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Testing Basics. Detection probability. L5asg – detprob for subdomain tests. What is the probability of detection with one randomly chosen test case per path? What is the probability of detection with an equal number of randomly chosen test cases?. Control Flow Graph. Operational profile - PowerPoint PPT Presentation
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1841f06detprob4
Testing Basics
Detection probability
L5asg – detprob for subdomain tests
What is the probability of detection with one randomly chosen test case per path?
What is the probability of detection with an equal number of randomly chosen test cases?
3841f06detprob4
Control Flow Graph
I: cout
B: type = isoscles
D: type = equilateral
F: type = not a triangle
H: type = bad input
A: type = scalene
C: if
E: if
G: if
Operational profile
3,3,3 abcdegi equi3,3,4 abcegi isos3,3,5 abcegi isos3,3,6 abcefgi not3,4,3 abcegi isos3,4,4 abcegi isos3,4,5 acegi scal3,4,6 acegi scal
All inputs are equally likely
4841f06detprob4
What are the failure probability for each color (separately)?
cin >> a >> b >> c ;type = “scalene”;if (a == b || a == c && b == c) type= “isosceles”;if (a == b || a == c) type = “equilateral”;if (a >= b+c || b >= a+c || c > a+b) type=“not a triangle”;if (a <= 0 || b <= 0 || c <= 0) type=“bad input”;cout<< type;
Blue Green Red
TTYP – smaller subdomains
What might be better smaller subdomains? Would MCC (multiple condition coverage)
be better subdomains
TTYP2 – C0 and C1 coverage
How do we deal with C0 and C1 coverage since they are not subdomain testing methodologies?
9841f06detprob4
Evaluating Testing Methods by Delivered Reliability
Frankl, Hamlet, Littlewood, Strigini
IEEE TOSE Aug98
Testing
Debug
Operational
Fault Detection Probability
Probability of a testing methodology finding a fault (if it existed)
Partition vs Random
Tests, Specifications, meets
Test or test case– single value of program input
– functional program - one input produces an output
Specification - S– set of input-output pairs
Program meets specification– iff for all x in spec, actual output matches spec output
Q: probability distribution
Q - probability distribution over input domain– Q:D -> [0,1] and Q(t) = 1
: Failure Probability
- failure probability for a randomly drawn point is Q*– Where(t) = 1 if and 0 if – and-phi(failure) and -sigma(success)
How does this relate to our notation?
Reliability
R(N) = (1- )N
Assumptions of initial model
Terms
q
d
3.2 SFR, w/o subdomains
d = tinF V(t)
P() = 1-(1-d)T
P(q) = (1-d)T
E() = 0* P() +q* P(q) = q(1-d)T
Thurs, Sep 6
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