Code-based products — smartphones, games, operating systems, hardware with code, and so on — must go through software testing to detect and correct bugs before going on the market. White box testing, or the method of detecting weaknesses, may be carried out by evaluating the quality characteristics of the built product or by testing the functionality based on specifications. This is a vital aspect of the software development life cycle (SDLC).

White box testing includes searching for bugs and anomalies in binaries and code. The tester investigates not only how the programme responds to different inputs, but also why it behaves as it does. Structural testing, code-based testing, open box testing, and glass box testing are all terminology used to characterise white box testing. These are words that describe how this testing approach examines the internal workings and overall structure of a product.

What Is White Box Testing?

Until evaluating the entire system, you can perform software testing on each module of code (unit testing) and multiple modules (integration testing). There are three main methods used by testers to evaluate a product:

  1. Black box testing,
  2. White box testing, and
  3. Grey box testing.

Black box testing prohibits testers from inspecting the application’s code or structural elements. They find bugs solely by observing the actions of the programme as it is checked against different parameters. The evaluator for white box research must be well-versed in the coding language being used. Since the tester can observe and analyse the operation, it is far more straightforward.

  • The flow of data through the code,
  • The rational paths were taken.
  • Conditional statements have a specific purpose.
  • Functionalities in coding that aren’t well-structured.

Grey box testing combines aspects of both black box and white box testing. It is based on a skewed understanding of an application’s internal workings.

How White Box Testing Works

Executing a sequence of predefined inputs and observing the results is known as white box checking. If there are any anomalies in the outputs, the bugs are registered. The procedure is repeated until all major bugs have been removed by creating and running test cases. The tester must also have a thorough understanding of safe coding practises in order to eliminate any insecure statements that could enable an attacker to insert code or exploit the application to obtain additional data.

Consider the following pseudocode and test cases, which you can use to get started:

example func(int a, int b) 
{  
	if (a>b)    
	Print ("The first value you entered is higher!");  
	else if (a<b)   
	Print ("The second value you entered is higher!");  
	else if (a=b)  
	Print ("The values entered are equal!);  

The test cases for the above could include values such as:

  • a=56, b= 31
  • a=5, b=51
  • a=-2, b=5
  • a=7, b=7

How White Box Testing and Secure Code Review Differ

Despite the fact that both safe code review and white box testing have the same aim of identifying flaws in source code, they are two different methodologies.

Safe code review is mainly concerned with auditing source code for security vulnerabilities and ensuring that sufficient security measures have been enforced in the appropriate locations.
White box testing has a broader reach that can include security enhancements as well as testing other aspects such as performance, code design, and usability.

Furthermore, safe code review does not require physical testing of the product. It entails reading the code and reviewing it in order to find security flaws. The code is physically checked against the established test suites in white box testing, on the other hand. To summarise, white box testing uses the product code to test it, while protected code analysis just reads the code to assess it for vulnerabilities.

Breaking Down the 5 White Box Testing Techniques

There are many types of white box testing methods, each with its own set of coverage criteria, and different resources classify them differently based on the number of criteria. For the purposes of this article, we’ll categorise the techniques using the five parameters below:

  1. Statement coverage
  2. Branch coverage
  3. Condition coverage
  4. Path testing
  5. Data flow testing

The following parts will focus on getting a general understanding of how these methods operate before moving on to some white box testing tools.

Statement Coverage

An instruction or a line of code is referred to as a sentence. The coverage is determined by the number of executed statements divided by the total number of statements. The better the statement coverage, the higher the ratio. Every line of code should ideally execute at least once, and the ultimate goal of this testing phase is to ensure that this happens.

Let’s return to the pseudocode example we mentioned earlier for a moment. What is the statement coverage if we run the first test case (a=56, b=31)?

In the above test case, three of the seven claims are executed. As a result, the coverage in this case is about 42.85 percent. In most projects, however, the minimum suitable coverage target is about 70-80 percent. Write new test cases and re-test the code if the coverage falls short.

Branch Coverage

The number of executed branches divided by the total number of branches in the software is known as branch coverage. The options that arise from a decision statement are referred to as branches (a conditional loop, an if-else clause, etc.). It also includes unconditional branches, with the goal of executing each branch at least once to ensure 100 percent coverage.

Let’s use a flowchart to visualise the sample pseudocode:

There are six divisions in total in the diagram above (highlighted in blue). Only the true branch of the first condition is executed in the first test case (a-56, b=31). 16.67% of the branches are shielded. When you consider the second test case (a=5, b=51), three of the six divisions are protected. This ensures that 50% of the branches are protected.

Condition Coverage

Conditional constructs in programming languages execute statements depending on whether a Boolean expression evaluates to true or false. You want all of the conditions (each part of the Boolean expressions) in the programme to test as true and false at least once with condition coverage, also known as predicate coverage. The ratio of the number of true and false conditions to the total number of conditions is known as condition coverage.

Consider the code below:

void example (float x, float y)
{
if ((x==0) || y>0)
y=y/x;	// statement executed if condition is true
	else
	// statement executed if the above expression is false
}

At least one test case should be considered in this example, where the expression (including the individual sub-expressions) evaluates to true and false (so that the else condition executes). The next sentence would result in a division by zero error if the condition x=0 evaluates to true. To rule out any exceptions, it’s critical to assess all possible outcomes.

Path Testing

In a control flow graph, a route is the path from the starting node to the terminal node. There may be several routes and terminal nodes. If you try to cover all possible paths in the presence of loops, the number of paths can become incredibly high.

In path testing, the test suite should perform all linearly independent paths in order for the tests to achieve path coverage. McCabe’s cyclomatic metric can be used to count the number of linearly independent paths in a programme. The higher the resultant number, the more complicated and complex the code. This software quality metric offers a quantitative measure of testing complexity and reliability.

1. while (a>b){	
2. 	a=a-1;
3. 	b=b+a;}
4. 	c=a+b;

The cyclomatic complexity V(G) of a control flow graph G is measured as V(G)=E-N+2, where N is the number of nodes in G and E is the number of edges. Since there are four edges and four nodes in this case, the cyclomatic complexity value is two. This means you’ll need at least two test cases because there are two linearly independent paths.

If the McCabe metric for any CFG is a higher value, such as 12, it means that a minimum of 12 test cases would be expected, raising not only the degree of complexity but also the probability of missing possible bugs. Furthermore, you can only compute the smallest number of test cases necessary, but that doesn’t tell us how to create those test cases. As a result, it’s not a viable option for larger projects.

Data Flow Testing

Data flow research focuses on the places in the software where variables are described and used. It examines how data flows across these variables and can detect inconsistencies in the program’s logical constructs. It can, for example, assist you in detecting attempts to use a variable without first initialising it or in failing to use an initialised variable in the programme.

Consider the following pseudocode as an example:

1. read (a, b)
2. if(a>=b)
3. x = a+1
4. else x = b-1
5. print x

Let’s look at the CFG for the previous example:

It’s called a predicate usage when the value of a variable defines an execution path (for example, in a while loop) (p-use). Computation usage is when the value of a variable is used to determine an output or to define another variable (c-use).

Node 1 defines the variables a and b, which are used on nodes 2,3 and 2,4 respectively. On nodes 3, 4, and 5, the variable x is specified and used.

The Advantages and Disadvantages of White Box Testing

Because of its resource-intensive and rigorous design, white box testing is commonly used for mission-critical applications and systems. Although it gives us more insight into an application’s internal workings, there are several disadvantages to consider. Let’s look at the advantages and disadvantages of using this testing method.

Advantages of White Box Testing Technique

The following are some of the benefits of using white box testing:

Efficient Code Optimization: The resulting code can be designed to eliminate bugs and satisfy requirements.
White box testing is easy to automate and integrate with the SDLC process, allowing for early detection of anomalies.
Comprehensive Testing: White box testing is a systematic process that ensures the evaluation of all structural elements and code, based on the defined minimum acceptable coverage criteria.

Disadvantages of White Box Testing Techniques

White box research, like almost everything else in life, isn’t flawless and has limitations. The following are some of the flaws:

  • Complexity: Depending on the size of the application and the scope of testing, white box testing can be a time-consuming and costly process.
  • Cost and effort intensive: Finding the right resources with the right skill set and ability to do extensive testing can be difficult.
  • Time Consuming: White box testing takes time, especially for larger applications with more stringent code coverage requirements. This method of testing can trigger unanticipated delays, especially if serious bugs are found later in the software development lifecycle.
  • Susceptible to Human Errors: Human error is always a possibility, particularly when performing manual tests.

White Box Testing Tools

White box testing can be done with a variety of instruments, much like testing techniques. The following are a few of the more famous ones:

  • Veracode — Veracode provides a scalable, automated testing solution that works in tandem with the development process to reduce the cost of bug fixes.
  • RCUNIT — RCUNIT is a system for analysing C programmes. It’s open source and can be used under the terms of the MIT License.
  • NUnit — NUnit is a free and open-source unit testing platform for Java applications.
    The language of the internet.
  • JUnit — Junit is a Java application testing platform.
  • PyUnit is a Python unit testing platform that is a Python language variant of Junit.

Other tools, such as JsUnit, CppUnit, EMMA, Googletest, and cfix, may be useful depending on the programming language.

Final Thoughts

By now, you should have a good understanding of what white box testing is, how certain white box testing methods operate, and what resources are available to use. We’ve also spoken about what white box testing isn’t, how it varies from other forms of testing like black box and grey box, and how it differs from protected code review.

Consider the advantages and disadvantages of each approach when deciding which method is best for evaluating your application. Make your decision based on your unique requirements and resource availability. Most companies and developers sign their code with a code signing certificate after checking it. This is done before shipping the software. This is done to establish their identity, reassure users that the code has not been tampered with, and prevent the Windows SmartScreen “Unknown Publisher” warning.

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