You made it here, that's great! In the following two sections we'll provide you with a self-assessment challenge and general information about the platform and submission requirements. Make sure to read through both before trying to submit your solution.
Parse a JSON-object provided to you via stdin, concatenate the strings in the "snippets" array with the "delimiter" between the snippets. Then calculate the sha256-hash of the string and print the result in hex as a JSON-object in the form
{"hash": <the sha256-hash>}
to stdout. For example, if the given JSON would be
{"snippets": ["a", "b", "c"], "delimiter": "-"}
you have to calculate the sha256-hash of the string "a-b-c".
Your solution should then be:
{"hash": "cbd2be7b96f770a0326948ebd158cf539fab0627e8adbddc97f7a65c6a8ae59a"}
Upload you solution to the
submission platform and check
whether it worked correctly. Make sure to thoroughly read the next section so
that your solution fulfills the submission requirements.
During the course you'll step into the shoes of a sophisticated secret agent with a machine-learning background: You'll try to hide secret messages in plain sight by using an LLM to encode them within what looks like normal text to others. But what was a special agent without a villain trying to get hold of the messages? Well, probably less work for nine credits. You'll also step into the shoes of this villain, trying to build a detector for hidden messages.
Why do we need a platform for all this? - Well, that's the best part. As every group builds both, a "hider" and a "seeker", we can let them play against each other. The "hider" tries to hide messages in plain text while the "seeker" tries to predict which texts contain hidden messages and which don't. During the semester, you'll find a scoreboard showing how each team's "hiders" and "seekers" perform against each other. To make all this possible you'll have to upload them to this platform of course.
To get yourself started, we prepared a small test to exemplify the process, which will be very similar during the semester. We strongly encourage to proceed through as it shouldn't take long and ensures that you'll have a smooth start once the course starts.
The general structure is fairly easy, as you can see in Figure 1. You just set up a directory with a certain structure (more on that in a second), archive it and upload the archive to this platform. We'll automatically unpack the archive, run your code and update the results on the scoreboard page. For the self-assessment, the result only indicates whether your archive was created correctly and the solution to the test challenge was correct. During the course, the scoreboard will probably be a bit more interesting!
So let's dive into the directory structure real quick. There are only three requirements which have to be fulfilled:
stemo:assessment built from
this
Dockerfile.
submission.tar.gz ├─ Dockerfile ├─ main.py ┊
To create the .tar.gz-archive, run tar czf submission.tar.gz * from your project-directory's root. That's it, your archive is ready to be uploaded.