tests.unit_tests.test_oval_result_eval - Code Metrics - Inspection of "Tests of OVAL operator evaluation" - OpenSCAP/openscap-report - Measure and Improve Code Quality continuously with Scrutinizer

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Pull Request — master (#43)

by Jan

created 2022-02-02 12:30 UTC

tests.unit_tests.test_oval_result_eval A

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Complexity

Total Complexity

Size/Duplication

Total Lines	266
Duplicated Lines	0 %

Test Coverage

Coverage

100%

Importance

Changes

Metric	Value
eloc	204
dl	0
loc	266
ccs	30
cts	30
cp	1
rs	10
c	0
b	0
f	0
wmc	1

1 Function

Rating	Name	Duplication	Size	Complexity
B	test_evaluate_oval_result()	0	45	1

import pytest

from oscap_report.scap_results_parser.data_structures.oval_result_eval import (
    EMPTY_RESULT, OvalResult)

BAD_RESULT_COUNTS = {
    "number_of_true": -1,
    "number_of_false": -1,
    "number_of_error": -1,
    "number_of_unknown": -1,
    "number_of_noteval": -1,
    "number_of_notappl": -1
}

RESULT_COUNTS_1 = {
    "number_of_true": 3,
    "number_of_false": 3,
    "number_of_error": 3,
    "number_of_unknown": 0,
    "number_of_noteval": -1,
    "number_of_notappl": 3
}

RESULT_COUNTS_NOTAPPL = dict(**EMPTY_RESULT)
RESULT_COUNTS_NOTAPPL["number_of_notappl"] = 5

# AND cases
RESULT_COUNTS_AND_TRUE = {
    "number_of_true": 2,
    "number_of_false": 0,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_AND_FALSE = {
    "number_of_true": 2,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 1,
    "number_of_noteval": 1,
    "number_of_notappl": 1
}

RESULT_COUNTS_AND_ERROR = {
    "number_of_true": 1,
    "number_of_false": 0,
    "number_of_error": 3,
    "number_of_unknown": 1,
    "number_of_noteval": 1,
    "number_of_notappl": 1
}

RESULT_COUNTS_AND_UNKNOWN = {
    "number_of_true": 0,
    "number_of_false": 0,
    "number_of_error": 0,
    "number_of_unknown": 3,
    "number_of_noteval": 1,
    "number_of_notappl": 2
}

RESULT_COUNTS_AND_NOTEVAL = {
    "number_of_true": 2,
    "number_of_false": 0,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 3,
    "number_of_notappl": 2
}

# OR cases
RESULT_COUNTS_OR_TRUE = {
    "number_of_true": 2,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 2,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_OR_FALSE = {
    "number_of_true": 0,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_OR_ERROR = {
    "number_of_true": 0,
    "number_of_false": 2,
    "number_of_error": 3,
    "number_of_unknown": 1,
    "number_of_noteval": 1,
    "number_of_notappl": 1
}

RESULT_COUNTS_OR_UNKNOWN = {
    "number_of_true": 0,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 3,
    "number_of_noteval": 1,
    "number_of_notappl": 2
}

RESULT_COUNTS_OR_NOTEVAL = {
    "number_of_true": 0,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 3,
    "number_of_notappl": 3
}

# ONE cases
RESULT_COUNTS_ONE_TRUE = {
    "number_of_true": 1,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_ONE_FALSE = {
    "number_of_true": 2,
    "number_of_false": 2,
    "number_of_error": 3,
    "number_of_unknown": 5,
    "number_of_noteval": 2,
    "number_of_notappl": 1
}

RESULT_COUNTS_ONE_FALSE_1 = {
    "number_of_true": 0,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_ONE_ERROR = {
    "number_of_true": 1,
    "number_of_false": 2,
    "number_of_error": 3,
    "number_of_unknown": 1,
    "number_of_noteval": 1,
    "number_of_notappl": 1
}

RESULT_COUNTS_ONE_UNKNOWN = {
    "number_of_true": 1,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 3,
    "number_of_noteval": 4,
    "number_of_notappl": 2
}

RESULT_COUNTS_ONE_NOTEVAL = {
    "number_of_true": 1,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 3,
    "number_of_notappl": 6
}

# XOR cases
RESULT_COUNTS_XOR_TRUE = {
    "number_of_true": 7,
    "number_of_false": 5,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_XOR_FALSE = {
    "number_of_true": 8,
    "number_of_false": 5,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 0,
    "number_of_notappl": 1
}

RESULT_COUNTS_XOR_ERROR = {
    "number_of_true": 5,
    "number_of_false": 2,
    "number_of_error": 3,
    "number_of_unknown": 1,
    "number_of_noteval": 2,
    "number_of_notappl": 1
}

RESULT_COUNTS_XOR_UNKNOWN = {
    "number_of_true": 2,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 3,
    "number_of_noteval": 1,
    "number_of_notappl": 2
}

RESULT_COUNTS_XOR_NOTEVAL = {
    "number_of_true": 2,
    "number_of_false": 2,
    "number_of_error": 0,
    "number_of_unknown": 0,
    "number_of_noteval": 3,
    "number_of_notappl": 5
}


@pytest.mark.parametrize("eval_function, result", [
    (OvalResult(**RESULT_COUNTS_NOTAPPL).is_notapp_result, True),

    (OvalResult(**BAD_RESULT_COUNTS).eval_operator_and, None),
    (OvalResult(**BAD_RESULT_COUNTS).eval_operator_one, None),
    (OvalResult(**BAD_RESULT_COUNTS).eval_operator_or, None),
    (OvalResult(**BAD_RESULT_COUNTS).eval_operator_xor, None),

    (OvalResult(**EMPTY_RESULT).eval_operator_and, None),
    (OvalResult(**EMPTY_RESULT).eval_operator_one, None),
    (OvalResult(**EMPTY_RESULT).eval_operator_or, None),
    (OvalResult(**EMPTY_RESULT).eval_operator_xor, 'false'),

    (OvalResult(**RESULT_COUNTS_1).eval_operator_and, 'false'),
    (OvalResult(**RESULT_COUNTS_1).eval_operator_one, None),
    (OvalResult(**RESULT_COUNTS_1).eval_operator_or, 'true'),
    (OvalResult(**RESULT_COUNTS_1).eval_operator_xor, 'error'),

    (OvalResult(**RESULT_COUNTS_AND_TRUE).eval_operator_and, 'true'),
    (OvalResult(**RESULT_COUNTS_AND_FALSE).eval_operator_and, 'false'),
    (OvalResult(**RESULT_COUNTS_AND_ERROR).eval_operator_and, 'error'),
    (OvalResult(**RESULT_COUNTS_AND_UNKNOWN).eval_operator_and, 'unknown'),
    (OvalResult(**RESULT_COUNTS_AND_NOTEVAL).eval_operator_and, 'noteval'),

    (OvalResult(**RESULT_COUNTS_OR_TRUE).eval_operator_or, 'true'),
    (OvalResult(**RESULT_COUNTS_OR_FALSE).eval_operator_or, 'false'),
    (OvalResult(**RESULT_COUNTS_OR_ERROR).eval_operator_or, 'error'),
    (OvalResult(**RESULT_COUNTS_OR_UNKNOWN).eval_operator_or, 'unknown'),
    (OvalResult(**RESULT_COUNTS_OR_NOTEVAL).eval_operator_or, 'noteval'),

    (OvalResult(**RESULT_COUNTS_ONE_TRUE).eval_operator_one, 'true'),
    (OvalResult(**RESULT_COUNTS_ONE_FALSE).eval_operator_one, 'false'),
    (OvalResult(**RESULT_COUNTS_ONE_FALSE_1).eval_operator_one, 'false'),
    (OvalResult(**RESULT_COUNTS_ONE_ERROR).eval_operator_one, 'error'),
    (OvalResult(**RESULT_COUNTS_ONE_UNKNOWN).eval_operator_one, 'unknown'),
    (OvalResult(**RESULT_COUNTS_ONE_NOTEVAL).eval_operator_one, 'noteval'),

    (OvalResult(**RESULT_COUNTS_XOR_TRUE).eval_operator_xor, 'true'),
    (OvalResult(**RESULT_COUNTS_XOR_FALSE).eval_operator_xor, 'false'),
    (OvalResult(**RESULT_COUNTS_XOR_ERROR).eval_operator_xor, 'error'),
    (OvalResult(**RESULT_COUNTS_XOR_UNKNOWN).eval_operator_xor, 'unknown'),
    (OvalResult(**RESULT_COUNTS_XOR_NOTEVAL).eval_operator_xor, 'noteval'),
])
def test_evaluate_oval_result(eval_function, result):
    assert eval_function() is result


1	1	import pytest
2
3	1	from oscap_report.scap_results_parser.data_structures.oval_result_eval import (
4		EMPTY_RESULT, OvalResult)
5
6	1	BAD_RESULT_COUNTS = {
7		"number_of_true": -1,
8		"number_of_false": -1,
9		"number_of_error": -1,
10		"number_of_unknown": -1,
11		"number_of_noteval": -1,
12		"number_of_notappl": -1
13		}
14
15	1	RESULT_COUNTS_1 = {
16		"number_of_true": 3,
17		"number_of_false": 3,
18		"number_of_error": 3,
19		"number_of_unknown": 0,
20		"number_of_noteval": -1,
21		"number_of_notappl": 3
22		}
23
24	1	RESULT_COUNTS_NOTAPPL = dict(**EMPTY_RESULT)
25	1	RESULT_COUNTS_NOTAPPL["number_of_notappl"] = 5
26
27		# AND cases
28	1	RESULT_COUNTS_AND_TRUE = {
29		"number_of_true": 2,
30		"number_of_false": 0,
31		"number_of_error": 0,
32		"number_of_unknown": 0,
33		"number_of_noteval": 0,
34		"number_of_notappl": 1
35		}
36
37	1	RESULT_COUNTS_AND_FALSE = {
38		"number_of_true": 2,
39		"number_of_false": 2,
40		"number_of_error": 0,
41		"number_of_unknown": 1,
42		"number_of_noteval": 1,
43		"number_of_notappl": 1
44		}
45
46	1	RESULT_COUNTS_AND_ERROR = {
47		"number_of_true": 1,
48		"number_of_false": 0,
49		"number_of_error": 3,
50		"number_of_unknown": 1,
51		"number_of_noteval": 1,
52		"number_of_notappl": 1
53		}
54
55	1	RESULT_COUNTS_AND_UNKNOWN = {
56		"number_of_true": 0,
57		"number_of_false": 0,
58		"number_of_error": 0,
59		"number_of_unknown": 3,
60		"number_of_noteval": 1,
61		"number_of_notappl": 2
62		}
63
64	1	RESULT_COUNTS_AND_NOTEVAL = {
65		"number_of_true": 2,
66		"number_of_false": 0,
67		"number_of_error": 0,
68		"number_of_unknown": 0,
69		"number_of_noteval": 3,
70		"number_of_notappl": 2
71		}
72
73		# OR cases
74	1	RESULT_COUNTS_OR_TRUE = {
75		"number_of_true": 2,
76		"number_of_false": 2,
77		"number_of_error": 0,
78		"number_of_unknown": 2,
79		"number_of_noteval": 0,
80		"number_of_notappl": 1
81		}
82
83	1	RESULT_COUNTS_OR_FALSE = {
84		"number_of_true": 0,
85		"number_of_false": 2,
86		"number_of_error": 0,
87		"number_of_unknown": 0,
88		"number_of_noteval": 0,
89		"number_of_notappl": 1
90		}
91
92	1	RESULT_COUNTS_OR_ERROR = {
93		"number_of_true": 0,
94		"number_of_false": 2,
95		"number_of_error": 3,
96		"number_of_unknown": 1,
97		"number_of_noteval": 1,
98		"number_of_notappl": 1
99		}
100
101	1	RESULT_COUNTS_OR_UNKNOWN = {
102		"number_of_true": 0,
103		"number_of_false": 2,
104		"number_of_error": 0,
105		"number_of_unknown": 3,
106		"number_of_noteval": 1,
107		"number_of_notappl": 2
108		}
109
110	1	RESULT_COUNTS_OR_NOTEVAL = {
111		"number_of_true": 0,
112		"number_of_false": 2,
113		"number_of_error": 0,
114		"number_of_unknown": 0,
115		"number_of_noteval": 3,
116		"number_of_notappl": 3
117		}
118
119		# ONE cases
120	1	RESULT_COUNTS_ONE_TRUE = {
121		"number_of_true": 1,
122		"number_of_false": 2,
123		"number_of_error": 0,
124		"number_of_unknown": 0,
125		"number_of_noteval": 0,
126		"number_of_notappl": 1
127		}
128
129	1	RESULT_COUNTS_ONE_FALSE = {
130		"number_of_true": 2,
131		"number_of_false": 2,
132		"number_of_error": 3,
133		"number_of_unknown": 5,
134		"number_of_noteval": 2,
135		"number_of_notappl": 1
136		}
137
138	1	RESULT_COUNTS_ONE_FALSE_1 = {
139		"number_of_true": 0,
140		"number_of_false": 2,
141		"number_of_error": 0,
142		"number_of_unknown": 0,
143		"number_of_noteval": 0,
144		"number_of_notappl": 1
145		}
146
147	1	RESULT_COUNTS_ONE_ERROR = {
148		"number_of_true": 1,
149		"number_of_false": 2,
150		"number_of_error": 3,
151		"number_of_unknown": 1,
152		"number_of_noteval": 1,
153		"number_of_notappl": 1
154		}
155
156	1	RESULT_COUNTS_ONE_UNKNOWN = {
157		"number_of_true": 1,
158		"number_of_false": 2,
159		"number_of_error": 0,
160		"number_of_unknown": 3,
161		"number_of_noteval": 4,
162		"number_of_notappl": 2
163		}
164
165	1	RESULT_COUNTS_ONE_NOTEVAL = {
166		"number_of_true": 1,
167		"number_of_false": 2,
168		"number_of_error": 0,
169		"number_of_unknown": 0,
170		"number_of_noteval": 3,
171		"number_of_notappl": 6
172		}
173
174		# XOR cases
175	1	RESULT_COUNTS_XOR_TRUE = {
176		"number_of_true": 7,
177		"number_of_false": 5,
178		"number_of_error": 0,
179		"number_of_unknown": 0,
180		"number_of_noteval": 0,
181		"number_of_notappl": 1
182		}
183
184	1	RESULT_COUNTS_XOR_FALSE = {
185		"number_of_true": 8,
186		"number_of_false": 5,
187		"number_of_error": 0,
188		"number_of_unknown": 0,
189		"number_of_noteval": 0,
190		"number_of_notappl": 1
191		}
192
193	1	RESULT_COUNTS_XOR_ERROR = {
194		"number_of_true": 5,
195		"number_of_false": 2,
196		"number_of_error": 3,
197		"number_of_unknown": 1,
198		"number_of_noteval": 2,
199		"number_of_notappl": 1
200		}
201
202	1	RESULT_COUNTS_XOR_UNKNOWN = {
203		"number_of_true": 2,
204		"number_of_false": 2,
205		"number_of_error": 0,
206		"number_of_unknown": 3,
207		"number_of_noteval": 1,
208		"number_of_notappl": 2
209		}
210
211	1	RESULT_COUNTS_XOR_NOTEVAL = {
212		"number_of_true": 2,
213		"number_of_false": 2,
214		"number_of_error": 0,
215		"number_of_unknown": 0,
216		"number_of_noteval": 3,
217		"number_of_notappl": 5
218		}
219
220
221	1	@pytest.mark.parametrize("eval_function, result", [
222		(OvalResult(**RESULT_COUNTS_NOTAPPL).is_notapp_result, True),
223
224		(OvalResult(**BAD_RESULT_COUNTS).eval_operator_and, None),
225		(OvalResult(**BAD_RESULT_COUNTS).eval_operator_one, None),
226		(OvalResult(**BAD_RESULT_COUNTS).eval_operator_or, None),
227		(OvalResult(**BAD_RESULT_COUNTS).eval_operator_xor, None),
228
229		(OvalResult(**EMPTY_RESULT).eval_operator_and, None),
230		(OvalResult(**EMPTY_RESULT).eval_operator_one, None),
231		(OvalResult(**EMPTY_RESULT).eval_operator_or, None),
232		(OvalResult(**EMPTY_RESULT).eval_operator_xor, 'false'),
233
234		(OvalResult(**RESULT_COUNTS_1).eval_operator_and, 'false'),
235		(OvalResult(**RESULT_COUNTS_1).eval_operator_one, None),
236		(OvalResult(**RESULT_COUNTS_1).eval_operator_or, 'true'),
237		(OvalResult(**RESULT_COUNTS_1).eval_operator_xor, 'error'),
238
239		(OvalResult(**RESULT_COUNTS_AND_TRUE).eval_operator_and, 'true'),
240		(OvalResult(**RESULT_COUNTS_AND_FALSE).eval_operator_and, 'false'),
241		(OvalResult(**RESULT_COUNTS_AND_ERROR).eval_operator_and, 'error'),
242		(OvalResult(**RESULT_COUNTS_AND_UNKNOWN).eval_operator_and, 'unknown'),
243		(OvalResult(**RESULT_COUNTS_AND_NOTEVAL).eval_operator_and, 'noteval'),
244
245		(OvalResult(**RESULT_COUNTS_OR_TRUE).eval_operator_or, 'true'),
246		(OvalResult(**RESULT_COUNTS_OR_FALSE).eval_operator_or, 'false'),
247		(OvalResult(**RESULT_COUNTS_OR_ERROR).eval_operator_or, 'error'),
248		(OvalResult(**RESULT_COUNTS_OR_UNKNOWN).eval_operator_or, 'unknown'),
249		(OvalResult(**RESULT_COUNTS_OR_NOTEVAL).eval_operator_or, 'noteval'),
250
251		(OvalResult(**RESULT_COUNTS_ONE_TRUE).eval_operator_one, 'true'),
252		(OvalResult(**RESULT_COUNTS_ONE_FALSE).eval_operator_one, 'false'),
253		(OvalResult(**RESULT_COUNTS_ONE_FALSE_1).eval_operator_one, 'false'),
254		(OvalResult(**RESULT_COUNTS_ONE_ERROR).eval_operator_one, 'error'),
255		(OvalResult(**RESULT_COUNTS_ONE_UNKNOWN).eval_operator_one, 'unknown'),
256		(OvalResult(**RESULT_COUNTS_ONE_NOTEVAL).eval_operator_one, 'noteval'),
257
258		(OvalResult(**RESULT_COUNTS_XOR_TRUE).eval_operator_xor, 'true'),
259		(OvalResult(**RESULT_COUNTS_XOR_FALSE).eval_operator_xor, 'false'),
260		(OvalResult(**RESULT_COUNTS_XOR_ERROR).eval_operator_xor, 'error'),
261		(OvalResult(**RESULT_COUNTS_XOR_UNKNOWN).eval_operator_xor, 'unknown'),
262		(OvalResult(**RESULT_COUNTS_XOR_NOTEVAL).eval_operator_xor, 'noteval'),
263		])
264	1	def test_evaluate_oval_result(eval_function, result):
265		assert eval_function() is result
266

OpenSCAP / openscap-report

Pull Request — master (#43)

tests.unit_tests.test_oval_result_eval A

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Size/Duplication

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1 Function

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