Undirected Replacement Paths: Dual Fault Reduces to Single Source

📅 2026-05-03
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🤖 AI Summary
This work resolves the open question of whether two-fault replacement paths (2-FRP) in undirected graphs are computationally harder than single-source replacement paths (SSRP). By constructing the first tight weight-preserving reduction from 2-FRP to SSRP, the paper demonstrates their computational equivalence, challenging the prevailing intuition that handling two faults is inherently more difficult. The approach integrates graph-theoretic reductions, fast matrix multiplication, and combinatorial optimization, and is analyzed under fine-grained complexity assumptions. The resulting algorithm matches the best-known running times for SSRP across various edge-weight regimes, significantly improving upon prior results for 2-FRP and establishing corresponding fine-grained lower bounds.
📝 Abstract
Given a graph and two fixed vertices $s$ and $t$, the Replacement Path Problem (RP) is to compute for every edge $e$, the distance between $s$ and $t$ when $e$ is removed. There are two natural extensions to RP: (1) Single Source Replacement Paths (SSRP): Given a graph $G$ and a source node $s$, compute for every vertex $v$ and every edge $e$ the $s$-$v$ distance in $G \setminus \{e\}$. That is, we do not fix the target anymore. (2) $2$-Fault Replacement Paths (2-FRP): Given a graph $G$ and two nodes $s$ and $t$, compute for every pair of edges $e, e'$ the $s$-$t$ distance in $G \setminus \{e, e'\}$. That is, we consider two failures instead of one. Previously, there was no known reduction between SSRP and 2-FRP. It seemed plausible that 2-FRP would be computationally harder because there are no settings where 2-FRP admits a faster algorithm than SSRP. In directed unweighted graphs there is a provable gap in complexity, and in undirected graphs many of the known 2-FRP algorithms in a variety of settings are much slower than those for SSRP in the same setting. The main contribution of this paper is a tight reduction from undirected $2$-FRP to undirected SSRP, showing that contrary to prior intuition, 2-FRP is not harder than SSRP. As our reduction is weight-preserving, we obtain the first algorithms for $2$-FRP that match the best-known runtimes for SSRP: (1) $\tilde{O}(M n^ω)$ for weights in $[1, M]$ [GVW19], improving upon $O(Mn^{2.87})$ [CZ24]; (2) $n^3/2^{Ω(\sqrt{\log n})}$ for weights in $[1, \text{poly}(n)]$ [GVW19], improving over the previous $n^3\text{polylog}(n)$ running time [VWWX22]; (3) $\tilde{O}(mn^{1/2}+n^{2})$ combinatorial time for unweighted graphs [CC19], and more generally for rational weights in $[1, 2]$ [CM20], improving upon $\tilde{O}(n^{3-1/18})$ [CZ24]. We complement these upper bounds with tight lower bounds under fine-grained hypotheses.
Problem

Research questions and friction points this paper is trying to address.

Replacement Paths
Single Source Replacement Paths
2-Fault Replacement Paths
Undirected Graphs
Fine-grained Complexity
Innovation

Methods, ideas, or system contributions that make the work stand out.

Replacement Paths
Fault Tolerance
Graph Algorithms
Fine-Grained Complexity
Reduction
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