The learning algorithm that should have been added previously.

z3gi/learn/algorithm.py

+from typing import List, Tuple
+from typing import cast
+
+from model import Automaton
+from learn import Learner
+from test import TestTemplate
+
+class Statistics():
+    def __init__(self):
+        self.num_tests = 0
+        self.num_inputs = 0
+        self.suite_size = 0
+
+    def add_inputs(self, num):
+        self.num_inputs += num
+
+    def add_tests(self, num):
+        self.num_tests += num
+
+    def set_suite_size(self, num):
+        self.suite_size = num
+
+    def __str__(self):
+        return "Total number tests used in learning: {0} \n" \
+               "Total number inputs used in learning: {1} \n " \
+               "Test suite size: {2}".format(self.num_tests,
+                                             self.num_inputs,
+                                             self.suite_size)
+
+
+def learn(learner:Learner, test_type:type, traces: List[object]) -> Tuple[Automaton, Statistics]:
+    statistics = Statistics()
+    if len(traces) == 0:
+        return (None, statistics)
+    else:
+        statistics.set_suite_size(len(traces))
+        test = cast(TestTemplate, test_type(traces.pop(0)))
+        definition = None
+        learner.add(test.trace)
+        statistics.add_tests(1)
+        statistics.add_inputs(test.size())
+        done = False
+        model = None
+        while not done:
+            (model, definition) = learner.model(old_definition=definition)
+            done = True
+            for trace in traces:
+                test = cast(TestTemplate, test_type(trace))
+                ce = test.check(model)
+                if ce is not None:
+                    learner.add(ce)
+                    statistics.add_tests(1)
+                    statistics.add_inputs(test.size())
+                    done = False
+                    break
+        return (model, statistics)
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