent than before 2024.

AI as a component in your project is both good ... but sometimes also bad. Its easy to feel that you have a great system beacsue your generative AI model creates very dynamic work. AI models give no value technichally to the proejct, its like a database, something you use outside the web tech stack. Traning AI models is also not part of this course, such work can contribute to your project but not be a major part of the work you get credits for.

Evaliute evaluation of course

  • 2024: overal grade 3.50
  • 2023: overal grade 3.95
  • 2022: overal grade 4.06 (covid year)
  • 2021: overal grade 2.93 (covid year)
  • 2020: overal grade 4.27
  • 2019: overal grade 4.47

Page responsible: Erik Berglund
Last updated: 2025-04-03