DFS follows a branch deeply before returning to pending branches.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | from bisect import bisect_left # Depth First Search Reachability in Python # # PURPOSE # DFS follows a branch deeply before returning to pending branches. An explicit stack avoids # language recursion limits for reachability exploration. # # METHOD # Push the source and mark it. Pop a vertex, count it, then mark and push each unseen # neighbor. Marking when pushed bounds stack entries to at most n. # # COMPLEXITY # O(n squared) time with a matrix and O(n) auxiliary space. Adjacency lists reduce traversal # to O(V+E). # # CONTRACT # Flattened n by n 0/1 matrix, n >= 1, valid source. Returns the number of reachable # vertices INCLUDING source. Directed edges supported. # Public APIs infer array lengths except in C, which accepts pointer/length pairs. Vertex # counts and matrix dimensions remain explicit. Arrays must contain signed 32-bit integers. # Sorted order, correct tree topology, and caller-owned data-structure invariants are # preconditions; checking them on every query would change query complexity. # Scalar and shape checks are included. Value-range checks are included where needed to # prevent invalid indexing or nontermination. Allocation sizes are capped at 4,000,000 # workspace entries. Arithmetic outside Python raises an error on 32-bit overflow; Python # uses arbitrary precision. Native allocation failures propagate. In-place outputs may be # partly updated after arithmetic failure. These are single-threaded, in-memory # implementations. # # LANGUAGE DETAILS # Python 3.9+: automatic lengths, native lists, arbitrary-precision arithmetic, and # bisect_left for LIS. Invalid scalar/shape inputs raise ValueError. Integer element types # and sorted/tree invariants remain caller preconditions. # # EXAMPLE # Expected return: 3. # Run: python example.py # Tests for this exact source artifact run before publication. The accompanying source # archive includes unit cases, runtime results, and source hashes. def alg_require(condition): if not condition: raise ValueError("invalid algorithm input; see contract") def alg_size(n): alg_require(0 <= n <= 4000000) return n def dfs_reachable(graph: list[int], n: int, source: int) -> int: alg_require(isinstance(graph, (list, tuple)) and len(graph) <= 1000000) alg_require(type(n) is int and -2147483648 <= n <= 2147483647) alg_require(type(source) is int and -2147483648 <= source <= 2147483647) alg_require(n >= 0 and n <= 1000000) alg_require(len(graph) == n * n) alg_require(n >= 1 and source >= 0 and (source < n)) seen: list[int] = [0] * alg_size(n) stack: list[int] = [0] * alg_size(n) top: int = 1 count: int = 0 u: int = 0 v: int = 0 stack[0] = source seen[source] = 1 while top > 0: top -= 1 u = stack[top] count += 1 v = 0 while v < n: if graph[u * n + v] != 0 and seen[v] == 0: seen[v] = 1 stack[top] = v top += 1 v += 1 return count graph = [0, 1, 0, 0, 0, 1, 0, 0, 0] n = 3 source = 0 result = dfs_reachable(graph, n, source) print(result) |