BENCHMARKING.md

@@ -15,16 +15,25 @@ python3 benchmarks/run.py --binary build-benchmark/partridge_benchmark \
 The default policy is one unrecorded warm-up followed by five repetitions per
 case, with a 600-second timeout for each process.  Solver stdout is captured;
 the probe renders into an in-memory stream so grids do not perturb terminal I/O.
-Override the policy with `--orders`, `--warmup`, `--repetitions`, and
-`--timeout`.  Order 9 uses the constructive odd-order path, searching order 8
-and then tiling the enlarged border, so it is suitable for normal local
-benchmarking:
+Override the policy with `--orders`, `--warmup`, `--repetitions`, `--timeout`,
+and `--candidate-order`.  Ascending candidate sizes are the production default.
+Order 9 uses the constructive odd-order path, searching order 8 and then tiling
+the enlarged border, so it is suitable for normal local benchmarking:
 
 ```sh
 python3 benchmarks/run.py --binary build-benchmark/partridge_benchmark \
   --orders 8 9 --warmup 1 --repetitions 5 --timeout 60 > benchmark.json
 ```
 
+Use `--direct-search` when benchmarking the skyline core rather than the public
+even-predecessor construction used for odd orders from 9 onwards:
+
+```sh
+python3 benchmarks/run.py --binary build-benchmark/partridge_benchmark \
+  --orders 6 7 8 9 --warmup 1 --repetitions 5 --timeout 60 \
+  --candidate-order ascending --direct-search > direct.json
+```
+
 The JSON contains every run and median, range, and median absolute deviation
 for solve, construction, independent validation, and rendering.  Direct-search
 cases report zero construction time: their setup and allocation remain part of
@@ -59,6 +68,52 @@ Do not use wall-clock thresholds as correctness checks.  Keep the generated
 JSON outside version control unless it is being deliberately added as a named
 comparison baseline.
 
+## Smallest-valley skyline
+
+The solver stores one filled height per board column instead of one value per
+cell.  Equal adjacent heights form conceptual vertical bars.  A valley is a
+maximal bar lower than both neighbours, with board edges treated as bars of
+full board height.  Each node scans for the smallest-width valley, breaking
+ties by lower height and then leftmost position, and tries every available
+square which fits at that valley's far-left edge.
+
+This branching remains complete: the bottom-left cell of the selected valley
+must be covered, a square covering it cannot begin to the left across the
+taller neighbour, and it cannot extend beyond the equal-height run without
+overlap or leaving an unreachable hole.  Trying every fitting available size
+therefore includes the placement used by every possible completion.
+
+For board width `W` and order `n`, the skyline scan is `O(W)`.  A node tries at
+most `n` candidates and each placement or exact undo changes at most `n`
+heights, giving `O(W + n^2)` local work.  The skyline, multiplicities,
+placements, and recursion stack use `O(W + n^2)` state, compared with the
+former `O(W^2)` cell grid.
+
+One-run exploratory measurements used the issue #4 dirty worktree at base
+commit `0a7ce1e`, Apple Clang 21.0.0, `-O3 -DNDEBUG`, macOS arm64, one worker,
+no warm-up, and a 15-second timeout.  Every completed result passed the
+independent benchmark validator:
+
+| Order | Result | Ascending time | Ascending nodes | Descending time | Descending nodes |
+| --- | --- | ---: | ---: | ---: | ---: |
+| 6 | infeasible | 0.040 s | 659,598 | 0.039 s | 659,598 |
+| 7 | infeasible | 3.103 s | 43,604,507 | 3.071 s | 43,604,507 |
+| 8 | solution | 0.585 s | 7,735,369 | 0.941 s | 12,186,125 |
+| 9 direct | solution | 3.831 s | 45,840,266 | timeout | unavailable |
+
+The infeasible orders exhaust the same tree in either direction.  Ascending
+was selected as the default because it reaches the first order-8 solution with
+36% fewer nodes and also completed direct order 9 within the timeout;
+descending direct order 9 did not.
+
+A direct ascending order-10 probe exceeded 20 seconds.  Public order 10 is
+also a direct search, and public order 11 first searches order 10 before using
+odd-predecessor construction.  Consequently neither 10 nor 11 is in the
+routine correctness suite: doing so would test the same unresolved order-10
+search bottleneck, while the existing route-boundary test still verifies that
+11 selects construction.  Revisit both sizes when order 10 completes within a
+practical test budget.
+
 ## Post-correctness baseline
 
 This framework starts from commit `ce39d0a` after the rendering assertion fix

CMakeLists.txt

@@ -24,6 +24,7 @@ if(BUILD_TESTING)
   add_test(NAME solver-small COMMAND partridge_tests solver-small)
   add_test(NAME solver-completion COMMAND partridge_tests solver-completion)
   add_test(NAME search-counters COMMAND partridge_tests search-counters)
+  add_test(NAME skyline-search COMMAND partridge_tests skyline-search)
   find_package(Python3 COMPONENTS Interpreter)
   if(Python3_Interpreter_FOUND)
     add_test(NAME benchmark-format

TESTING.md

@@ -13,9 +13,13 @@ The tests independently check board dimensions, square multiplicities, bounds,
 overlap, and complete coverage.  They cover small unsatisfiable solver inputs, a
 known order-8 solution, invalid placement diagnostics, and construction of an
 order-9 solution from the order-8 fixture.  The routed order-9 solver test
-checks that its search counters exactly match order 8.  The rendering test also
-formats the known order-8 solution and checks the resulting grid dimensions and
-coverage.
+checks that its search counters exactly match order 8.  The skyline tests check
+smallest-width valley selection and deterministic tie-breaking, validate an
+order-8 result with descending candidates, and independently validate a direct
+order-9 search with ascending candidates.  That direct test is deliberately
+separate from the public order-9 route, which uses even-predecessor
+construction.  The rendering test also formats the known order-8 solution and
+checks the resulting grid dimensions and coverage.
 
 When Python is available, `reference-support` also tests the dependency-free
 placement JSON validator.  If the optional OR-Tools package is present, it
@@ -45,6 +49,4 @@ ctest --test-dir build-ubsan --output-on-failure
 ```
 
 The sanitizer flags shown are supported by Clang and GCC.  Other compilers may
-require different flags.  A feasible solver run currently exposes the
-pre-existing defect tracked by issue #14; the test additions deliberately do
-not include its separate fix.
+require different flags.

benchmarks/benchmark.cc

@@ -26,26 +26,29 @@ namespace {
     double construction_seconds;
   };
 
-  auto solve(std::uint64_t order, bool instrument, SearchCounters &counters)
+  auto solve(std::uint64_t order, bool instrument,
+             CandidateOrder candidate_order, bool direct_search,
+             SearchCounters &counters)
       -> TimedSolution {
     auto const predecessor_order =
-        uses_odd_construction(order) ? order - 1 : order;
+        !direct_search && uses_odd_construction(order) ? order - 1 : order;
     auto const search_begin = Clock::now();
     auto predecessor =
         instrument
-            ? search_solution_instrumented(predecessor_order, counters)
-            : search_solution(predecessor_order);
+            ? search_solution_instrumented(predecessor_order, counters,
+                                           candidate_order)
+            : search_solution(predecessor_order, candidate_order);
     auto const search_end = Clock::now();
 
     auto const construction_begin = Clock::now();
-    auto result = uses_odd_construction(order)
+    auto result = !direct_search && uses_odd_construction(order)
                       ? construct_odd_solution(order, std::move(predecessor))
                       : std::move(predecessor);
     auto const construction_end = Clock::now();
     return {
         std::move(result),
         seconds(search_begin, search_end),
-        uses_odd_construction(order)
+        !direct_search && uses_odd_construction(order)
             ? seconds(construction_begin, construction_end)
             : 0.0,
     };
@@ -90,8 +93,9 @@ namespace {
 }
 
 int main(int argc, char **argv) {
-  if (argc != 3) {
-    std::cerr << "usage: partridge_benchmark ORDER counters|plain\n";
+  if (argc < 3 || argc > 5) {
+    std::cerr << "usage: partridge_benchmark ORDER counters|plain "
+                 "[ascending|descending] [public|direct]\n";
     return 2;
   }
   auto const order = static_cast<std::uint64_t>(std::strtoull(argv[1], nullptr, 10));
@@ -100,9 +104,26 @@ int main(int argc, char **argv) {
     std::cerr << "counter mode must be counters or plain\n";
     return 2;
   }
+  auto const candidate_order =
+      argc < 4 || std::string_view(argv[3]) == "ascending"
+          ? CandidateOrder::ascending
+          : CandidateOrder::descending;
+  if (argc >= 4 && std::string_view(argv[3]) != "ascending" &&
+      std::string_view(argv[3]) != "descending") {
+    std::cerr << "candidate order must be ascending or descending\n";
+    return 2;
+  }
+  auto const direct_search =
+      argc == 5 && std::string_view(argv[4]) == "direct";
+  if (argc == 5 && std::string_view(argv[4]) != "public" &&
+      std::string_view(argv[4]) != "direct") {
+    std::cerr << "search route must be public or direct\n";
+    return 2;
+  }
 
   SearchCounters counters;
-  auto timed = solve(order, instrument, counters);
+  auto timed =
+      solve(order, instrument, candidate_order, direct_search, counters);
 
   auto const validation_begin = Clock::now();
   auto const validation_ok = valid(order, timed.result);
@@ -120,6 +141,12 @@ int main(int argc, char **argv) {
       << "{\"schema_version\":1"
       << ",\"order\":" << order
       << ",\"instrumented\":" << boolean(instrument)
+      << ",\"candidate_order\":\""
+      << (candidate_order == CandidateOrder::ascending ? "ascending"
+                                                       : "descending")
+      << "\""
+      << ",\"search_route\":\""
+      << (direct_search ? "direct" : "public") << "\""
       << ",\"solved\":" << boolean(!timed.result.squares().empty())
       << ",\"valid\":" << boolean(validation_ok)
       << ",\"timing_seconds\":{\"solve\":" << timed.search_seconds

benchmarks/run.py

@@ -74,16 +74,16 @@ def environment(binary):
             "logical_cpus": os.cpu_count(),
         },
         "workers": 1,
-        "search_policy": "single-threaded, deterministic, largest-fitting-first",
+        "search_policy": "single-threaded, deterministic, smallest-width valley",
         "seed": None,
     }
 
 
-def run_once(binary, order, mode, timeout):
+def run_once(binary, order, mode, candidate_order, search_route, timeout):
     started = time.monotonic()
     try:
         process = subprocess.run(
-            [str(binary), str(order), mode],
+            [str(binary), str(order), mode, candidate_order, search_route],
             check=False,
             capture_output=True,
             text=True,
@@ -216,6 +216,12 @@ def main():
     parser.add_argument("--warmup", type=int, default=1)
     parser.add_argument("--repetitions", type=int, default=5)
     parser.add_argument("--timeout", type=float, default=600.0)
+    parser.add_argument(
+        "--candidate-order",
+        choices=("ascending", "descending"),
+        default="ascending",
+    )
+    parser.add_argument("--direct-search", action="store_true")
     parser.add_argument(
         "--measure-overhead",
         action="store_true",
@@ -241,11 +247,25 @@ def main():
         mode_results = {mode: {"runs": []} for mode in modes}
         for trial in range(args.warmup):
             for mode in trial_modes(modes, trial):
-                run_once(args.binary, order, mode, args.timeout)
+                run_once(
+                    args.binary,
+                    order,
+                    mode,
+                    args.candidate_order,
+                    "direct" if args.direct_search else "public",
+                    args.timeout,
+                )
         for trial in range(args.repetitions):
             for mode in trial_modes(modes, trial):
                 mode_results[mode]["runs"].append(
-                    run_once(args.binary, order, mode, args.timeout)
+                    run_once(
+                        args.binary,
+                        order,
+                        mode,
+                        args.candidate_order,
+                        "direct" if args.direct_search else "public",
+                        args.timeout,
+                    )
                 )
         for result in mode_results.values():
             result["summary"] = summarize(result["runs"])
@@ -270,6 +290,8 @@ def main():
             "warmup_runs": args.warmup,
             "measured_repetitions": args.repetitions,
             "per_run_timeout_seconds": args.timeout,
+            "candidate_order": args.candidate_order,
+            "search_route": "direct" if args.direct_search else "public",
             "stdout": "captured; rendered grid suppressed by probe",
         },
         "cases": cases,

main.cc

@@ -131,97 +131,6 @@ namespace {
     std::vector<Square> squares_;
   };
 
-  /** An N * N grid of characters. */
-  struct Grid {
-    // Type to use for the grid contents
-    using T = std::int_fast64_t;
-
-    /** Construct a grid of given side-length. */
-    explicit Grid(size_t length) : grid_(length * length, empty), length_(length) {
-    }
-
-    Grid(Grid const &other) = delete;
-
-    Grid(Grid &&other) noexcept = default;
-
-    Grid &operator=(Grid const &other) = delete;
-
-    Grid &operator=(Grid &&other) noexcept = default;
-
-    ~Grid() noexcept = default;
-
-    /** Get grid length */
-    [[nodiscard]] auto end() const noexcept -> size_t { return static_cast<size_t>(grid_.size()); }
-
-    /** Add a square to the grid. */
-    auto add(Square const &sq) noexcept -> void {
-      /* One would expect the fastest way to do this would be to have x be the
-       * fastest increasing index so we store [pos, pos + 1,..., pos+length, ...]
-       * But experimentation tells us this isn't so, and storing
-       * [pos, pos + length, ..., pos + 1, ...] is faster!
-       */
-      for (auto x = 0; x < sq.length(); ++x) {
-        for (auto y = sq.pos(); y < sq.pos() + sq.length() * length_; y += length_) {
-          grid_[x + y] = filled;
-        }
-      }
-    }
-
-    /** Clear a square from the grid. */
-    auto clear(Square const &sq) noexcept -> void {
-      for (auto x = 0; x < sq.length(); ++x) {
-        for (auto y = sq.pos(); y < sq.pos() + sq.length() * length_; y += length_) {
-          grid_[x + y] = empty;
-        }
-      }
-    }
-
-    /** \brief Get length of the largest square that fits at \a pos in the grid.
-     */
-    [[nodiscard]] auto largest_square(Pos pos, size_t n) const noexcept -> size_t {
-      assert(pos < end());
-
-      /* Because of how we walk through the grid (starting at 0,0 then increasing
-       * x followed by y) we can assume that if the position (b, y) is clear
-       * (i.e. a '.') then (b, y + i) is clear for all i > 0.
-       *
-       * This means we only need to look for the first non-clear position along the
-       * current row.
-       */
-      auto const pos_x = pos % length_;
-      auto const pos_y0 = pos - pos_x;
-      auto b = pos;
-      // Make sure we don't go looking in the next row.
-      auto const e = std::min(pos + n, pos_y0 + length_);
-      while (b < e) {
-        if (grid_[b] != empty) { break; }
-        ++b;
-      }
-      // Check that this length fits vertically as well.
-      auto const len = b - pos;
-      auto const pos_y = pos / length_;
-      auto const ye = std::min(pos_y + len, length_);
-      return ye - pos_y;
-    }
-
-    /** Get the next position to check starting at pos.
-     *
-     * Returns grid_.length() if no more positions available.
-     */
-    [[nodiscard]] auto next_pos(Pos pos) const noexcept -> Pos {
-      auto const b = grid_.begin() + static_cast<std::ptrdiff_t>(pos);
-      auto const p = std::find(b, grid_.end(), empty);
-      return p - grid_.begin();
-    }
-
-  private:
-    std::vector<T> grid_; ///< The grid
-    size_t length_; ///< Side length
-
-    static constexpr char empty = 0; ///< Character used for an empty cell.
-    static constexpr char filled = 1; ///< Character used for a filled cell,
-  };
-
   /** Get the n-th triangular number. */
   auto triangle_num(size_t n) noexcept -> size_t { return (n * (n + 1)) / 2; }
 
@@ -245,112 +154,155 @@ namespace {
     size_t completed_tasks = 0;
   };
 
-  /** Search directly for a solution to the \a n th Partridge problem.
-   *
-   * Returns the grid of the solution.
-   */
+  enum class CandidateOrder {
+    ascending,
+    descending,
+  };
+
+  /** A maximal level skyline segment which is lower than its neighbours. */
+  struct Valley {
+    size_t x;
+    size_t height;
+    size_t width;
+  };
+
+  /** Return the narrowest local valley, breaking ties by height then x. */
+  [[nodiscard]] auto smallest_valley(std::vector<size_t> const &skyline) noexcept
+      -> Valley {
+    Valley best{0, 0, skyline.size()};
+    bool found = false;
+    for (size_t begin = 0; begin < skyline.size();) {
+      auto end = begin + 1;
+      while (end < skyline.size() && skyline[end] == skyline[begin]) {
+        ++end;
+      }
+      auto const left_height =
+          begin == 0 ? skyline.size() : skyline[begin - 1];
+      auto const right_height =
+          end == skyline.size() ? skyline.size() : skyline[end];
+      auto const lower_than_left = skyline[begin] < left_height;
+      auto const lower_than_right = skyline[begin] < right_height;
+      auto const width = end - begin;
+      if (lower_than_left && lower_than_right &&
+          (!found || width < best.width ||
+           (width == best.width && skyline[begin] < best.height) ||
+           (width == best.width && skyline[begin] == best.height &&
+            begin < best.x))) {
+        best = {begin, skyline[begin], width};
+        found = true;
+      }
+      begin = end;
+    }
+    assert(found);
+    return best;
+  }
+
   template<bool Instrument>
-  auto search_solution_impl(size_t const n, SearchCounters *const counters) noexcept
-      -> Results {
-    /* Implementation is iterative, as opposed to recursive.
-     *
-     * The recursive implementation is easier to understand - but is
-     * slightly slower because of the repeated function calls (and
-     * entry/exit).
-     *
-     * The basic algorithm is to start at the origin of the grid we
-     * want to place squares on and iterate over the permutations of
-     * available squares until we find one that fits.
-     */
-
-    // grid is our in-progress grid of square positions.
-    auto const length = triangle_num(n);
-    Grid grid(length);
-
-    /* avail_sqs is a vector indexed by square length indicating how many
-     * squares are available.  Initially set up so that avail_sqs[i] = i.
-     */
-    Avail avail_sqs;
-    for (auto i = 0; i <= n; ++i) { avail_sqs.push_back(i); }
-
-    /* sqs is a vector used as a stack of the squares currently placed.
-     * We reserve the length we need so as not to have too many allocations.
-     */
-    std::vector<Square> sqs;
-    sqs.reserve(length);
-
-    // Start at the origin with a square of longest side length.
-    Pos pos = 0;
-    size_t idx = n;
-
+  auto search_skyline(size_t const n, size_t const length,
+                      CandidateOrder const candidate_order,
+                      std::vector<size_t> &skyline, Avail &available,
+                      std::vector<Square> &squares,
+                      SearchCounters *const counters) noexcept -> bool {
     if constexpr (Instrument) {
       assert(counters != nullptr);
       ++counters->search_nodes;
     }
 
-    while (true) {
+    if (squares.size() == length) {
+      return true;
+    }
+
+    auto const valley = smallest_valley(skyline);
+    auto const largest =
+        std::min({n, valley.width, length - valley.height});
+    auto try_side = [&](size_t const side) {
       if constexpr (Instrument) {
         ++counters->loop_iterations;
       }
-      /* If the idx is 0 we've looked at all possible square lengths for this
-       * position, and they've failed.  Pop the last square of the stack, remove
-       * it from the grid and try the next smaller size in the same position.
-       */
-      if (idx == 0) {
-        // No squares on the stack -> failed to find a solution.
-        if (sqs.empty()) { break; }
-
-        auto sq = sqs.back();
-        sqs.pop_back();
-        grid.clear(sq);
-        ++avail_sqs[sq.length()];
-        if constexpr (Instrument) {
-          ++counters->backtracks;
-        }
-        pos = sq.pos();
-        idx = sq.length() - 1;
-        continue;
+      if (available[side] == 0) {
+        return false;
       }
 
-      // If there are no squares available of the current size try the next one.
-      if (avail_sqs[idx] == 0) {
-        --idx;
-        continue;
-      }
-
-      /* Place a square of side length idx at pos, push this onto the stack and
-       * set up to look at the next position.
-       */
-      auto const sq = Square(pos, idx);
       if constexpr (Instrument) {
         ++counters->attempted_placements;
       }
-      --avail_sqs[idx];
-      grid.add(sq);
-      sqs.push_back(sq);
+      --available[side];
+      std::fill_n(skyline.begin() + static_cast<std::ptrdiff_t>(valley.x),
+                  side, valley.height + side);
+      squares.emplace_back(valley.x + valley.height * length, side);
 
-      pos = grid.next_pos(pos + idx);
-
-      // Have we reached the end?  If so success!
-      if (pos == grid.end()) { break; }
+      if (search_skyline<Instrument>(n, length, candidate_order, skyline,
+                                     available, squares, counters)) {
+        return true;
+      }
 
+      squares.pop_back();
+      std::fill_n(skyline.begin() + static_cast<std::ptrdiff_t>(valley.x),
+                  side, valley.height);
+      ++available[side];
       if constexpr (Instrument) {
-        ++counters->search_nodes;
+        ++counters->backtracks;
       }
-      idx = grid.largest_square(pos, n);
+      return false;
+    };
+
+    if (candidate_order == CandidateOrder::ascending) {
+      for (size_t side = 1; side <= largest; ++side) {
+        if (try_side(side)) {
+          return true;
+        }
+      }
+    } else {
+      for (auto side = largest; side != 0; --side) {
+        if (try_side(side)) {
+          return true;
+        }
+      }
+    }
+    return false;
   }
 
-    return {length, sqs};
+  /** Search directly for a solution to the \a n th Partridge problem.
+   *
+   * The state is one filled height per board column.  At each node the
+   * narrowest local valley is found by a linear scan and candidates are tried
+   * at its far-left edge.  A placement or undo touches one entry per square
+   * column.  Scanning the profile costs O(board width); trying up to n
+   * candidates and updating up to n columns for each costs O(n^2), for
+   * O(board width + n^2) local work per node and the same total state.
+   */
+  template<bool Instrument>
+  auto search_solution_impl(size_t const n, CandidateOrder const candidate_order,
+                            SearchCounters *const counters) noexcept
+      -> Results {
+    auto const length = triangle_num(n);
+    std::vector<size_t> skyline(length);
+    Avail available(n + 1);
+    for (size_t side = 0; side <= n; ++side) {
+      available[side] = side;
+    }
+    std::vector<Square> squares;
+    squares.reserve(length);
+    static_cast<void>(search_skyline<Instrument>(
+        n, length, candidate_order, skyline, available, squares, counters));
+
+    return {length, std::move(squares)};
   }
 
-  auto search_solution(size_t const n) noexcept -> Results {
-    return search_solution_impl<false>(n, nullptr);
+  auto search_solution(
+      size_t const n,
+      CandidateOrder const candidate_order = CandidateOrder::ascending) noexcept
+      -> Results {
+    return search_solution_impl<false>(n, candidate_order, nullptr);
   }
 
   auto search_solution_instrumented(size_t const n,
-                                    SearchCounters &counters) noexcept -> Results {
+                                    SearchCounters &counters,
+                                    CandidateOrder const candidate_order =
+                                        CandidateOrder::ascending) noexcept
+      -> Results {
     counters = {};
-    return search_solution_impl<true>(n, &counters);
+    return search_solution_impl<true>(n, candidate_order, &counters);
   }
 
   /** Construct an odd-order solution from its even-order predecessor. */

tests/tests.cc

@@ -343,6 +343,42 @@ namespace {
     return failures;
   }
 
+  auto test_skyline_search() -> int {
+    int failures = 0;
+    auto const narrowest =
+        smallest_valley(std::vector<std::uint64_t>{4, 2, 2, 4, 0, 0, 0, 4});
+    failures += expect(
+        narrowest.x == 1 && narrowest.height == 2 && narrowest.width == 2,
+        "skyline did not select the smallest-width valley");
+
+    auto const tie =
+        smallest_valley(std::vector<std::uint64_t>{4, 1, 4, 4, 2, 4});
+    failures += expect(tie.x == 1 && tie.height == 1 && tie.width == 1,
+                       "skyline valley tie-break is not deterministic");
+
+    SearchCounters descending_counters;
+    auto const descending = search_solution_instrumented(
+        8, descending_counters, CandidateOrder::descending);
+    auto validation = validate(8, descending);
+    failures += expect(
+        validation.valid(),
+        "descending skyline search returned an invalid order-8 solution:\n" +
+            validation.text());
+
+    SearchCounters direct_nine_counters;
+    auto const direct_nine = search_solution_instrumented(
+        9, direct_nine_counters, CandidateOrder::ascending);
+    validation = validate(9, direct_nine);
+    failures += expect(
+        validation.valid(),
+        "direct skyline search returned an invalid order-9 solution:\n" +
+            validation.text());
+    failures += expect(
+        direct_nine_counters.search_nodes != descending_counters.search_nodes,
+        "direct order-9 coverage unexpectedly reused predecessor construction");
+    return failures;
+  }
+
   auto test_solver_completion() -> int {
     int failures = 0;
     for (auto const order: std::array<std::uint64_t, 2>{1, 8}) {
@@ -385,6 +421,9 @@ int main(int argc, char **argv) {
   if (test == "search-counters") {
     return test_search_counters();
   }
+  if (test == "skyline-search") {
+    return test_skyline_search();
+  }
   std::cerr << "unknown test: " << test << '\n';
   return 2;
 }