diff --git a/cache/client_1_update.pkl b/cache/client_1_update.pkl
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diff --git a/tests/test_offline_cache.py b/tests/test_offline_cache.py
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+import os
+import random
+import sys
+
+# Ensure repository root is on sys.path for package import during tests
+ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
+if ROOT not in sys.path:
+    sys.path.insert(0, ROOT)
+
+from interplanetary_edge_orchestrator_privacy import Client, Server
+
+
+def generate_dataset(n_samples: int, n_features: int, seed: int = 0):
+    rng = random.Random(seed)
+    X = [[rng.gauss(0.0, 1.0) for _ in range(n_features)] for _ in range(n_samples)]
+    true_w = [rng.gauss(0.0, 1.0) for _ in range(n_features)]
+    y = [sum(X[i][k] * true_w[k] for k in range(n_features)) + rng.gauss(0.0, 0.1) for i in range(n_samples)]
+    return X, y, true_w
+
+
+def test_offline_client_can_cache_and_load_update(tmp_path=None):
+    random.seed(0)
+    n_features = 3
+    n_clients = 2
+
+    # Client 0 will operate online; Client 1 will operate offline to exercise cache.
+    X0, y0, _ = generate_dataset(40, n_features, seed=1)
+    X1, y1, _ = generate_dataset(40, n_features, seed=2)
+
+    online = Client(client_id=0, data_X=X0, data_y=y0, connected=True, cache_dir=str(tmp_path or "cache"))
+    offline = Client(client_id=1, data_X=X1, data_y=y1, connected=False, cache_dir=str(tmp_path or "cache"))
+    server = Server(n_features)
+
+    # Initialize weights and collect updates from online client
+    online.initialize(n_features)
+    upd_online = online.train(server.w, lr=0.01, epochs=5)
+
+    # Train offline client; its update should be cached to disk
+    offline.initialize(n_features)
+    upd_offline = offline.train(server.w, lr=0.01, epochs=5)
+
+    # Load the cached offline update and verify it matches the returned value
+    cached_offline = offline.load_update()
+    assert cached_offline == upd_offline
+
+    # Now perform a server aggregation including the offline update read from cache
+    updates = [upd_online, cached_offline]
+    server.aggregate(updates, noise_scale=0.0, seed=123)
+
+    # Basic sanity: server weights moved from initial zeros
+    w_init = [0.0 for _ in range(n_features)]
+    assert isinstance(server.w, list) and len(server.w) == n_features
+    assert any(abs(server.w[i] - w_init[i]) > 1e-9 for i in range(n_features))