|
1
|
1 |
|
import pytest |
|
2
|
|
|
|
|
3
|
1 |
|
from openscap_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
