Bounty Points: 75
Branch Instructions
push changes to a new 'ds' branch
Explanation:
Current clock list management is inefficient
Removes items while iterating: for i in clock: if i[2]==t: clock.remove(i)
$O(n^2)$ complexity due to list.remove() in loop
No priority queue for event scheduling
Current problematic code:
for i in clock:
if i[2] == t:
clock.remove(i) # $O(n)$ operation in $O(n)$ loopPossible fix/approach:
- Replace list with
heapq-based priority queue
- Use event-based scheduling with
(time, event\_data)
- Alternative: dictionary with time as key
- Benchmark before/after improvements
- Document complexity improvements
Maintainer notes:
- Current approach causes performance issues with large graphs
- Focus on clock/event management data structure
- Should maintain same simulation logic
Resources:
- Python
heapq documentation
- Event-driven simulation patterns
Bounty Points: 75
Branch Instructions
push changes to a new 'ds' branch
Explanation:
Current clock list management is inefficient
$O(n^2)$ complexity due to
Removes items while iterating:
for i in clock: if i[2]==t: clock.remove(i)list.remove()in loopNo priority queue for event scheduling
Current problematic code:
Possible fix/approach:
heapq-based priority queue(time, event\_data)Maintainer notes:
Resources:
heapqdocumentation