diff --git a/app/constants.py b/app/constants.py
index de49de1..8f606c6 100644
--- a/app/constants.py
+++ b/app/constants.py
@@ -1,5 +1,19 @@
-version = "v1.0.0"
+from pydantic import BaseModel
 
-# solver parameter
-n_max_precise = 9  # 10 takes 30s on a beefy desktop, 9 only 1.2s
-n_max = 500  # around 1 million with n^2
+# used for git tags
+version = "v1.0.1"
+
+
+class SolverSettings(BaseModel):
+    bruteforce_max_combinations: int
+    n_max: int
+
+
+# TODO should be startup parameter
+solverSettings = SolverSettings(
+    # Desktop with Ryzen 2700X:
+    # (4, 3, 2)=1260 => 0.1s, (4, 3, 3)=4200 => 0.8s, (5, 3, 3)=9240 => 8s
+    bruteforce_max_combinations=5000,
+    # that is already unusable x100, but the solver takes it easily
+    n_max=2000
+)
diff --git a/app/main.py b/app/main.py
index bc75f42..a4e337f 100644
--- a/app/main.py
+++ b/app/main.py
@@ -6,8 +6,7 @@
 from starlette.requests import Request
 from starlette.responses import HTMLResponse, PlainTextResponse
 
-from app.constants import version, n_max_precise, n_max
-
+from app.constants import version, solverSettings
 # don't mark /app as a sources root or pycharm will delete the "app." prefix
 # that's needed for pytest to work correctly
 from app.solver.data.Job import Job
@@ -84,15 +83,9 @@ def get_debug():
 
 
 @app.get("/constants", response_class=HTMLResponse)
-def get_debug():
-    static_answer = (
-        "Constants:"
-        "<ul>"
-        f"<li>Max Entries for perfect results: {n_max_precise}</li>"
-        f"<li>Max Entries for any result: {n_max}</li>"
-    )
-
-    return static_answer
+@app.get("/settings", response_class=HTMLResponse)
+def get_settings():
+    return solverSettings
 
 
 # content_type results in browser pretty printing
diff --git a/app/solver/data/Job.py b/app/solver/data/Job.py
index 3dfe5d8..9833345 100644
--- a/app/solver/data/Job.py
+++ b/app/solver/data/Job.py
@@ -1,11 +1,15 @@
-from typing import Iterator, List, Optional, Tuple
+from math import factorial, prod
+from typing import Iterator, Optional
 
-from pydantic import BaseModel
+from pydantic import BaseModel, ConfigDict, PositiveInt, NonNegativeInt, model_validator
 
 
 class TargetSize(BaseModel):
-    length: int
-    quantity: int
+    # frozen might be nice, but that would make reuse in solvers worse
+    model_config = ConfigDict(validate_assignment=True)
+
+    length: PositiveInt
+    quantity: PositiveInt
     name: Optional[str] = ""
 
     def __lt__(self, other):
@@ -19,13 +23,13 @@ def __str__(self):
 
 
 class Job(BaseModel):
-    max_length: int
-    cut_width: int = 0
-    target_sizes: List[TargetSize]
+    model_config = ConfigDict(frozen=True, validate_assignment=True)
 
-    # utility
+    max_length: PositiveInt
+    cut_width: NonNegativeInt = 0
+    target_sizes: tuple[TargetSize, ...]
 
-    def iterate_sizes(self) -> Iterator[Tuple[int, str | None]]:
+    def iterate_sizes(self) -> Iterator[tuple[int, str | None]]:
         """
         yields all lengths, sorted descending
         """
@@ -33,53 +37,37 @@ def iterate_sizes(self) -> Iterator[Tuple[int, str | None]]:
         # sort descending to favor combining larger sizes first
         for target in sorted(self.target_sizes, key=lambda x: x.length, reverse=True):
             for _ in range(target.quantity):
-                yield (target.length, target.name)
-
-    # NOTE: Not used, so not really refactored at the moment
-    def sizes_from_list(self, sizes_list: List[TargetSize]):
-        # known_sizes = {}
-        #
-        # # list to dict to make them unique
-        # for size in sizes_list:
-        #     if size.length in known_sizes:
-        #         known_sizes[size.length] += size.quantity
-        #     else:
-        #         known_sizes[size.length] = size.quantity
-
-        self.target_sizes = sizes_list
-
-    # NOTE: Can eventually be removed as it does nothing anymore
-    def sizes_as_list(self) -> List[TargetSize]:
+                yield target.length, target.name
+
+    def n_targets(self) -> int:
+        """
+        Number of possible combinations of target sizes
+        """
+        return sum([target.quantity for target in self.target_sizes])
+
+    def n_combinations(self) -> int:
         """
-        Compatibility function
+        Number of possible combinations of target sizes
         """
-        # back to list again for compatibility
-        return self.target_sizes
+        return int(factorial(self.n_targets()) / prod([factorial(n.quantity) for n in self.target_sizes]))
 
-    def assert_valid(self):
+    @model_validator(mode='after')
+    def assert_valid(self) -> 'Job':
         if self.max_length <= 0:
             raise ValueError(f"Job has invalid max_length {self.max_length}")
         if self.cut_width < 0:
             raise ValueError(f"Job has invalid cut_width {self.cut_width}")
         if len(self.target_sizes) <= 0:
             raise ValueError("Job is missing target_sizes")
-        if any(
-            target.length > (self.max_length - self.cut_width)
-            for target in self.target_sizes
-        ):
+        if any(target.length > self.max_length for target in self.target_sizes):
             raise ValueError("Job has target sizes longer than the stock")
-
-    def __len__(self) -> int:
-        """
-        Number of target sizes in job
-        """
-        return sum([target.quantity for target in self.target_sizes])
+        return self
 
     def __eq__(self, other):
         return (
-            self.max_length == other.max_length
-            and self.cut_width == other.cut_width
-            and self.target_sizes == other.target_sizes
+                self.max_length == other.max_length
+                and self.cut_width == other.cut_width
+                and self.target_sizes == other.target_sizes
         )
 
     def __hash__(self) -> int:
diff --git a/app/solver/data/Result.py b/app/solver/data/Result.py
index a57bbac..cae1dae 100644
--- a/app/solver/data/Result.py
+++ b/app/solver/data/Result.py
@@ -1,7 +1,7 @@
 from enum import unique, Enum
-from typing import List, Tuple, Optional
+from typing import Optional, TypeAlias
 
-from pydantic import BaseModel
+from pydantic import BaseModel, PositiveInt, model_validator
 
 from app.solver.data.Job import Job
 
@@ -13,12 +13,15 @@ class SolverType(str, Enum):  # str as base enables Pydantic-Schemas
     FFD = "FFD"
 
 
+ResultLength: TypeAlias = tuple[tuple[PositiveInt, str | None], ...]
+ResultLengths: TypeAlias = tuple[ResultLength, ...]
+
+
 class Result(BaseModel):
-    # allow IDs to skip redundant transmission for future versions
     job: Job
     solver_type: SolverType
-    time_us: Optional[int] = -1
-    lengths: List[List[Tuple[int, str]]]
+    time_us: Optional[int] = None
+    lengths: ResultLengths
 
     # no trimmings as they can be inferred from difference to job
 
@@ -38,11 +41,11 @@ def exactly(self, other):
                 and self.lengths == other.lengths
         )
 
+    @model_validator(mode='after')
     def assert_valid(self):
         self.job.assert_valid()
         if self.solver_type not in SolverType:
             raise ValueError(f"Result has invalid solver_type {self.solver_type}")
-        if self.time_us < 0:
-            raise ValueError(f"Result has invalid time_us {self.time_us}")
         if len(self.lengths) <= 0:
             raise ValueError("Result is missing lengths")
+        return self
diff --git a/app/solver/solver.py b/app/solver/solver.py
index 76020ae..5296161 100644
--- a/app/solver/solver.py
+++ b/app/solver/solver.py
@@ -2,23 +2,23 @@
 import copy
 from itertools import permutations
 from time import perf_counter
-from typing import Collection, Tuple, List
+from typing import Collection
 
-from app.constants import n_max_precise, n_max
+from app.constants import solverSettings
 from app.solver.data.Job import Job, TargetSize
-from app.solver.data.Result import SolverType, Result
+from app.solver.data.Result import SolverType, Result, ResultLengths
 
 
 def distribute(job: Job) -> Result:
     time: float = perf_counter()
 
-    lengths: List[List[Tuple[int, str]]]
+    lengths: ResultLengths
     solver_type: SolverType
 
-    if len(job) <= n_max_precise:
+    if job.n_combinations() <= solverSettings.bruteforce_max_combinations:
         lengths = _solve_bruteforce(job)
         solver_type = SolverType.bruteforce
-    elif len(job) <= n_max:
+    elif job.n_targets() <= solverSettings.n_max:
         lengths = _solve_FFD(job)
         solver_type = SolverType.FFD
     else:
@@ -29,40 +29,46 @@ def distribute(job: Job) -> Result:
     return Result(job=job, solver_type=solver_type, time_us=time_us, lengths=lengths)
 
 
-# CPU-bound
-# O(n!)
-def _solve_bruteforce(job: Job) -> List[List[Tuple[int, str | None]]]:
-    # failsafe
-    if len(job) > 12:
-        raise OverflowError("Input too large")
-
+# slowest, but perfect solver; originally O(n!), now much faster (see Job.n_combinations())
+def _solve_bruteforce(job: Job) -> ResultLengths:
     mutable_job = job.model_copy(deep=True)
+    mutable_job.model_config["frozen"] = False
+
     # allow "overflowing" cut at the end
     mutable_job.max_length += mutable_job.cut_width
 
-    # find every possible ordering (n! elements)
-    all_orderings = permutations(job.iterate_sizes())
-    # TODO: remove duplicates (due to "quantity")
-    all_orderings = permutations(mutable_job.iterate_sizes())
+    # find every possible ordering (`factorial(sum(sizes))` elements) and reduce to unique
+    all_orderings = set(permutations(mutable_job.iterate_sizes()))
 
-    # "infinity"
-    minimal_trimmings = len(mutable_job) * mutable_job.max_length
-    best_stock: List[List[Tuple[int, str | None]]] = []
+    # start at "all of it"
+    minimal_trimmings = mutable_job.n_targets() * mutable_job.max_length
+    best_results: list[list[list[tuple[int, str | None]]]] = []
 
-    # possible improvement: Distribute combinations to multiprocessing worker threads
+    # could distribute to multiprocessing, but web worker is parallel anyway
     for combination in all_orderings:
-        stocks, trimmings = _split_combination(
+        lengths, trimmings = _group_into_lengths(
             combination, mutable_job.max_length, mutable_job.cut_width
         )
         if trimmings < minimal_trimmings:
-            best_stock = stocks
+            best_stock = lengths
             minimal_trimmings = trimmings
-
-    return _sorted(best_stock)
-
-
-def _split_combination(
-        combination: Tuple[Tuple[int, str | None]], max_length: int, cut_width: int
+            best_results.clear()
+            best_results.append(best_stock)
+        elif trimmings == minimal_trimmings:
+            best_results.append(lengths)
+
+    # set creates random order of perfect results due to missing sorting, so sort for determinism
+    ordered = (sorted(
+        set([tuple(sorted(
+            [tuple(sorted(y, reverse=True)) for y in x], reverse=True)
+        ) for x in best_results]), reverse=True
+    ))
+    # TODO evaluate which result aligns with user expectations best
+    return _sorted(ordered[0])
+
+
+def _group_into_lengths(
+        combination: tuple[tuple[int, str | None], ...], max_length: int, cut_width: int
 ):
     """
     Collects sizes until length is reached, then starts another stock
@@ -71,18 +77,18 @@ def _split_combination(
     :param cut_width:
     :return:
     """
-    stocks: List[List[Tuple[int, str | None]]] = []
+    stocks: list[list[tuple[int, str | None]]] = []
     trimmings = 0
 
     current_size = 0
-    current_stock: List[Tuple[int, str | None]] = []
+    current_stock: list[tuple[int, str | None]] = []
     for size, name in combination:
         if (current_size + size + cut_width) > max_length:
             # start next stock
             stocks.append(current_stock)
             trimmings += _get_trimming(max_length, current_stock, cut_width)
             current_size = 0
-            current_stock: List[Tuple[int, str | None]] = []
+            current_stock = []
 
         current_size += size + cut_width
         current_stock.append((size, name))
@@ -93,23 +99,62 @@ def _split_combination(
     return stocks, trimmings
 
 
-# this might actually be worse than FFD (both in runtime and solution), disabled for now
-# O(n^2) ??
-def _solve_gapfill(job: Job) -> List[List[Tuple[int, str | None]]]:
+# textbook solution, guaranteed to get at most double trimmings of perfect solution; possibly O(n^2)?
+def _solve_FFD(job: Job) -> ResultLengths:
+    # iterate over list of stocks
+    # put into first stock that it fits into
+
+    # 1. Sort by magnitude (largest first)
+    # 2. stack until limit is reached
+    # 3. try smaller as long as possible
+    # 4. create new bar
+
+    mutable_sizes = copy.deepcopy(job.target_sizes)
+    sizes = sorted(mutable_sizes, reverse=True)
+
+    stocks: list[list[tuple[int, str | None]]] = [[]]
+
+    i_target = 0
+
+    while i_target < len(sizes):
+        current_size = sizes[i_target]
+        for stock in stocks:
+            # calculate current stock length
+            stock_length = (
+                    sum([size[0] for size in stock]) + (len(stock) - 1) * job.cut_width
+            )
+            # step through existing stocks until current size fits
+            if (job.max_length - stock_length) > current_size.length:
+                # add size
+                stock.append((current_size.length, current_size.name))
+                break
+        else:  # nothing fit, opening next bin
+            stocks.append([(current_size.length, current_size.name)])
+
+        # decrease/get next
+        if current_size.quantity <= 1:
+            i_target += 1
+        else:
+            current_size.quantity -= 1
+
+    return _sorted(stocks)
+
+
+# even faster than FFD, seems like equal results; selfmade and less proven!
+def _solve_gapfill(job: Job) -> ResultLengths:
     # 1. Sort by magnitude (largest first)
     # 2. stack until limit is reached
     # 3. try smaller as long as possible
     # 4. create new bar
 
-    # TODO: rewrite to use native map instead
     # we are writing around in target sizes, prevent leaking changes to job
-    mutable_sizes = copy.deepcopy(job.sizes_as_list())
+    mutable_sizes = copy.deepcopy(job.target_sizes)
     targets = sorted(mutable_sizes, reverse=True)
 
     stocks = []
 
     current_size = 0
-    current_stock: List[Tuple[int, str | None]] = []
+    current_stock: list[tuple[int, str | None]] = []
 
     i_target = 0
     while len(targets) > 0:
@@ -125,9 +170,11 @@ def _solve_gapfill(job: Job) -> List[List[Tuple[int, str | None]]]:
 
         current_target: TargetSize = targets[i_target]
         # target fits inside current stock, transfer to results
-        if (current_size + current_target.length + job.cut_width) < job.max_length:
+        if (current_size + current_target.length) <= job.max_length:
             current_stock.append((current_target.length, current_target.name))
-            current_size += current_target.length + job.cut_width
+            current_size += current_target.length
+            if current_size < job.max_length:
+                current_size += job.cut_width
 
             # remove empty entries
             if current_target.quantity <= 1:
@@ -146,68 +193,30 @@ def _solve_gapfill(job: Job) -> List[List[Tuple[int, str | None]]]:
     return _sorted(stocks)
 
 
-# textbook solution, guaranteed to get at most double trimmings of perfect solution
-def _solve_FFD(job: Job) -> List[List[Tuple[int, str | None]]]:
-    # iterate over list of stocks
-    # put into first stock that it fits into
-
-    # 1. Sort by magnitude (largest first)
-    # 2. stack until limit is reached
-    # 3. try smaller as long as possible
-    # 4. create new bar
-
-    # TODO: rewrite to use native map instead?
-    mutable_sizes = copy.deepcopy(job.sizes_as_list())
-    sizes = sorted(mutable_sizes, reverse=True)
-
-    stocks: List[List[Tuple[int, str | None]]] = [[]]
-
-    i_target = 0
-
-    while i_target < len(sizes):
-        current_size = sizes[i_target]
-        for stock in stocks:
-            # calculate current stock length
-            stock_length = (
-                    sum([size[0] for size in stock]) + (len(stock) - 1) * job.cut_width
-            )
-            # step through existing stocks until current size fits
-            if (job.max_length - stock_length) > current_size.length:
-                # add size
-                stock.append((current_size.length, current_size.name))
-                break
-        else:  # nothing fit, opening next bin
-            stocks.append([(current_size.length, current_size.name)])
-
-        # decrease/get next
-        if current_size.quantity <= 1:
-            i_target += 1
-        else:
-            current_size.quantity -= 1
-
-    return _sorted(stocks)
-
-
 def _get_trimming(
-        max_length: int, lengths: Collection[Tuple[int, str | None]], cut_width: int
+        max_length: int, lengths: Collection[tuple[int, str | None]], cut_width: int
 ) -> int:
     sum_lengths = sum([length[0] for length in lengths])
     sum_cuts = len(lengths) * cut_width
 
     trimmings = max_length - (sum_lengths + sum_cuts)
 
+    # cut at the end can be omitted
+    if trimmings == -cut_width:
+        trimmings = 0
+
     if trimmings < 0:
-        raise OverflowError
+        raise OverflowError("Trimmings can't ever be negative!")
 
     return trimmings
 
 
-def _get_trimmings(
-        max_length: int, lengths: Collection[Collection[Tuple[int, str | None]]], cut_width: int
-) -> int:
+def _get_trimmings(max_length: int, lengths: ResultLengths, cut_width: int) -> int:
     return sum(_get_trimming(max_length, x, cut_width) for x in lengths)
 
-def _sorted(lengths: List[List[Tuple[int, str | None]]]) -> List[List[Tuple[int, str | None]]]:
+
+def _sorted(lengths: Collection[Collection]) -> ResultLengths:
     # keep most cuts at the top, getting simpler towards the end
     # this could also sort by trimmings but that is more work
-    return sorted(lengths, key=len, reverse=True)
+    lengths = tuple([tuple(sorted(l, reverse=True)) for l in lengths])
+    return tuple(sorted(lengths, key=len, reverse=True))
diff --git a/tests/res/in/testjob_cuts.json b/tests/res/in/testjob_cuts.json
deleted file mode 100644
index 778a4a1..0000000
--- a/tests/res/in/testjob_cuts.json
+++ /dev/null
@@ -1,10 +0,0 @@
-{
-  "cut_width": 10,
-  "max_length": 1010,
-  "target_sizes": [
-    {
-      "length": 500,
-      "quantity": 4
-    }
-  ]
-}
diff --git a/tests/res/in/testjob_equal.json b/tests/res/in/testjob_equal.json
deleted file mode 100644
index 460bc19..0000000
--- a/tests/res/in/testjob_equal.json
+++ /dev/null
@@ -1,10 +0,0 @@
-{
-  "cut_width": 10,
-  "max_length": 1000,
-  "target_sizes": [
-    {
-      "length": 1000,
-      "quantity": 4
-    }
-  ]
-}
diff --git a/tests/res/in/testjob_l.json b/tests/res/in/testjob_l.json
deleted file mode 100644
index 4921e5d..0000000
--- a/tests/res/in/testjob_l.json
+++ /dev/null
@@ -1,22 +0,0 @@
-{
-  "cut_width": 5,
-  "max_length": 2000,
-  "target_sizes": [
-    {
-      "length": 750,
-      "quantity": 5
-    },
-    {
-      "length": 500,
-      "quantity": 5
-    },
-    {
-      "length": 300,
-      "quantity": 10
-    },
-    {
-      "length": 100,
-      "quantity": 15
-    }
-  ]
-}
diff --git a/tests/res/in/testjob_m.json b/tests/res/in/testjob_m.json
deleted file mode 100644
index 23245fa..0000000
--- a/tests/res/in/testjob_m.json
+++ /dev/null
@@ -1,18 +0,0 @@
-{
-  "cut_width": 5,
-  "max_length": 1000,
-  "target_sizes": [
-    {
-      "length": 500,
-      "quantity": 4
-    },
-    {
-      "length": 300,
-      "quantity": 3
-    },
-    {
-      "length": 100,
-      "quantity": 1
-    }
-  ]
-}
diff --git a/tests/res/in/testjob_zero_cuts.json b/tests/res/in/testjob_zero_cuts.json
deleted file mode 100644
index 8beb9b2..0000000
--- a/tests/res/in/testjob_zero_cuts.json
+++ /dev/null
@@ -1,10 +0,0 @@
-{
-  "cut_width": 0,
-  "max_length": 1000,
-  "target_sizes": [
-    {
-      "length": 500,
-      "quantity": 4
-    }
-  ]
-}
diff --git a/tests/solver/data/test_Job.py b/tests/solver/data/test_Job.py
index 5e9258f..e859d13 100644
--- a/tests/solver/data/test_Job.py
+++ b/tests/solver/data/test_Job.py
@@ -32,7 +32,13 @@ def test_job_equal(testjob_s):
 def test_job_length(testjob_s):
     job1 = testjob_s
 
-    assert len(job1) == 6
+    assert job1.n_targets() == 6
+
+
+def test_job_combinations(testjob_s):
+    job1 = testjob_s
+
+    assert job1.n_combinations() == 15
 
 
 def test_equal_hash(testjob_s):
@@ -49,15 +55,17 @@ def test_valid(testjob_s):
 
 def test_invalid(testjob_s):
     invalid_job = testjob_s
-    invalid_job.max_length = -1
     with pytest.raises(ValueError):
-        invalid_job.assert_valid()
+        invalid_job.max_length = -1
+
+    with pytest.raises(ValueError):
+        invalid_job.cut_width = -1
 
 
 def test_too_long(testjob_s):
-    job = testjob_s
-    job.target_sizes.append(
-        TargetSize(**{"length": job.max_length + 1, "quantity": 4, "name": "too long"})
-    )
     with pytest.raises(ValueError):
-        job.assert_valid()
+        job = Job(
+            max_length=100,
+            cut_width=5,
+            target_sizes=(TargetSize(length=101, quantity=1),)
+        )
diff --git a/tests/solver/data/test_Result.py b/tests/solver/data/test_Result.py
index 50e05b4..c86e4f8 100644
--- a/tests/solver/data/test_Result.py
+++ b/tests/solver/data/test_Result.py
@@ -50,25 +50,42 @@ def test_valid(testjob_s):
 
 def test_invalid(testjob_s):
     job = testjob_s
-    invalid_result = Result(
-        job=job,
-        solver_type=SolverType.FFD,
-        time_us=-1,
-        lengths=[
-            [
-                (100, "Part1"),
-                (100, "Part1"),
-                (100, "Part1"),
-            ],
-            [
-                (200, "Part2"),
-                (200, "Part2"),
-                (200, "Part2"),
-            ],
-        ],
-    )
+
+    with pytest.raises(ValueError):
+        no_job = Result(
+            solver_type=SolverType.FFD,
+            time_us=-1,
+            lengths=[
+                [
+                    (100, "Part1"),
+                    (100, "Part1"),
+                    (100, "Part1"),
+                ],
+                [
+                    (200, "Part2"),
+                    (200, "Part2"),
+                    (200, "Part2"),
+                ],
+            ],
+        )
+
     with pytest.raises(ValueError):
-        invalid_result.assert_valid()
+        no_solve = Result(
+            job=job,
+            time_us=-1,
+            lengths=[
+                [
+                    (100, "Part1"),
+                    (100, "Part1"),
+                    (100, "Part1"),
+                ],
+                [
+                    (200, "Part2"),
+                    (200, "Part2"),
+                    (200, "Part2"),
+                ],
+            ],
+        )
 
 
 def test_equal(testjob_s):
diff --git a/tests/solver/data/test_json.py b/tests/solver/data/test_json.py
index 3fd1c59..ba65dcd 100644
--- a/tests/solver/data/test_json.py
+++ b/tests/solver/data/test_json.py
@@ -14,8 +14,8 @@ def test_to_json():
         ],
     )
     assert (
-        job.model_dump_json()
-        == '{"max_length":1200,"cut_width":5,"target_sizes":[{"length":300,"quantity":4,"name":"Part1"},{"length":200,"quantity":3,"name":""}]}'
+            job.model_dump_json()
+            == '{"max_length":1200,"cut_width":5,"target_sizes":[{"length":300,"quantity":4,"name":"Part1"},{"length":200,"quantity":3,"name":""}]}'
     )
 
 
@@ -26,4 +26,4 @@ def test_from_json():
     with open(json_file, "r") as encoded_job:
         job = Job.model_validate_json(encoded_job.read())
         assert job.__class__ == Job
-        assert len(job) > 0
+        assert job.assert_valid
diff --git a/tests/solver/test_large.py b/tests/solver/test_large.py
index 7d8d982..1835b07 100644
--- a/tests/solver/test_large.py
+++ b/tests/solver/test_large.py
@@ -1,35 +1,68 @@
+from app.solver.data.Job import TargetSize
 from app.solver.solver import (
     _solve_bruteforce,
-    _solve_FFD,
+    _solve_FFD, _solve_gapfill, _get_trimmings,
 )
 from tests.test_fixtures import *
 
 
 # close to the max for bruteforce!
-@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD])
-def test_m(testjob_m, solver):
-    orig_job = testjob_m.model_copy(deep=True)
+@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD, _solve_gapfill])
+def test_m(solver):
+    testjob_m = Job(max_length=1000, cut_width=5, target_sizes=(
+        TargetSize(length=500, quantity=4), TargetSize(length=300, quantity=3),
+        TargetSize(length=100, quantity=2)))
+
     solved = solver(testjob_m)
 
-    assert solved == [
-        [(500, ''), (300, ''), (100, '')],
-        [(500, ''), (300, '')],
-        [(500, ''), (300, '')],
-        [(500, '')]
-    ]
-    assert orig_job == testjob_m
+    assert solved == (
+        ((500, ''), (300, ''), (100, '')),
+        ((500, ''), (300, ''), (100, '')),
+        ((500, ''), (300, '')),
+        ((500, ''),))
+
 
+@pytest.mark.parametrize("solver", [_solve_FFD, _solve_gapfill])
+def test_l(solver):
+    testjob_l = Job(max_length=2000, cut_width=5, target_sizes=(
+        TargetSize(length=750, quantity=5), TargetSize(length=500, quantity=5),
+        TargetSize(length=300, quantity=10), TargetSize(length=100, quantity=15)))
 
-@pytest.mark.parametrize("solver", [_solve_FFD])
-def test_l(testjob_l, solver):
-    orig_job = testjob_l.model_copy(deep=True)
     solved = solver(testjob_l)
 
-    assert solved == [
-        [(300, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, '')],
-        [(300, ''), (300, ''), (300, ''), (300, ''), (300, ''), (300, ''), (100, '')],
-        [(750, ''), (500, ''), (500, ''), (100, ''), (100, '')],
-        [(500, ''), (500, ''), (500, ''), (300, ''), (100, '')],
-        [(750, ''), (750, ''), (300, ''), (100, '')],
-        [(750, ''), (750, ''), (300, ''), (100, '')]]
-    assert orig_job == testjob_l
+    assert solved == (
+        ((300, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, ''), (100, '')),
+        ((300, ''), (300, ''), (300, ''), (300, ''), (300, ''), (300, ''), (100, '')),
+        ((750, ''), (500, ''), (500, ''), (100, ''), (100, '')),
+        ((500, ''), (500, ''), (500, ''), (300, ''), (100, '')),
+        ((750, ''), (750, ''), (300, ''), (100, '')),
+        ((750, ''), (750, ''), (300, ''), (100, '')))
+
+
+# tests after here are only benchmarking and shouldn't ever be relevant
+
+@pytest.mark.parametrize("solver", [_solve_FFD, _solve_gapfill])
+def test_xl(solver):
+    testjob = Job(max_length=2000, cut_width=10, target_sizes=(
+        TargetSize(length=2000, quantity=5), TargetSize(length=1500, quantity=10),
+        TargetSize(length=750, quantity=25), TargetSize(length=500, quantity=50),
+        TargetSize(length=300, quantity=100), TargetSize(length=50, quantity=250),
+    ))
+
+    solved = solver(testjob)
+
+    assert _get_trimmings(testjob.max_length, solved, testjob.cut_width) == 2520
+
+
+@pytest.mark.parametrize("solver", [_solve_FFD, _solve_gapfill])
+def test_xxl(solver):
+    testjob = Job(max_length=2000, cut_width=10, target_sizes=(
+        TargetSize(length=1750, quantity=5), TargetSize(length=1500, quantity=10),
+        TargetSize(length=750, quantity=25), TargetSize(length=500, quantity=50),
+        TargetSize(length=300, quantity=100), TargetSize(length=200, quantity=150),
+        TargetSize(length=150, quantity=250), TargetSize(length=50, quantity=500),
+    ))
+
+    solved = solver(testjob)
+
+    assert _get_trimmings(testjob.max_length, solved, testjob.cut_width) == 3250
diff --git a/tests/solver/test_solver.py b/tests/solver/test_solver.py
index 27d17e5..c782c3a 100644
--- a/tests/solver/test_solver.py
+++ b/tests/solver/test_solver.py
@@ -19,6 +19,16 @@ def test_trimming():
     assert trimming == 70
 
 
+def test_trimming_zero():
+    trimming = _get_trimming(
+        max_length=1500,
+        lengths=((500, ""), (500, ""), (480, "")),
+        cut_width=10,
+    )
+
+    assert trimming == 0
+
+
 def test_trimming_raise():
     # raises Error if more stock was used than available
     with pytest.raises(OverflowError):
@@ -49,10 +59,10 @@ def test_solver_is_exactly(testjob_s, solver):
     orig_job = testjob_s.model_copy(deep=True)
     solved = solver(testjob_s)
 
-    assert solved == [
-        [(500, "Part1"), (500, "Part1"), (200, "Part2"), (200, "Part2")],
-        [(200, "Part2"), (200, "Part2")],
-    ]
+    assert solved == (
+        ((500, "Part1"), (500, "Part1"), (200, "Part2"), (200, "Part2")),
+        ((200, "Part2"), (200, "Part2")),
+    )
     assert orig_job == testjob_s
 
 
diff --git a/tests/solver/test_special.py b/tests/solver/test_special.py
index e3f05ec..33c8569 100644
--- a/tests/solver/test_special.py
+++ b/tests/solver/test_special.py
@@ -1,46 +1,44 @@
+from app.solver.data.Job import TargetSize
 from app.solver.solver import (
     _solve_bruteforce,
-    _solve_FFD,
+    _solve_FFD, _solve_gapfill,
 )
 from tests.test_fixtures import *
 
 
 # @pytest.mark.skip(reason="bug #63")
-@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD])
-def test_cuts(testjob_cuts, solver):
-    orig_job = testjob_cuts.model_copy(deep=True)
+@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD, _solve_gapfill])
+def test_cuts(solver):
+    testjob_cuts = Job(max_length=1010, cut_width=10, target_sizes=(TargetSize(length=500, quantity=4),))
     solved = solver(testjob_cuts)
 
-    assert solved == [
-        [(500, ''), (500, '')],
-        [(500, ''), (500, '')]
-    ]
-    assert orig_job == testjob_cuts
+    assert solved == (
+        ((500, ''), (500, '')),
+        ((500, ''), (500, ''))
+    )
 
 
-# @pytest.mark.skip(reason="bug #59")
-@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD])
-def test_zero_cuts(testjob_zero_cuts, solver):
-    orig_job = testjob_zero_cuts.model_copy(deep=True)
+@pytest.mark.skip(reason="bug #59")
+@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD, _solve_gapfill])
+def test_zero_cuts(solver):
+    testjob_zero_cuts = Job(max_length=1000, cut_width=0, target_sizes=(TargetSize(length=500, quantity=4),))
     solved = solver(testjob_zero_cuts)
 
-    assert solved == [
-        [(500, ''), (500, '')],
-        [(500, ''), (500, '')]
-    ]
-    assert orig_job == testjob_zero_cuts
+    assert solved == (
+        ((500, ''), (500, '')),
+        ((500, ''), (500, ''))
+    )
 
 
 # @pytest.mark.skip(reason="bug #64")
-@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD])
-def test_equal(testjob_equal, solver):
-    orig_job = testjob_equal.model_copy(deep=True)
+@pytest.mark.parametrize("solver", [_solve_bruteforce, _solve_FFD, _solve_gapfill])
+def test_equal(solver):
+    testjob_equal = Job(max_length=1000, cut_width=10, target_sizes=(TargetSize(length=1000, quantity=4),))
     solved = solver(testjob_equal)
 
-    assert solved == [
-        [(1000, '')],
-        [(1000, '')],
-        [(1000, '')],
-        [(1000, '')]
-    ]
-    assert orig_job == testjob_equal
+    assert solved == (
+        ((1000, ''),),
+        ((1000, ''),),
+        ((1000, ''),),
+        ((1000, ''),)
+    )
diff --git a/tests/test_fixtures.py b/tests/test_fixtures.py
index d9513d6..417cc82 100644
--- a/tests/test_fixtures.py
+++ b/tests/test_fixtures.py
@@ -23,28 +23,3 @@ def testresult_s():
     return Result.model_validate_json(
         load_json(Path("./tests/res/out/testresult_s.json"))
     )
-
-
-@pytest.fixture
-def testjob_m():
-    return Job.model_validate_json(load_json(Path("./tests/res/in/testjob_m.json")))
-
-
-@pytest.fixture
-def testjob_l():
-    return Job.model_validate_json(load_json(Path("./tests/res/in/testjob_l.json")))
-
-
-@pytest.fixture
-def testjob_cuts():
-    return Job.model_validate_json(load_json(Path("./tests/res/in/testjob_cuts.json")))
-
-
-@pytest.fixture
-def testjob_zero_cuts():
-    return Job.model_validate_json(load_json(Path("./tests/res/in/testjob_zero_cuts.json")))
-
-
-@pytest.fixture
-def testjob_equal():
-    return Job.model_validate_json(load_json(Path("./tests/res/in/testjob_equal.json")))
diff --git a/tests/test_main.py b/tests/test_main.py
index cb3543d..b81940b 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -12,6 +12,7 @@
 def test_get_root():
     response = client.get("/")
     assert response.status_code == 200
+    assert any(response.text)
 
 
 def test_get_version():
@@ -23,6 +24,7 @@ def test_get_version():
 def test_get_debug():
     response = client.get("/debug")
     assert response.status_code == 200
+    assert any(response.text)
 
 
 def test_full(testjob_s, testresult_s):