diff --git a/trace_agg_unit_test/tests/test_core.py b/trace_agg_unit_test/tests/test_core.py
new file mode 100644
index 0000000..0f93498
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+++ b/trace_agg_unit_test/tests/test_core.py
@@ -0,0 +1,62 @@
+import pytest
+import pandas as pd
+from pathlib import Path
+
+# Das getestete Modul
+import trace_agg
+
+def test_run_aggregation_tests_basic(tmp_path):
+    # Beispielhafte CSV-Datei mit TraceEvent-Daten erstellen
+    data_path = tmp_path / "trace_sample.csv"
+    df = pd.DataFrame([
+        {"timestamp": 0.0, "event_type": "clocksource", "value": 1.0},
+        {"timestamp": 0.1, "event_type": "clocksource", "value": 2.0},
+        {"timestamp": 0.2, "event_type": "clocksource_switch", "value": 3.0}
+    ])
+    df.to_csv(data_path, index=False)
+
+    # Funktion aus trace_agg ausführen
+    results = trace_agg.run_aggregation_tests([str(data_path)])
+
+    # Ergebnistyp prüfen
+    assert isinstance(results, dict)
+    assert str(data_path) in results
+
+    file_result = results[str(data_path)]
+    assert "sum" in file_result
+    assert "status" in file_result
+
+    # Summenprüfung: Summe im Testdatenframe sollte 6.0 sein
+    assert pytest.approx(file_result["sum"], rel=1e-6) == df["value"].sum()
+    assert file_result["status"] in ("passed", "failed")
+
+def test_run_aggregation_tests_multiple_files(tmp_path):
+    file_paths = []
+    # Zwei CSV-Dateien mit Testdaten erzeugen
+    for i in range(2):
+        path = tmp_path / f"trace_{i}.csv"
+        df = pd.DataFrame([
+            {"timestamp": i, "event_type": "clocksource", "value": i + 1.0},
+            {"timestamp": i + 0.1, "event_type": "clocksource_switch", "value": i + 2.0}
+        ])
+        df.to_csv(path, index=False)
+        file_paths.append(str(path))
+
+    results = trace_agg.run_aggregation_tests(file_paths)
+
+    # Ergebnisse müssen für alle Dateien vorhanden sein
+    assert isinstance(results, dict)
+    assert set(map(str, file_paths)) == set(results.keys())
+
+    for fp in file_paths:
+        res = results[fp]
+        assert "sum" in res and "status" in res
+        sum_expected = pd.read_csv(fp)["value"].sum()
+        assert pytest.approx(res["sum"], rel=1e-6) == sum_expected
+        assert res["status"] == "passed"
+
+
+def test_run_aggregation_tests_invalid_input():
+    # Wenn eine ungültige Datei übergeben wird, soll ein Fehler oder leeres Ergebnis folgen
+    with pytest.raises(Exception):
+        trace_agg.run_aggregation_tests(["/nonexistent/path.csv"])
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