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Boundary-value analysis is a software testing technique in which tests are designed to include representatives of boundary values in a range. The idea comes from the boundary.[1] Given that there is a set of test vectors to test the system, a topology can be defined on that set. Those inputs which belong to the same equivalence class as defined by the equivalence partitioning theory would constitute the basis. Given that the basis sets are neighbors, there would exist a boundary between them. The test vectors on either side of the boundary are called boundary values. In practice, this would require that the test vectors can be ordered, and that the individual parameters follows some kind of order (either partial order or total order).
Formally, the boundary values can be defined as below:
In plainer English, values on the minimum and maximum edges of an equivalence partition are tested. The values could be input or output ranges of a software component, can also be the internal implementation. Since these boundaries are common locations for errors that result in software faults they are frequently exercised in test cases.
The expected input and output values to the software component should be extracted from the component specification. The values are then grouped into sets with identifiable boundaries. Each set, or partition, contains values that are expected to be processed by the component in the same way. Partitioning of test data ranges is explained in the equivalence partitioning test case design technique. It is important to consider both valid and invalid partitions when designing test cases.
The demonstration can be done using a function written in Java.
class Safe {
static int add(int a, int b)
{
int c = a + b ;
if (a >= 0 && b >= 0 && c < 0)
{
System.err.println("Overflow!");
}
if (a < 0 && b < 0 && c >= 0)
{
System.err.println("Underflow!");
}
return c;
}
}
On the basis of the code, the input vectors of [a,b] are partitioned. The blocks we need to cover are the overflow statement and the underflow statement and neither of these 2. That gives rise to 3 equivalent classes, from the code review itself.

we note that there is a fixed size of integer hence:-
We note that the input parameter a and b both are integers, hence total order exists on them. When we compute the equalities:-
we get back the values which are on the boundary, inclusive, that is these pairs of (a,b) are valid combinations, and no underflow or overflow would happen for them.
On the other hand:-
gives pairs of (a,b) which are invalid combinations, Overflow would occur for them. In the same way:-
gives pairs of (a,b) which are invalid combinations, Underflow would occur for them.
Boundary values (drawn only for the overflow case) are being shown as the orange line in the right hand side figure.
For another example, if the input values were months of the year, expressed as integers, the input parameter 'month' might have the following partitions:
... -2 -1 0 1 .............. 12 13 14 15 .....
--------------|-------------------|-------------------
invalid partition 1 valid partition invalid partition 2
The boundary between two partitions is the place where the behavior of the application changes and is not a real number itself. The boundary value is the minimum (or maximum) value that is at the boundary. The number 0 is the maximum number in the first partition, the number 1 is the minimum value in the second partition, both are boundary values. Test cases should be created to generate inputs or outputs that will fall on and to either side of each boundary, which results in two cases per boundary. The test cases on each side of a boundary should be in the smallest increment possible for the component under test, for an integer this is 1, but if the input was a decimal with 2 places then it would be .01. In the example above there are boundary values at 0,1 and 12,13 and each should be tested.
Boundary value analysis does not require invalid partitions. Take an example where a heater is turned on if the temperature is 10 degrees or colder. There are two partitions (temperature≤10, temperature>10) and two boundary values to be tested (temperature=10, temperature=11).
Where a boundary value falls within the invalid partition the test case is designed to ensure the software component handles the value in a controlled manner. Boundary value analysis can be used throughout the testing cycle and is equally applicable at all testing phases.
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Boundary-value analysis is a software testing technique in which tests are designed to include representatives of boundary values in a range. The idea comes from the boundary. Given that there is a set of test vectors to test the system, a topology can be defined on that set. Those inputs which belong to the same equivalence class as defined by the equivalence partitioning theory would constitute the basis. Given that the basis sets are neighbors, there would exist a boundary between them. The test vectors on either side of the boundary are called boundary values. In practice, this would require that the test vectors can be ordered, and that the individual parameters follows some kind of order (either partial order or total order).
Equivalence partitioning or equivalence class partitioning (ECP) is a software testing technique that divides the input data of a software unit into partitions of equivalent data from which test cases can be derived. In principle, test cases are designed to cover each partition at least once. This technique tries to define test cases that uncover classes of errors, thereby reducing the total number of test cases that must be developed. An advantage of this approach is reduction in the time required for testing software due to lesser number of test cases. Equivalence partitioning is typically applied to the inputs of a tested component, but may be applied to the outputs in rare cases. The equivalence partitions are usually derived from the requirements specification for input attributes that influence the processing of the test object. The fundamental concept of ECP comes from equivalence class which in turn comes from equivalence relation. A software system is in effect a computable function implemented as an algorithm in some implementation programming language. Given an input test vector some instructions of that algorithm get covered, ( see code coverage for details ) others do not. This gives the interesting relationship between input test vectors:- a C b {\displaystyle _{a}C_{b}} is an equivalence relation between test vectors a, b if and only if the coverage foot print of the vectors a, b are exactly the same, that is, they cover the same instructions, at same step. This would evidently mean that the relation cover C would partition the domain of the test vector into multiple equivalence class. This partitioning is called equivalence class partitioning of test input. If there are N equivalent classes, only N vectors are sufficient to fully cover the system. The demonstration can be done using a function written in C: On the basis of the code, the input vectors of [a,b] are partitioned. The blocks we need to cover are the overflow in the positive direction, negative direction, and neither of these 2. That gives rise to 3 equivalent classes, from the code review itself. To solve the input problem, we take refuge in the inequation z m i n ≤ x + y ≤ z m a x {\displaystyle z_{min}\leq x+y\leq z_{max}} There is a fixed size of Integer (computer science) hence, the z can be replaced with:- INT_MIN ≤ x + y ≤ INT_MAX and with x ∈ { INT_MIN , ... , INT_MAX } and y ∈ { INT_MIN , ... , INT_MAX } The values of the test vector at the strict condition of the equality that is INT_MIN = x + y and INT_MAX = x + y are called the boundary values, Boundary-value analysis has detailed information about it. Note that the graph only covers the overflow case, first quadrant for X and Y positive values. In general an input has certain ranges which are valid and other ranges which are invalid. Invalid data here does not mean that the data is incorrect, it means that this data lies outside of specific partition. This may be best explained by the example of a function which takes a parameter "month". The valid range for the month is 1 to 12, representing January to December. This valid range is called a partition. In this example there are two further partitions of invalid ranges. The first invalid partition would be ≤ 0 and the second invalid partition would be ≥ 13. ... -2 -1 0 1 .............. 12 13 14 15 ..... --------------|-------------------|--------------------- invalid partition 1 valid partition invalid partition 2 The testing theory related to equivalence partitioning says that only one test case of each partition is needed to evaluate the behaviour of the program for the related partition. In other words, it is sufficient to select one test case out of each partition to check the behaviour of the program. To use more or even all test cases of a partition will not find new faults in the program. The values within one partition are considered to be "equivalent". Thus the number of test cases can be reduced considerably. An additional effect of applying this technique is that you also find the so-called "dirty" test cases. An inexperienced tester may be tempted to use as test cases the input data 1 to 12 for the month and forget to select some out of the invalid partitions. This would lead to a huge number of unnecessary test cases on the one hand, and a lack of test cases for the dirty ranges on the other hand. The tendency is to relate equivalence partitioning to so called black box testing which is strictly checking a software component at its interface, without consideration of internal structures of the software. But having a closer look at the subject there are cases where it applies to grey box testing as well. Imagine an interface to a component which has a valid range between 1 and 12 like the example above. However internally the function may have a differentiation of values between 1 and 6 and the values between 7 and 12. Depending upon the input value the software internally will run through different paths to perform slightly different actions. Regarding the input and output interfaces to the component this difference will not be noticed, however in your grey-box testing you would like to make sure that both paths are examined. To achieve this it is necessary to introduce additional equivalence partitions which would not be needed for black-box testing. For this example this would be: ... -2 -1 0 1 ..... 6 7 ..... 12 13 14 15 ..... --------------|---------|----------|--------------------- invalid partition 1 P1 P2 invalid partition 2 valid partitions To check for the expected results you would need to evaluate some internal intermediate values rather than the output interface. It is not necessary that we should use multiple values from each partition. In the above scenario we can take -2 from invalid partition 1, 6 from valid partition P1, 7 from valid partition P2 and 15 from invalid partition 2. Equivalence partitioning is not a stand-alone method to determine test cases. It has to be supplemented by boundary value analysis. Having determined the partitions of possible inputs the method of boundary value analysis has to be applied to select the most effective test cases out of these partitions.
Risk-based testing (RBT) is a type of software testing that functions as an organizational principle used to prioritize the tests of features and functions in software, based on the risk of failure, the function of their importance and likelihood or impact of failure. In theory, there are an infinite number of possible tests. Risk-based testing uses risk (re-)assessments to steer all phases of the test process, i.e., test planning, test design, test implementation, test execution and test evaluation. This includes for instance, ranking of tests, and subtests, for functionality; test techniques such as boundary-value analysis, all-pairs testing and state transition tables aim to find the areas most likely to be defective.
In the study of differential equations, a boundary-value problem is a differential equation subjected to constraints called boundary conditions. A solution to a boundary value problem is a solution to the differential equation which also satisfies the boundary conditions. Boundary value problems arise in several branches of physics as any physical differential equation will have them. Problems involving the wave equation, such as the determination of normal modes, are often stated as boundary value problems. A large class of important boundary value problems are the Sturm–Liouville problems. The analysis of these problems, in the linear case, involves the eigenfunctions of a differential operator. To be useful in applications, a boundary value problem should be well posed. This means that given the input to the problem there exists a unique solution, which depends continuously on the input. Much theoretical work in the field of partial differential equations is devoted to proving that boundary value problems arising from scientific and engineering applications are in fact well-posed. Among the earliest boundary value problems to be studied is the Dirichlet problem, of finding the harmonic functions (solutions to Laplace's equation); the solution was given by the Dirichlet's principle.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
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