# vtk-0001: CWE-407 — O(C×npts²) linear dedup scan in vtkStaticCleanPolyData
# vtk-0002: CWE-407 — O(numPts×numLabels) linear label-set scan in vtkGeneralizedSurfaceNets3D

---

## vtk-0001

### Severity
HIGH

### File
`Filters/Core/vtkStaticCleanPolyData.cxx:257,293,343,403`

### Description
`vtkStaticCleanPolyData::RequestData()` deduplicates point IDs within each
cell using a `std::vector<vtkIdType> cellIds` maintained per cell.  For each
point in the cell the code calls `std::find(cellIds.begin(), cellIds.end(),
ptId)` before appending to the vector.  The pattern appears four times for
the four cell types: verts, lines, polys, and triangle strips.

The outer loop iterates over all C cells in the mesh.  For each cell the
inner loop iterates npts times and each iteration does an O(k) linear scan
(where k grows from 0 to npts−1).  Total cost per cell: O(npts²).  Total
cost: O(C × npts²).

For a triangulated surface with C = 10 000 000 triangles this is
O(C × 9) ≈ 90 M ops — manageable.  But for strip-based or high-valence mesh
data (npts up to 64–256) the cost becomes O(C × npts²) = O(C × 65536) ops,
a 7 000× regression over the expected O(C × npts) cost.

The source comment even notes: "Just use a vector to keep track of unique
ids — it's a small set so find() will execute relatively fast."  This is
only true when npts is always small, but VTK processes arbitrary meshes.

### Root Cause
`cellIds` is a `std::vector<vtkIdType>`.  Deduplication via linear scan is
O(k) per point.  Replacing with `std::unordered_set<vtkIdType>` reduces the
membership test to O(1) amortized, cutting deduplication from O(npts²) to
O(npts) per cell.

### Fix
Replace `std::vector<vtkIdType> cellIds` with `std::unordered_set<vtkIdType>
seenIds` for the dedup check; accumulate the insertion-ordered result in a
separate `std::vector` only when building the output cell.

### Speedup
At npts = 64 (strip with 64 points): 64²/64 = 64× per cell.
At npts = 256: 256× per cell.
Asymptotic: O(C × npts²) → O(C × npts).

### Affected Operations
- `vtkStaticCleanPolyData::RequestData()` — used as a preprocessing step
  before virtually every VTK geometry pipeline (surface nets, voronoi,
  ghost-cell generation, smoothing, etc.)

---

## vtk-0002

### Severity
HIGH

### File
`Filters/Meshing/vtkGeneralizedSurfaceNets3D.cxx:1150`

### Description
When no explicit labels are provided, `RequestData()` collects the unique
set of region IDs by iterating all numPts point scalars and calling
`std::find(autoLabels.begin(), autoLabels.end(), regionId)` before
appending to `autoLabels`:

```cpp
for (vtkIdType i = 0; i < numPts; ++i) {
    double regionId = static_cast<double>(regions->GetValue(i));
    if (regionId >= 0 &&
        std::find(autoLabels.begin(), autoLabels.end(), regionId) == autoLabels.end())
    {
        autoLabels.push_back(regionId);
    }
}
```

Cost: O(numPts × numLabels).  For a 50 M-point segmentation volume with
200 tissue classes: 50M × 200 = 10^10 comparisons where O(numPts) suffices.

### Root Cause
`autoLabels` is a `std::vector<double>`.  The uniqueness check is a linear
scan.  An `std::unordered_set<double>` provides O(1) membership.

### Fix
Use `std::unordered_set<double>` for the existence check during collection,
then move the sorted result into a vector if ordering is needed.

### Speedup
At numPts = 50 000 000, numLabels = 200: 200× speedup.
Asymptotic: O(numPts × numLabels) → O(numPts).

### Affected Operations
- `vtkGeneralizedSurfaceNets3D::RequestData()` — called when processing
  multi-label segmentation volumes (medical imaging, simulation data)