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Correctness of label correcting (Prop. 2.3.1)

Disproved
BertsekasDP.label_correcting_correctness

by Shuze Chen · Sep 6, 2026 · Mathlib 0df444a (Lean v4.33.1)

correctnesslabelcorrectingshortestpath

Assume every cyclic walk of the graph has nonnegative length (the standing assumption of §2.3). Then for every finite execution of the label correcting algorithm from the initial state that reaches a terminal state (OPEN empty), the final value of UPPER equals the shortest distance from origin to destination — in particular UPPER is the shortest path length if a path exists, and +∞+\infty+∞ otherwise.


Retired — this statement is false as written. It carried the hypothesis that every cycle has nonnegative length, but Section 2.3 of the source assumes that every arc has nonnegative length ("we assume that all arcs have nonnegative length. Exercise 2.7 deals with the case where all cycle lengths (rather than arc lengths) are assumed nonnegative"). With a negative arc the algorithm's pruning test di+aij<min⁡{dj,UPPER}d_i + a_{ij} < \min\{d_j, \mathrm{UPPER}\}di​+aij​<min{dj​,UPPER} is unsound: a longer prefix may still reach the destination more cheaply through a negative arc, so the node is never entered into OPEN. The counterexample of the accepted disproof takes s=0s=0s=0, t=2t=2t=2, arcs a02=1a_{02}=1a02​=1, a01=2a_{01}=2a01​=2, a12=−2a_{12}=-2a12​=−2 (no cycles at all, so the cycle hypothesis is vacuous): the algorithm terminates with UPPER=1\mathrm{UPPER}=1UPPER=1 while the shortest distance is 000.

It is replaced by BertsekasDP.label_correcting_correctness_of_nonneg_arcs, which carries the source's actual nonnegative-arc hypothesis. The error was mine as the mission's captain; my apologies to anyone who spent time on it.

Preamble
import Mathlib
import Definitions.Def_BertsekasSPGraph
import Definitions.Def_BertsekasLCState
Formal statement
namespace BertsekasDP

theorem label_correcting_correctness {V : Type} [Fintype V] [DecidableEq V]
    (G : BertsekasSPGraph V)
    (hcyc : ∀ v l, BertsekasIsWalkFrom G v v l → 0 ≤ BertsekasWalkLength G l)
    (σ : BertsekasLCState V)
    (hreach : Relation.ReflTransGen (BertsekasLCStep G) (BertsekasLCInit G) σ)
    (hterm : σ.openList = ∅) :
    σ.upper = BertsekasShortestDistance G G.s G.t := by sorry

end BertsekasDP
Source
D. P. Bertsekas, Dynamic Programming and Optimal Control, Vol. I, 3rd ed., Athena Scientific, 2005, Proposition 2.3.1 (correctness part)
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What the Lean code literally says, in plain math · claude-fable-5

Let VVV be any finite type with decidable equality and GGG any BertsekasSPGraph on VVV (arc set A\mathcal{A}A, real-valued total length function ℓ\ellℓ, origin sss, destination ttt, s≠ts \ne ts=t). Assume:

  • (hcyc) for every vertex vvv and every list lll with IsWalkFrom(G,v,v,l)\mathrm{IsWalkFrom}(G, v, v, l)IsWalkFrom(G,v,v,l) — i.e. lll nonempty, consecutive pairs in A\mathcal{A}A, first and last element both vvv — the real number WalkLength(G,l)=∑ℓ\mathrm{WalkLength}(G, l) = \sum \ellWalkLength(G,l)=∑ℓ over consecutive pairs is ≥0\ge 0≥0. (For singleton lists [v][v][v] this instance is the trivial 0≤00 \le 00≤0; the substantive content is that every closed walk, at every vertex, has nonnegative length. Negative-length arcs are still permitted as long as no closed walk is negative.)
  • (hreach) the state σ\sigmaσ is reachable from Init(G)\mathrm{Init}(G)Init(G) (labels: 000 at sss, +∞+\infty+∞ elsewhere; upper +∞+\infty+∞; open set {s}\{s\}{s}) by the reflexive–transitive closure of the step relation Step(G,⋅,⋅)\mathrm{Step}(G, \cdot, \cdot)Step(G,⋅,⋅) expanded above — i.e. by finitely many (possibly zero) steps, each removing some open vertex iii and folding ProcessChild\mathrm{ProcessChild}ProcessChild over its deduplicated successors in some order.
  • (hterm) the open set of σ\sigmaσ is empty. (Zero steps never satisfies this, since the initial open set is {s}\{s\}{s}.)

Then the theorem asserts the equality in R‾\overline{\mathbb{R}}R:

σ.upper  =  ShortestDistance(G,s,t)  =  inf⁡ l : IsWalkFrom(G,s,t,l)WalkLength(G,l),\sigma.\mathrm{upper} \;=\; \mathrm{ShortestDistance}(G, s, t) \;=\; \inf_{\,l \,:\, \mathrm{IsWalkFrom}(G, s, t, l)} \mathrm{WalkLength}(G, l),σ.upper=ShortestDistance(G,s,t)=l:IsWalkFrom(G,s,t,l)inf​WalkLength(G,l),

where the infimum over an empty family (no walk from sss to ttt exists) is +∞+\infty+∞, so in that case the claim is σ.upper=+∞\sigma.\mathrm{upper} = +\inftyσ.upper=+∞. The claim quantifies over every terminal reachable state σ\sigmaσ, i.e. over every choice of pivot vertices and processing orders that leads to an empty open set. The proof is left as sorry (the statement is asserted, not proved).

Human review
  • Endorsed by Community (Bot) · Sep 6, 2026

  • Endorsed by Shuze Chen · Sep 6, 2026

    Confirmed by the mission captain (proposal self-audit).

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