9 Proportion of units executed with and without bugs
500
400
450
300
350
200
250
150
100
50
0
1 3 5 7 9 11 13
Time measured in days
Expected and actual bugs
Expected bugs
Actual bugs
Number of bugs found
15 17 25 23 21 19
1200
1000
800
600
400
200
0
1 3 5 7 9 11 13
Time in days
Tests run on 4 features
Feature 4 tests
Feature 3 tests
Feature 2 tests
Feature 1 tests
Tests run
15 17 19 21 23 25
500
450
400
350
300
250
200
100
150
50
0
1 3 5 7 9 11 13
Time in days
Unit passed and failed
Units passed
Units
15 17 19 21 23 25
Units failed
Testing Processes and Infrastructure 107
From this relationship it can be seen that only some seventy-one units are buggy (13%). These units can then
be analyzed as discussed below to see whether the bug lay in the coding or the design, if for example the buggy
units are more complex than those without a detected bug, what kind of unit they were, what sort of bugs
predominated, whether a particular sort of test tended to find a particular kind of bug. This in turn will lead
to some replanning and divergence of effort to ensure that the unit tests are changed to find those bugs.
7.6.3 Bug Analysis
As tests are run, a quality profile of the software can be developed. Quality profiles using analyzers may
be run on the software before testing but it is as the software is being tested that the software??™s behavior
and the importance of the tool-derived profiles become evident.
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