Wednesday, 18 May 2011

White box testing

What is WBT?
White box testing
involves looking at the structure of the code. When you know the internal structure of a product, tests can be conducted to ensure that the internal operations performed according to the specification. And all internal components have been adequately exercised. In other word WBT tends to involve the coverage of the specification in the code.

Code coverage is defined in following types as listed below:

1. Segment coverage – Each segment of code b/w control structure is executed at least once.

2. Branch Coverage or Node Testing – Each branch in the code is taken in each possible direction at least once.

3. Compound Condition Coverage – When there are multiple conditions, you must test not only each direction but also each possible combinations of conditions, which is usually done by using a ‘Truth Table’

4. Basis Path Testing – Each independent path through the code is taken in a pre-determined order.

5. Data Flow Testing (DFT) – In this approach you track the specific variables through each possible calculation, thus defining the set of intermediate paths through the code i.e., those based on each piece of code chosen to be tracked. Even though the paths are considered independent, dependencies across multiple paths are not really tested for by this approach. DFT tends to reflect dependencies but it is mainly through sequences of data manipulation. This approach tends to uncover bugs like variables used but not initialize, or declared but not used, and so on.

6. Path Testing – Path testing is where all possible paths through the code are defined and covered. This testing is extremely laborious and time consuming.

7. Loop Testing – In addition top above measures, there are testing strategies based on loop testing. These strategies relate to testing single loops, concatenated loops, and nested loops. Loops are fairly simple to test unless dependencies exist among the loop or b/w a loop and the code it contains.

What do we do in WBT?

In WBT, we use the control structure of the procedural design to derive test cases. Using WBT methods a tester can derive the test cases that

- Guarantee that all independent paths within a module have been exercised at least once.

- Exercise all logical decisions on their true and false values.

- Execute all loops at their boundaries and within their operational bounds

- Exercise internal data structures to ensure their validity.

White box testing (WBT) is also called Structural or Glass box testing.

Why WBT?

We do WBT because Black box testing is unlikely to uncover numerous sorts of defects in the program. These defects can be of the following nature:

- Logic errors and incorrect assumptions are inversely proportional to the probability that a program path will be executed. Error tend to creep into our work when we design and implement functions, conditions or controls that are out of the program

- The logical flow of the program is sometimes counterintuitive, meaning that our unconscious assumptions about flow of control and data may lead to design errors that are uncovered only when path testing starts.

- Typographical errors are random, some of which will be uncovered by syntax checking mechanisms but others will go undetected until testing begins.

Skills Required

1. Talking theoretically, all we need to do in WBT is to define all logical paths, develop test cases to exercise them and evaluate results i.e. generate test cases to exercise the program logic exhaustively.

2. For this we need to know the program well i.e. We should know the specification and the code to be tested; related documents should be available too us .We must be able to tell the expected status of the program versus the actual status found at any point during the testing process.


Unfortunately in WBT, exhaustive testing of a code presents certain logistical problems. Even for small programs, the number of possible logical paths can be very large. For instance, a 100 line C Language program that contains two nested loops executing 1 to 20 times depending upon some initial input after some basic data declaration. Inside the interior loop four if-then-else constructs are required. Then there are approximately 1014 logical paths that are to be exercised to test the program exhaustively. Which means that a magic test processor developing a single test case, execute it and evaluate results in one millisecond would require 3170 years working continuously for this exhaustive testing which is certainly impractical. Exhaustive WBT is impossible for large software systems. But that doesn’t mean WBT should be considered as impractical. Limited WBT in which a limited no. of important logical paths are selected and exercised and important data structures are probed for validity, is both practical and WBT. It is suggested that white and black box testing techniques can be coupled to provide an approach that that validates the software interface selectively ensuring the correction of internal working of the software.

Tools used for White Box testing:

Few Test automation tool vendors offer white box testing tools which:

1) Provide run-time error and memory leak detection;

2) Record the exact amount of time the application spends in any given block of code for the purpose of finding inefficient code bottlenecks; and

3) Pinpoint areas of the application that have and have not been executed.

Basis Path Testing : Basis path testing is a white box testing technique first proposed by Tom McCabe. The Basis path method enables to derive a logical complexity measure of a procedural design and use this measure as a guide for defining a basis set of execution paths. Test Cases derived to exercise the basis set are guaranteed to execute every statement in the program at least one time during testing.

Flow Graph Notation: The flow graph depicts logical control flow using a diagrammatic notation. Each structured construct has a corresponding flow graph symbol.

Cyclomatic Complexity: Cyclomatic complexity is a software metric that provides a quantitative measure of the logical complexity of a program. When used in the context of a basis path testing method, the value computed for Cyclomatic complexity defines the number for independent paths in the basis set of a program and provides us an upper bound for the number of tests that must be conducted to ensure that all statements have been executed at least once.

An independent path is any path through the program that introduces at least one new set of processing statements or a new condition.

Computing Cyclomatic Complexity: Cyclomatic complexity has a foundation in graph theory and provides us with extremely useful software metric. Complexity is computed in one of the three ways:

1. The number of regions of the flow graph corresponds to the Cyclomatic complexity.

2. Cyclomatic complexity, V(G), for a flow graph, G is defined as
V (G) = E-N+2 Where E, is the number of flow graph edges, N is the number of flow graph nodes.

3. Cyclomatic complexity, V (G) for a flow graph, G is also defined as:
V (G) = P+1 where P is the number of predicate nodes contained in the flow graph G.

Graph Matrices: The procedure for deriving the flow graph and even determining a set of basis paths is amenable to mechanization. To develop a software tool that assists in basis path testing, a data structure, called a graph matrix can be quite useful.
A Graph Matrix is a square matrix whose size is equal to the number of nodes on the flow graph. Each row and column corresponds to an identified node, and matrix entries correspond to connections between nodes.

Control Structure Testing: Described below are some of the variations of Control Structure Testing:

Condition Testing: Condition testing is a test case design method that exercises the logical conditions contained in a program module.

Data Flow Testing: The data flow testing method selects test paths of a program according to the locations of definitions and uses of variables in the program.

Loop Testing: Loop Testing is a white box testing technique that focuses exclusively on the validity of loop constructs. Four classes of loops can be defined: Simple loops, Concatenated loops, nested loops, and unstructured loops.

Simple Loops: The following sets of tests can be applied to simple loops, where ‘n’ is the maximum number of allowable passes through the loop.

1. Skip the loop entirely.

2. Only one pass through the loop.

3. Two passes through the loop.

4. ‘m’ passes through the loop where m is less than n.

5. n-1, n, n+1 passes through the loop.

Nested Loops: If we extend the test approach from simple loops to nested loops, the number of possible tests would grow geometrically as the level of nesting increases.

1. Start at the innermost loop. Set all other loops to minimum values.

2. Conduct simple loop tests for the innermost loop while holding the outer loops at their minimum iteration parameter values. Add other tests for out-of-range or exclude values.

3. Work outward, conducting tests for the next loop, but keep all other outer loops at minimum values and other nested loops to "typical" values.

4. Continue until all loops have been tested.

Concatenated Loops: Concatenated loops can be tested using the approach defined for simple loops, if each of the loops is independent of the other. However, if two loops are concatenated and the loop counter for loop 1 is used as the initial value for loop 2, then the loops are not independent.

Unstructured Loops: Whenever possible, this class of loops should be redesigned to reflect the use of the structured programming constructs.

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