There is exactly one test of whether an environment is reproducible, and it is not a file listing. It is: a labmate ran it and got your number. Everything else is a proxy. This lab’s stack makes the proxy especially untrustworthy — Gurobi, CPLEX and GAMS all change behaviour across versions in ways that move a solution without producing an error, and ReEDS carries its own version-sensitive assumptions.
The Turing Way, reproducible environments chapter. It covers the concepts and the tooling landscape well. The standard is sharper on what specifically has to be recorded, and that specificity is the thing being graded here — read the standard’s dependency rule directly.
The standard’s dependency rule. It states what must be recorded and in what combination; this lesson deliberately does not restate it.
Pair with another student in the class.
Your partner, on their own machine, working from your README alone, reproduces one named figure from your work. You may not help. You may not be in the room. Any question they have to ask you is a defect in the README, and it goes in the log.
They write the run log: what they ran, what broke, what they had to guess. They sign it. If the number differs, that is not automatically a failure — but you must state a tolerance and say whether the divergence sits inside it. A tolerance chosen after seeing the divergence is not a tolerance.
Repo URL plus your partner’s signed run log.
This replaces your arithmetic entry for the week you do it. Submit it to that week’s WA assignment in Canvas — the same one you would have submitted anyway. It is not an extra piece of work on top of the log.
You do not submit anything to the milestone yet. When all four skills in M2 are done, submit the M2 — Reproducible Code assignment, which is just an index saying which week each one went in.