Batch-add 12 Backlog Models#1067
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- New skill .claude/skills/auto-pipeline: orchestrator that drives one Backlog issue from quality gate to Final review via fresh-context subagents (check-issue, fix-issue, run-pipeline, review-pipeline). Substantive issue-body problems are routed to codex xhigh; fundamental flaws with no public reference park the issue on OnHold. - check-issue: add Rule Check 5 (Completeness, fail label "Incomplete"). Mandatory literature research + codebase corner-case enumeration + hand-tracing on >= 2 non-canonical instances for every [Rule] issue. - review-structural: add Step 4b (Round-trip Execution, mandatory for Rule reviews). Reviewer must run cargo test by name, paste the "test result: ok" line, and confirm the test exercises the four phases of a real round-trip. - review-quality: promote "closed-loop without round-trip verification" from a Minor flag to Critical, with explicit red flags (is_some-only, target-side-only asserts, unique-optimum instances). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Robotics inverse-kinematics problem: given link lengths l_j, target
g in R^2, per-link sampled orientations Phi_j, and consecutive-pair
admissibility sets A_j, pick indices a_j in {0..m_j-1} with
(a_{j-1}, a_j) in A_j minimizing the squared end-effector distance
||sum_j l_j (cos phi_{j,a_j}, sin phi_{j,a_j}) - g||^2.
- src/models/misc/minimum_discrete_planar_inverse_kinematics.rs:
per-link dims (non-binary), Min<f64> objective, A_j feasibility
returns Min(None), declare_variants! default entry, ProblemSchemaEntry
+ ProblemSizeFieldEntry, canonical example_db spec via inventory.
- src/unit_tests/models/misc/...: creation, evaluate (feasible/
infeasible), brute-force solver, serialization roundtrip.
- problemreductions-cli/: new (f64,f64) and Vec<Vec<(usize,usize)>>
schema parsers; --link-lengths/--target-point/--orientation-samples/
--allowed-pairs flags via the schema-driven create path.
- docs/paper: problem-def block + display-name + worked example;
references.bib entries for Salloum2025 and DaiIzattTedrake2019.
Reference: Salloum et al., "Quantum annealing for inverse kinematics
in robotics", Scientific Reports 2025, doi:10.1038/s41598-025-34346-z.
Closes #994
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The brute-force search space is prod_{j=1}^n m_j, not 2^n — per-link
sample counts m_j are arbitrary. Add a `total_configurations()` getter
that returns the product, and rewrite the declare_variants! complexity
as `num_links * total_configurations` (n vertices in evaluate cost
times the iteration space).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Trivial single-line rewrite to match rustfmt. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-k-plex problem: given graph G=(V,E), vertex weights w, and integer
k>=1, find max-weight subset S subseteq V such that the induced
subgraph G[S] has maximum degree at most k-1 (i.e. every selected
vertex has at most k-1 selected neighbours). Generalizes
MaximumIndependentSet (the k=1 case) and is the complement-graph view
of maximum k-plex from the clique-relaxation literature.
- src/models/graph/maximum_co_k_plex.rs: MaximumCoKPlex<G,W,K>
parameterized by graph type, weight type, and K-multiplier. Only the
KN (runtime-k) variant registered initially per the issue's
"initially KN, K1/K2/... later" plan. Max<W::Sum> objective,
induced-degree feasibility, declare_variants! default + i32 variant,
canonical example via inventory (5-cycle weights (5,1,4,1,3) k=2,
optimum {0,2,4} value 12).
- src/unit_tests/models/graph/maximum_co_k_plex.rs: creation,
evaluate-feasible (issue optimum + smaller feasible), evaluate-
infeasible (degree-2 violation), brute-force solver, serialization.
- problemreductions-cli/src/commands/create/: schema-driven CLI maps
schema field bound_k to existing --k flag with semantic validation.
- docs/paper: problem-def block with C_5 worked example and k=1 ->
MaximumIndependentSet equivalence note; references.bib gains
Hernandez2016MolecularSimilarity and HosseinianButenko2022KDependent.
References: arXiv:1601.06693 (Hernandez et al., 2016) for the
molecular-similarity framing; doi:10.1016/j.dam.2021.10.015
(Hosseinian & Butenko, 2022) for the maximum k-dependent set view.
Closes #1015
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
MCES: given two directed edge-labelled graphs G1, G2, find a partial injective map f: U1 ⊆ V1 → V2 maximizing the number of preserved labelled arcs (u, λ, v) ∈ E1 with f(u), f(v) defined and (f(u), λ, f(v)) ∈ E2. Edge labels must match exactly; set semantics (no multiplicities); disconnected common subgraphs allowed; no secondary tie-break. - src/models/graph/maximum_common_edge_subgraph.rs: local LabelledArc + LabelledDigraph structs (does not extend the existing Graph trait hierarchy in this PR). dims = vec![|V2|+1; |V1|] with the +1 slot encoding ⊥. Max<i64> objective with injectivity feasibility on the matched slots. ProblemSchemaEntry + ProblemSizeFieldEntry for num_vertices_1/_2 and num_arcs_1/_2, declare_variants! default with complexity (num_vertices_2+1)^num_vertices_1. Canonical example via inventory from the issue's 5-vs-4-vertex instance with optimum value 5. - src/unit_tests/models/graph/maximum_common_edge_subgraph.rs: 12 tests covering creation, evaluate-feasible (optimum 5), evaluate-injectivity-violated, evaluate-fewer-preserved, brute-force solver, serialization. - problemreductions-cli/: new --graph-1 / --graph-2 flags with a LabelledDigraph parser; alias MCES. - docs/paper: problem-def block, display-name, MCES worked example. - docs/paper/references.bib: corrected per Crossref against the check-issue warning — Bahiense2012 first names (Laura/Gordana/Breno), Soule2021 author list (Soule/Reinharz/Sarrazin-Gendron/Denise/ Waldispuhl) and venue, Bokhari1981 volume (C-30). References: doi:10.1109/TC.1981.1675756 (Bokhari 1981), doi:10.1016/j.dam.2012.01.026 (Bahiense et al. 2012, polyhedral investigation), doi:10.1371/journal.pcbi.1008990 (Soule et al. 2021, RNA networks application). The direct `MaximumCommonEdgeSubgraph -> ILP` rule (#1019) is out of scope for this PR and will follow separately. Closes #1018 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Exact-cardinality edge-weighted clique: given a simple undirected
graph G=(V,E), edge weights w: E→R, and an integer k with 0≤k≤|V|,
find a vertex subset S with |S|=k forming a clique that maximizes
the sum of weights of edges induced by S. Edge weights may be
negative; k=0 and k=1 are admitted with objective value 0.
Distinct from the existing MaximumClique (vertex-weighted, no
exact-k) and KClique (decision problem with threshold |S|>=k).
- src/models/graph/maximum_edge_weighted_k_clique.rs:
MaximumEdgeWeightedKClique<W: WeightElement> with SimpleGraph fixed;
edge_weights vector aligned to graph.edges() order, runtime k field.
dims = vec![2; |V|]. Max<W::Sum> objective; infeasible when |S|≠k
or S is not a clique. declare_variants! default (SimpleGraph,i32)
plus (SimpleGraph,f64). Canonical example via inventory from the
issue's 4-vertex instance with negative weight (clique {0,1,2}
value 8 beats {0,1,3} value 6).
- src/unit_tests/models/graph/maximum_edge_weighted_k_clique.rs:
12 tests covering creation, evaluate-feasible (both optima),
evaluate-infeasible-wrong-size, evaluate-infeasible-not-clique,
brute-force solver, edge cases k=0 and k=1 (value 0), f64 variant,
serialization roundtrip, panic guards.
- docs/paper: problem-def block with worked example highlighting that
the optimum includes a negative edge; display-name entry; cites
Gouveia & Martins 2015 and Hunting/Faigle/Kern 2001.
- docs/paper/references.bib: Crossref-verified Gouveia2015MEWC
(author corrected to Pedro Martins, not Paulo as the issue body
said) and HuntingFaigleKern2001EWC.
References: doi:10.1007/s13675-014-0028-1 (Gouveia & Martins 2015,
sparse-graph compact formulations); doi:10.1016/S0377-2217(99)00449-X
(Hunting, Faigle & Kern 2001, Lagrangian relaxation).
The direct `MaximumEdgeWeightedKClique -> ILP` rule (#1021) is out
of scope for this PR and will follow separately.
Closes #1020
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Given a simple undirected graph G=(V,E), find a minimum-cardinality
edge set F ⊆ E such that every connected component of G - F is either
an isolated vertex or a highly connected graph on ≥3 vertices
(edge connectivity λ(H) > |V(H)|/2, strict). Components of size 2
are explicitly invalid. Weaker than clique-deletion: every K_k for
k≥3 is highly connected, but not every highly connected graph is a
clique.
- src/models/graph/highly_connected_deletion.rs: variables are EDGES
(x_e=1 means delete edge e). Min<i64> objective counts deletions;
infeasibility on any non-singleton component that is not highly
connected (and any 2-vertex component). Private edge_connectivity
helper computes λ via repeated max-flow with unit edge capacities
(fine for small components in tests). ProblemSchemaEntry,
ProblemSizeFieldEntry (num_vertices/num_edges), declare_variants!
default with complexity 2^num_edges. Canonical example via
inventory: K3 with leaf vertex 3 attached to 2 (4 vertices,
4 edges) — optimum deletes only (2,3), value 1.
- src/unit_tests/models/graph/highly_connected_deletion.rs: 17 tests
covering creation, evaluate-optimum, evaluate-zero-deletions-
infeasible, evaluate-delete-all-feasible, evaluate-infeasible
2-vertex-component and infeasible path-component, wrong-length
config guard, brute-force on canonical + a "double triangle"
discriminator instance (two K3's joined at a bridge — optimum 1)
to address the check-issue warning about example discriminatory
power, serialization, variant, plus edge_connectivity helper
tests (single vertex=0, single edge=1, P3=1, K3=2, K4=3).
- docs/paper: problem-def block with the K3-with-leaf worked example,
display-name entry; Crossref-verified BibTeX entries for Hüffner
et al. 2014 (TCBB) and Hartuv & Shamir 2000 (IPL), with proper
umlaut encoding H{"u}ffner per repo convention.
References: doi:10.1109/TCBB.2013.177 (Hüffner et al. 2014, partitioning
biological networks); doi:10.1016/S0020-0190(00)00142-3 (Hartuv &
Shamir 2000, HCS clustering algorithm).
The direct `HighlyConnectedDeletion -> ILP` rule (#1023) is out of
scope for this PR and will follow separately.
Closes #1022
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Classical directed-multigraph satisfaction problem: given D=(V,A) with
parallel arcs and loops allowed, decide whether a directed trail
exists that uses every arc exactly once. No start or end vertex is
fixed by the input. Empty-arc instance is accepted with the empty
trail; isolated vertices are ignored.
Polynomial-time solvable (O(num_vertices + num_arcs)) by the standard
Eulerian criterion plus Hierholzer construction, so this widens the
catalog beyond NP-hard problems.
- src/models/graph/eulerian_path.rs: EulerianPath { graph:
DirectedGraph }. dims = vec![m; m] where m = num_arcs (variable t
picks which arc occurrence is the t-th trail step); the brute-force
search space is m^m but the registry complexity reflects the
linear-time best-known algorithm. Or-typed feasibility: configuration
must be a permutation of {0..m-1} and consecutive arcs must chain
(end of arc t equals start of arc t+1). declare_variants! default
+ ProblemSchemaEntry + ProblemSizeFieldEntry. Canonical example via
inventory from the issue's 3-vertex 4-arc instance with parallel
arcs (yes-instance, witness config [0,2,3,1]).
- src/unit_tests/models/graph/eulerian_path.rs: 11 tests covering
creation, evaluate-valid-witness, evaluate-not-permutation,
evaluate-bad-trail, evaluate-out-of-range, evaluate-wrong-length,
brute-force yes (canonical) + brute-force no (the issue's 2-vertex
4-arc imbalanced counterexample), empty-arcs edge case (Or(true)
with the empty witness), serialization roundtrip, variant + name.
- problemreductions-cli/src/commands/create/schema_support.rs: wire
--graph (DirectedGraph) for EulerianPath via the existing parser.
- docs/paper: problem-def block with both the yes-instance and the
no-instance from the issue; display-name entry; references.bib gains
Crossref-verified BangJensenGutin2009Digraphs (J{\o}rgen Bang-Jensen,
o-slash) and Ebert1988ComputingEulerianTrails (J{"u}rgen Ebert,
u-umlaut) — corrected from the issue body's mojibake.
References: doi:10.1007/978-1-84800-998-1 (Bang-Jensen & Gutin 2009,
digraphs); doi:10.1016/0020-0190(88)90170-6 (Ebert 1988, computing
Eulerian trails).
The direct `EulerianPath -> ILP` rule (#1025) is out of scope for
this PR and will follow separately.
Closes #1024
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Biology-paper prize-collecting Steiner forest: given a network G with
nonnegative vertex prizes p(v), nonnegative edge costs c(e), and
tradeoff coefficients beta, omega, find a forest subgraph
F = (V_F, E_F) minimizing
beta * sum_{v notin V_F} p(v) + sum_{e in E_F} c(e) + omega * kappa(F)
where kappa(F) is the number of tree components (singleton selected
vertices count). Generalizes prize-collecting Steiner tree from one
connected tree to a forest; the artificial-root trick is deliberately
kept out of the base model and will live in the companion reduction
rule.
- src/models/graph/prize_collecting_steiner_forest.rs:
PrizeCollectingSteinerForest<G, W> with dims = vec![2; n+m] (vertex
bits then edge bits), Min<W::Sum> objective. Feasibility checks
edges-incident-to-selected-vertices and forest acyclicity; infeasible
→ Min(None). Canonical example via inventory from the issue's
3-vertex path with optimum [1,1,1, 1,0] value 5 (cost 1 + omega*2
components). declare_variants! default (SimpleGraph,i32) plus
(SimpleGraph,f64). Complexity 2^(num_vertices+num_edges).
- src/unit_tests/models/graph/prize_collecting_steiner_forest.rs:
13 tests — creation, evaluate-optimum, evaluate-full-path (value 9),
evaluate-three-singletons (value 6), evaluate-empty-forest
(value 12), evaluate-edge-without-endpoint-infeasible,
evaluate-cycle-infeasible (triangle selected entirely),
brute-force solver, serialization, f64 variant, panic guards.
- problemreductions-cli/: new --vertex-prizes / --edge-costs / --beta /
--omega flags via schema-driven create; mapping and fixture updates.
- docs/paper: problem-def block with worked example breakdown
(omitted-prize / edge-cost / component terms summing to 5);
display-name; Crossref-verified BibTeX for both Tuncbag et al.
papers (JCB 2013 and RECOMB 2012).
References: doi:10.1089/cmb.2012.0092 (Tuncbag et al. 2013, JCB);
doi:10.1007/978-3-642-29627-7_31 (Tuncbag et al. 2012, RECOMB).
The direct `PrizeCollectingSteinerForest -> SteinerTree` rule (#1027)
is out of scope for this PR and will follow separately.
Closes #1026
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Lexicographic objective on a directed multigraph with source s, sink t,
arc capacities u_e, and arc costs c_e: first maximize the s-t flow
value |f|, then among maximum-value flows minimize total arc cost
sum_e c_e f_e. Captures the CellRouter (Lummertz da Rocha et al. 2018)
model directly.
Architectural carve-out: the repo's Problem trait is discrete, so the
implementation restricts to INTEGRAL flows with dims=[c_e+1; m]. This
mirrors the existing MinimumEdgeCostFlow precedent and stays sound
for any rational instance by scaling. Documented in the module doc.
Lex encoding: Min<i64> with combined scalar
score = M * (max_possible_flow - flow_value) + cost
where M = sum_e c_e * u_e + 1 dominates any feasible cost — so lower
scores always prefer higher flow value first, breaking ties by lower
cost. Infeasible (capacity / conservation violations) → Min(None).
- src/models/graph/minimum_cost_maximum_flow.rs:
MinimumCostMaximumFlow { graph: DirectedGraph, source, sink,
capacities: Vec<i64>, costs: Vec<i64> }. Inherent helpers
flow_value(config) and total_cost(config) for tests. Canonical
example via inventory: V={0,1,2,3}, arcs [(0,1),(0,2),(1,2),
(1,3),(2,3)], capacities [2,1,1,1,2], costs [1,0,0,1,2] — optimum
config [2,1,1,1,2] with value 3 and cost 7. ProblemSchemaEntry +
ProblemSizeFieldEntry (num_vertices, num_arcs). declare_variants!
default with complexity (num_vertices+num_arcs)^6 (a conservative
polynomial placeholder justified by the LP formulation).
- src/unit_tests/models/graph/minimum_cost_maximum_flow.rs: 9 tests
covering creation, evaluate-optimum, evaluate-suboptimal-feasible,
evaluate-capacity-exceeded (infeasible), evaluate-conservation-
violated (infeasible), brute-force solver returning value 3 cost 7,
serialization, and the lex-tiebreaker test on a 4-vertex bottleneck
instance where two distinct max-value flows (value 1) exist with
costs 1 and 5 — brute-force must pick the cheaper one. The
tiebreaker test directly addresses the check-issue warning that
the original example admits a unique max-flow.
- problemreductions-cli/: new --source / --sink (usize) flags wired
via schema-driven create; --graph (DirectedGraph), --capacities,
--costs reused from the MECF wiring.
- docs/paper: problem-def block explaining the lex objective and the
integral-flow restriction, worked example with value/cost
breakdown; display-name; Crossref-verified BibTeX for
Lummertz da Rocha et al. 2018 (doi:10.1038/s41467-018-03214-y);
MIT 6.854 min-cost-flow notes as a @misc entry with URL.
References: doi:10.1038/s41467-018-03214-y (CellRouter, Nature Comms
2018); MIT 6.854 scribe notes for the standard min-cost-flow
equivalence.
The direct `MinimumCostMaximumFlow -> MinimumCostCirculation` rule
(#1031) is out of scope for this PR and will follow separately.
Closes #1029
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Classical minimum-cost circulation on a directed multigraph with
finite arc capacities u_e ≥ 0 and signed arc costs a_e ∈ R: find
g: E→R_{≥0} satisfying capacity bounds (0 ≤ g_e ≤ u_e) and flow
conservation at every vertex, minimizing sum_e a_e g_e.
This is the exact companion target for `MinimumCostMaximumFlow`
(reduction #1031) — the standard MCMF → MCCirc reduction uses a
sufficiently negative return arc from sink to source, which is why
signed costs must be supported in the base model.
Architectural carve-out (same as MinimumCostMaximumFlow #1029 and
MinimumEdgeCostFlow): the discrete Problem trait restricts to
INTEGRAL circulation with dims=[c_e+1; m]; sound for any rational
instance by scaling. Documented in the module doc.
- src/models/graph/minimum_cost_circulation.rs:
MinimumCostCirculation { graph: DirectedGraph, capacities: Vec<i64>,
costs: Vec<i64> } — no source/sink, conservation at every vertex.
Min<i64> objective; capacity-or-conservation violations → Min(None).
ProblemSchemaEntry + ProblemSizeFieldEntry (num_vertices, num_arcs).
declare_variants! default with conservative polynomial placeholder
(num_vertices+num_arcs)^6. Canonical example via inventory — a
3-vertex two-cycle instance discriminating between four feasible
alternatives (zero, cycle-A-only -2, cycle-B-only -3, both at
capacity -5) so round-trip tests have real discriminatory power,
addressing the check-issue warning about the issue's 2-vertex
example being too small.
- src/unit_tests/models/graph/minimum_cost_circulation.rs: 11 tests
covering creation, evaluate-optimum (config [2,2,1,1] → Min(-5)),
evaluate-zero, evaluate-cycle-A-only (-2), evaluate-cycle-B-only
(-3), evaluate-half-cycle-A (-4), evaluate-infeasible (capacity
exceeded, conservation violated), brute-force solver, serialization,
negative-cost-only-cycle smoke.
- problemreductions-cli/: --graph (DirectedGraph), --capacities,
--costs reused from MECF/MCMF wiring; new schema mapping for MCCirc.
- docs/paper: problem-def block with the two-cycle worked example
spelled out (per-unit costs, capacity bottlenecks), display-name
entry; reuses the existing mit6854MinCostFlow @misc bib entry
added with MCMF — no new references.bib changes.
References: MIT 6.854 (S2021) min-cost flow algorithms notes (shared
with #1029).
The direct `MinimumCostMaximumFlow -> MinimumCostCirculation` rule
(#1031) is out of scope for this PR and will follow separately.
Closes #1030
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Consensus-string problem under Hamming distance: given an alphabet
Σ = {0,...,q-1} and n equal-length strings s_1,...,s_n ∈ Σ^m, find a
center string c ∈ Σ^m minimizing max_i d_H(c, s_i). NP-hard (Frances
& Litman 1997, Lanctot et al. 1999), with extensive FPT and PTAS
literature (Gramm & Niedermeier 2003, Ma & Sun 2009, Li/Ma/Wang 2002).
Distinct from ClosestSubstring — every input string has the same
length as the center, so there is no window-selection decision.
- src/models/misc/closest_string.rs: ClosestString { alphabet_size,
strings: Vec<Vec<usize>> }. Validating constructor panics on
length mismatch or out-of-alphabet symbol. dims = vec![q; m].
Min<i64> objective (always feasible — every config in the cube is
a syntactically valid center). Inherent getters alphabet_size,
num_strings, string_length, total_length. ProblemSchemaEntry +
ProblemSizeFieldEntry with all four size fields. declare_variants!
default with complexity alphabet_size^string_length. Canonical
example via inventory from the issue's 4-string binary length-3
instance (optimal center [0,0,0], radius 2).
- src/unit_tests/models/misc/closest_string.rs: 11 tests covering
creation, evaluate at three different centers (c=000 → 2, c=100
→ 3, c=111 → 3), brute-force solver returning radius 2 over 8
candidates, three panic guards (empty input, length mismatch,
out-of-alphabet symbol), a q=3 length-2 ternary smoke test
(radius 2 over 9 candidates), and serialization.
- problemreductions-cli/: schema-driven create wires --alphabet-size
(usize) and --strings (Vec<Vec<usize>>) — reuses the existing
Vec<Vec<usize>> parser added with #994.
- docs/paper: problem-def block with all four Hamming distances
spelled out for c=000; display-name entry; Crossref-verified
Li/Ma/Wang 2002 (JACM) bib entry.
Reference: doi:10.1145/506147.506150 (Li, Ma & Wang 2002, JACM).
The direct `ClosestString -> ILP` rule (#1034) is out of scope for
this PR and will follow separately.
Closes #1032
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Window-selection generalization of ClosestString (#1032): given an alphabet Σ, n strings (NOT necessarily equal length), and a substring length ℓ, find a center c ∈ Σ^ℓ and start positions p_i selecting length-ℓ windows s_i[p_i .. p_i+ℓ) minimizing max_i d_H(c, s_i[p_i .. p_i+ℓ)). Motif-discovery model — NP-hard, no PTAS in general (Li, Ma & Wang 2002 JACM; Marx 2008). ClosestString is the special case where every input string has length exactly ℓ (single window per string). - src/models/misc/closest_substring.rs: ClosestSubstring { alphabet_size, strings: Vec<Vec<usize>>, substring_length }. Validating constructor panics on empty input, substring_length > min |s_i|, or out-of-alphabet symbol. dims concatenates ℓ center slots (domain {0..q-1}) with n window-start slots (domain {0..W_i-1} where W_i = |s_i| - ℓ + 1). Min<i64> objective, always feasible since every config in the cube is syntactically valid. Inherent getters alphabet_size, num_strings, substring_length, total_length, total_num_windows, num_window_choice_product (with saturating multiplication). ProblemSchemaEntry + ProblemSizeFieldEntry. declare_variants! default with complexity alphabet_size^substring_length * num_window_choice_product. Canonical example via inventory from the issue's 3 binary strings with ℓ=3 — optimum center [0,1,0] with window picks (0,1,0), radius 1 over 216 candidate configs. - src/unit_tests/models/misc/closest_substring.rs: 11 tests covering creation, evaluate at optimum (radius 1), evaluate at center [0,0,0] with all-zero windows (radius 2), evaluate at center [1,1,1] (radius >=1), brute-force solver, ClosestString reduction validation (substring_length = string_length → matches the #1032 canonical's radius 2), three panic guards (empty input, length mismatch, out-of-alphabet symbol), and serialization roundtrip. - problemreductions-cli/: schema-driven create wires --alphabet-size + --strings (reused from #1032) plus the new --substring-length (usize) flag. - docs/paper: problem-def block with the worked example listing all three window picks and per-window Hamming distances; display-name entry. Reuses the existing Li/Ma/Wang 2002 JACM BibTeX entry added with #1032 — no references.bib changes. Reference: doi:10.1145/506147.506150 (Li, Ma & Wang 2002, JACM) shared with #1032. The direct `ClosestSubstring -> ILP` rule (#1035) is out of scope for this PR and will follow separately. Closes #1033 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Classical protein-structure contact-map alignment: given two ordered
contact graphs G_1=(V_1,E_1) and G_2=(V_2,E_2), find an order-preserving
partial injective map f: V_1 → V_2 ∪ {unmatched} maximizing the number
of contacts {i,k} ∈ E_1 such that both i, k are matched and
{f(i), f(k)} ∈ E_2. Aliases: CMO, MaxCMO.
NP-hard with substantial literature on exact algorithms and integer
programming (Andonov, Malod-Dognin & Yanev 2011; Xie & Sahinidis 2007).
- src/models/graph/maximum_contact_map_overlap.rs:
MaximumContactMapOverlap { num_vertices_1, contacts_1, num_vertices_2,
contacts_2 }. Validating constructor normalizes each pair to sorted
form (u<v), rejects self-loops, duplicates, and out-of-range
endpoints. dims = vec![num_vertices_2 + 1; num_vertices_1] (value 0
encodes unmatched; value j+1 maps to vertex j of G_2). Max<i64>
objective; non-injective or non-order-preserving matched values →
Max(None). ProblemSchemaEntry + ProblemSizeFieldEntry; inherent
getters num_vertices_1/_2 and num_contacts_1/_2. declare_variants!
default with complexity (num_vertices_2+1)^num_vertices_1.
Canonical example via inventory: G_1 with 4 vertices and contacts
{(0,2),(1,3)}, G_2 with 5 vertices and contacts {(0,2),(0,3),(1,4)}
— optimum [1,2,4,5] preserves both contacts → Max(Some(2)).
- src/unit_tests/models/graph/maximum_contact_map_overlap.rs: 17 tests
covering creation, evaluate at optimum, all-unmatched, single-match,
non-injective Max(None), non-order-preserving Max(None), suboptimal
feasible (config [1,2,3,4] preserves 1 of 2 contacts), brute-force
solver returning Max(2), wrong-length and out-of-range guards,
serialization, alias resolution for CMO/MaxCMO, and three panic
guards (self-loop, duplicate contact, endpoint out of range).
- problemreductions-cli/: schema-driven create wires --num-vertices-1
/ --num-vertices-2 / --contacts-1 / --contacts-2 (Vec<(usize,usize)>
parser) via the existing CreateArgs + flag_map + tests fixture.
- docs/paper: problem-def block with the alignment table and the two
preserved-contact bullets; display-name; Crossref-verified BibTeX
for both Andonov-Malod-Dognin-Yanev 2011 and Xie-Sahinidis 2007
JCB papers (with N{\"o}el encoded per repo umlaut convention).
References: doi:10.1089/cmb.2009.0196 (Andonov, Malod-Dognin & Yanev
2011, JCB); doi:10.1089/cmb.2007.R007 (Xie & Sahinidis 2007, JCB).
The direct `MaximumContactMapOverlap -> ILP` rule (#1044) is out of
scope for this PR and will follow separately.
Closes #1043
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
isPANN
changed the title
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Coverage 97.93% 97.93%
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Net -83 lines across the four skill files touched by 694ef0c. auto-pipeline (-79): - Collapse Step 0a + 0b into a single picker block; the only difference was "filter by number" vs "sort and pick top" — now branched by whether the ISSUE env var is set. - Extract the boilerplate that was duplicated across all five subagent prompts (output-only-JSON-block contract, universal don'ts, malformed-JSON retry policy, severity vocabulary) into a single "Subagent Contract" section near the top. Each prompt now states only its scope and JSON shape. Drop the trailing "Reporting Contract" section (merged into the new one). - Trim the Board states table from 8 GraphQL IDs to the 3 columns the orchestrator actually writes (ready, on-hold, plus the Backlog it reads in Step 0). The IDs for In Progress / Review pool / Under review / Final review live in run-pipeline / review-pipeline where they are used. - Drop three rows from Common Mistakes that just echoed the spec (codex retry cap, increment SUBSTANTIVE_RETRIES, re-check after auto-fix); keep only the non-obvious cross-cutting traps. check-issue (-9 net): - Rule Check 5a no longer re-lists the literature fallback chain; one-line reference to Check 3c suffices. - Rule Check 5c verdict table drops the (severity: ...) annotations on Fail rows — severity classification is owned by auto-pipeline's Subagent Contract, not by check-issue itself. - Rule Check 5c drops the "cited reference does not contain the reduction" row that explicitly admitted overlap with Check 3c; add a one-line note that 3c handles that case. review-structural (-19): - Step 4b-4 (pred --via spot-check) was hedged out of its own purpose with a "fall back to 4b-2" escape hatch. Rewrite as a short focused step that uses pred --via when wired and is skipped (with a note) otherwise — no padding. review-quality (~2 net): - Replace the 4-criterion expansion of the round-trip rule (which was copy-pasted from review-structural Step 4b-3) with a single pointer to that source-of-truth section. Per the existing feedback_skill_no_duplication memory. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- MinimumDiscretePlanarInverseKinematics: simplify complexity string from "num_links * total_configurations" to "total_configurations" so it matches issue #994's stated O(prod_{j=1}^n m_j) baseline literally (the extra num_links factor was per-config feasibility-check work, not configs). - MinimumCostCirculation: add test_minimum_cost_circulation_issue_example_1030 that constructs issue #1030's verbatim 2-vertex example (arcs 0->1 cap=2 cost=3 and 1->0 cap=1 cost=-5, optimum -2). The existing richer 3-vertex canonical instance is kept as the primary discriminator.
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Summary
Serial batch-add of 12 Model issues from Backlog to one branch (
batch-add-models), driven by the new/auto-pipelineorchestrator. Each model: full Rust impl + unit tests + schema-driven CLI + Typstproblem-defentry + Crossref-verified BibTeX. 1 of the originally targeted 13 issues is parked on OnHold — see below.Foundation (commit 694ef0c)
/auto-pipeline: orchestrator that drives one Backlog issue from quality gate to Final review via fresh-context subagents (check-issue,fix-issue,run-pipeline,review-pipeline). Substantive issue-body problems route to codex xhigh; fundamental-flaw-without-reference issues park on OnHold.check-issue: new Rule Check 5 (Completeness, fail labelIncomplete) — mandatory literature + codebase + hand-trace on ≥2 corner cases for every[Rule]issue.review-structural: new Step 4b (Round-trip Execution, mandatory for Rule reviews) — reviewer mustcargo test --exact <name>, paste thetest result: okline, and confirm the test exercises all four phases of a real round-trip.review-quality: promoted "closed-loop without round-trip verification" to Critical with explicit red flags.Models added (12)
MinimumDiscretePlanarInverseKinematicsMaximumCoKPlexMaximumCommonEdgeSubgraphMaximumEdgeWeightedKCliqueHighlyConnectedDeletionEulerianPathPrizeCollectingSteinerForestMinimumCostMaximumFlowM*(max-flow)+costencoding; integral-flow carve-out (mirrors MECF)MinimumCostCirculationClosestStringq^mbrute-forceClosestSubstring[q;ℓ]++[W_i]MaximumContactMapOverlapEach model commits closes its issue via
Closes #<n>. Companion[Rule] X → ILP/SteinerTree/...issues are explicitly deferred to follow-up PRs.OnHold (1)
MaximumAcyclicAgreementForest— substantive errors in the issue body that need human re-derivation:T_1=((a,b),(c,d))vsT_2=((a,c),(b,d)), but the rooted SPR distance is 1 so MAAF should be smaller. Hand-checking the obvious 2-block partitions failed the edge-disjoint requirement, so the precise correct block structure isn't trivially derivable.Final-review fixes (commit e346156)
declare_variants!complexity fromnum_links * total_configurationstototal_configurationsso it matches the issue's literalO(prod_{j=1}^n m_j)baseline.test_minimum_cost_circulation_issue_example_1030which constructs the issue's verbatim 2-vertex example (arcs0→1cap=2 cost=3 and1→0cap=1 cost=-5, optimum -2). Existing richer 3-vertex canonical kept as the primary discriminator.Test plan
make fmtcleanmake clippycleanmake testgreen — ~5200 lib + 150 doc + integration suites all pass on the final commitmake checkon CI after push — CI run 26412628216 green (5m50s) on commit e346156make paperbuilds the Typst PDF cleanly — verified locally on commit e346156 (no warnings, 202 schemas exported)pred create --example <Model> | pred solve --solver brute-forcefor each of the 12 new models — 11/12 work via bare name;MaximumCoKPlexrequires explicit/i32disambiguation (same pattern as existingMaximumClique—Onedefault but example only registered fori32; not a regression)MinimumEdgeCostFlowM*(max_flow - value) + cost; alternative: tuple Value type — could be revisited later) — accepted;M > Σ cost_e·c_estrictly upper-bounds any feasible cost; integrates cleanly withMinaggregateBahiense / Manić / Piva / de Souza; Soulé entry matches DOI10.1371/journal.pcbi.1008990)Luis Gouveia and Pedro Martins)Falk H{"u}ffner)J{\o}rgen Bang-Jensen,J{"u}rgen Ebert)🤖 Generated with Claude Code