Your implementation will be graded using GradeScope.
Your score will comprise four elements.
Test score (60% of overall score): score regarding whether your analyzer reports all the expected true alarms
Precision score (15% of overall score): score regarding the precision of your analyzer
Efficiency score (15% of overall score): score regarding the efficiency of your worklist algorithm
Quiz (10% of overall score): will be graded manually after the late due date.
Since there is a Quiz of 10%, the maximum score you will see on the leaderboard will be 90.
Coverage
As explained in the README file, we will check the coverage of your code (> 80%) using the basic tests + your custom tests.
Refer to this document for how to add your custom tests.
How to submit
As before, push your code to GitHub first.
Then, submit via Gradescope, which you can access by the assignment with the name "5. ThriLLVM Analyzer" in KLMS.
Due date
Due: 5. 8 (Wed.) 23:59:59
Late Due: 5. 10 (Fri.) 23:59:59 (with late submission penalty).
Hi all,
This is an announcement about Homework 5. Here is the GitHub classroom link for this homework: https://classroom.github.com/a/ee8-XRqg
Auto grading
Your implementation will be graded using GradeScope.
Your score will comprise four elements.
Since there is a Quiz of 10%, the maximum score you will see on the leaderboard will be 90.
Coverage
As explained in the README file, we will check the coverage of your code (> 80%) using the basic tests + your custom tests. Refer to this document for how to add your custom tests.
How to submit
As before, push your code to GitHub first. Then, submit via Gradescope, which you can access by the assignment with the name "5. ThriLLVM Analyzer" in KLMS.
Due date
Due: 5. 8 (Wed.) 23:59:59 Late Due: 5. 10 (Fri.) 23:59:59 (with late submission penalty).