As long as you ensure A* / Dijkstra's (is there a functional difference if the edge weights are constant?) you'll get the shortest path. Part 2 was just simulation for me, if I started in the state of part 1 it took a minute to run through the rest of the bytes.
Simultaneously very fun and also the fucking worst.
Fun: Ooooh, I get to simulate a computer, exciting!
Worst: Literally 8 edge cases where fucking up even just one can fuck up your hour.
p2 discussion
I did this by hand. sort of. I mean I didn't code up something that found the answer.
Basically I looked at the program in the input and wrote it out, and realised that A was essentially a loop variable, where the number of iterations was the number of octal digits A would take to represent. The most significant octal digits (octits?) would determine the tail end of the output sequence, so to find the smallest A you can do a DFS starting from the MS octit. I did this by hand.
EDIT: code. Not gonna explain any of it.
class Comp {
List<int> reg;
List<int> prog;
int ip = 0;
List<int> output = [];
late List<(int, bool) Function()> ops;
int get combo => prog[ip + 1] < 4 ? prog[ip + 1] : reg[prog[ip + 1] - 4];
Comp(this.reg, this.prog) {
ops = [
() => (reg[0] = (reg[0] >> combo), false),
() => (reg[1] ^= prog[ip + 1], false),
() => (reg[1] = combo % 8, false),
() => (reg[0] != 0) ? (ip = prog[ip + 1], true) : (0, false),
() => (reg[1] ^= reg[2], false),
() {
output.add(combo % 8);
return (0, false);
},
() => (reg[1] = (reg[0] >> combo), false),
() => (reg[2] = (reg[0] >> combo), false)
];
}
compute() {
output.clear();
while (ip < prog.length) {
if (!ops[prog[ip]]().$2) {
ip += 2;
}
}
}
reset(int A) {
ip = 0;
reg[0] = A;
reg[1] = 0;
reg[2] = 0;
}
}
void d17(bool sub) {
List<String> input = getLines();
Comp c = Comp(
input.take(3).map((s) => s.split(" ").last).map(int.parse).toList(),
input.last.split(" ").last.split(",").map(int.parse).toList())
..compute();
print("Part a: ${c.output.join(",")}");
if (!sub) return;
List<int> sols = [];
bool dfs(int cur) {
bool found = false;
sols.add(cur);
int sol = sols.reduce((a, b) => 8 * a + b);
c..reset(sol)..compute();
if (c.prog
.whereIndexed((i, e) => i >= c.prog.length - c.output.length)
.foldIndexed(true, (i, p, e) => p && c.output[i] == e)) {
if (found = c.output.length == c.prog.length) {
print("Part b: $sol");
} else {
for (int i = 0; i < 8 && !(found = found || dfs(i)); i++) {}
}
}
sols.removeLast();
return found;
}
for (int a = 0; a < 8 && !dfs(a); a++) {}
}
EDIT: I have a sneaking suspicion that the computer will need to be re-used since the combo-operand 7 does not occur and is "reserved".
re p2
Also did this by hand to get my precious gold star, but then actually went back and implemented it
Some JQ extension required:
#!/usr/bin/env jq -n -rR -f
#─────────── Big-endian to_bits and from_bits ────────────#
def to_bits:
if . == 0 then [0] else { a: ., b: [] } | until (.a == 0;
.a /= 2 |
if .a == (.a|floor) then .b += [0]
else .b += [1] end | .a |= floor
) | .b end;
def from_bits:
{ a: 0, b: ., l: length, i: 0 } | until (.i == .l;
.a += .b[.i] * pow(2;.i) | .i += 1
) | .a;
#──────────── Big-endian xor returns integer ─────────────#
def xor(a;b): [a, b] | transpose | map(add%2) | from_bits ;
[ inputs | scan("\\d+") | tonumber ] | .[3:] |= [.]
| . as [$A,$B,$C,$pgrm] |
# Assert #
if [first(
range(8) as $x |
range(8) as $y |
range(8) as $_ |
[
[2,4], # B = A mod 8 # Zi
[1,$x], # B = B xor x # = A[i*3:][0:3] xor x
[7,5], # C = A << B (w/ B < 8) # = A(i*3;3) xor x
[1,$y], # B = B xor y # Out[i]
[0,3], # A << 3 # = A(i*3+Zi;3) xor y
[4,$_], # B = B xor C # xor Zi
[5,5], # Output B mod 8 #
[3,0] # Loop while A > 0 # A(i*3;3) = Out[i]
] | select(flatten == $pgrm) # xor A(i*3+Zi;3)
)] == [] # xor constant
then "Reverse-engineering doesn't neccessarily apply!" | halt_error
end |
# When minimizing higher bits first, which should always produce #
# the final part of the program, we can recursively add lower bits #
# Since they are always stricly dependent on a #
# xor of Output x high bits #
def run($A):
# $A is now always a bit array #
# ┌──i is our shift offset for A #
{ p: 0, $A,$B,$C, i: 0} | until ($pgrm[.p] == null;
$pgrm[.p:.p+2] as [$op, $x] | # Op & literal operand
[0,1,2,3,.A,.B,.C,null][$x] as $y | # Op & combo operand
# From analysis all XOR operations can be limited to 3 bits #
# Op == 2 B is only read from A #
# Op == 5 Output is only from B (mod should not be required) #
if $op == 0 then .i += $y
elif $op == 1 then .B = xor(.B|to_bits[0:3]; $x|to_bits[0:3])
elif $op == 2
and $x == 4 then .B = (.A[.i:.i+3] | from_bits)
elif $op == 3
and (.A[.i:]|from_bits) != 0
then .p = ($x - 2)
elif $op == 3 then .
elif $op == 4 then .B = xor(.B|to_bits[0:3]; .C|to_bits[0:3])
elif $op == 5 then .out += [ $y % 8 ]
elif $op == 6 then .B = (.A[.i+$y:][0:3] | from_bits)
elif $op == 7 then .C = (.A[.i+$y:][0:3] | from_bits)
else "Unexpected op and x: \({$op,$x})" | halt_error
end | .p += 2
) | .out;
[ { A: [], i: 0 } | recurse (
# Keep all candidate A that produce the end of the program, #
# since not all will have valid low-bits for earlier parts. #
.A = ([0,1]|combinations(6)) + .A | # Prepend all 6bit combos #
select(run(.A) == $pgrm[-.i*2-2:] ) # Match pgrm from end 2x2 #
| .i += 1
# Keep only the full program matches, and convert back to int #
) | select(.i == ($pgrm|length/2)) | .A | from_bits
]
| min # From all valid self-replicating intputs output the lowest #
I literally created different test inputs for all the examples given and that found a lot of bugs for me. Specifically the difference between literal and combo operators.
I used A*, though mathematically I would have been fine with Dijkstra's. Also, here's how I remember how to spell Dijkstra: ijk is in alphabetical order.
p2
If you've implemented path/back tracking on a search algo before, this wasn't too bad, though instead of tracking best parent you need to track equivalently best parents. Woke AOC trying to normalise families with more than two parents, SMH
DFS (it's all dfs all the time now, this is my life now, thanks AOC) pruned by unless-I-ever-passed-through-here-with-a-smaller-score-before worked well enough for Pt1. In Pt2 in order to get all the paths I only had to loosen the filter by a) not pruning for equal scores and b) only prune if the direction also matched.
Pt2 was easier for me because while at first it took me a bit to land on lifting stuff from Djikstra's algo to solve the challenge maze before the sun turns supernova, as I tend to store the paths for debugging anyway it was trivial to group them by score and count by distinct tiles.