Exploring Code Coverage Testing | What Is Code Coverage Testing ?

Code Coverage:

Code insurance is a crucial software program trying out metric, also called Code Coverage Testing. It assesses the quantity to which the supply code of a software application has been examined. This metric is instrumental in evaluating the first-rate of the take a look at suite and studying the thoroughness of software program verification. Code coverage is considered a shape of white container checking out, because it involves examining the internal structure and common sense of the code.

Purpose and Calculation:

At the cease of the improvement cycle, clients count on splendid software merchandise. Developers are answerable for handing over such merchandise, ensuring overall performance, capability, correctness, reliability, effectiveness, protection, and maintainability. Code coverage performs a sizeable position in assessing the performance and fine components of software program.

The components to calculate code coverage is:

Code Coverage = (Number of traces of code carried out) / (Total Number of lines of code in a machine element) * 100

  • Code Coverage Criteria:
    • Several criteria are taken into consideration for code insurance analysis:

  • Statement Coverage/Block Coverage:
    • Measures the wide variety of statements correctly achieved inside the program's supply code.
    • Formula: (Number of statements accomplished) / (Total Number of statements) * a hundred

  • Decision Coverage/Branch Coverage:
    • Evaluates the quantity of choice manipulate structures correctly achieved within the program's supply code.
    • Formula: (Number of selection/branch outcomes exercised) / (Total quantity of choice results in the supply code) * 100

  • Function Coverage:
    • Determines the quantity of functions called and executed at the least once in the source code.
    • Formula: (Number of functions known as) / (Total variety of capabilities) * a hundred

  • Condition Coverage/Expression Coverage:
    • Examines the quantity of Boolean situation/expression statements accomplished in conditional statements.
    • Formula: (Number of completed operands) / (Total Number of Operands) * a hundred

Types of Code Coverage :

  •  Function Coverage 
    •  Makes sure that all the functions that are written in the code will be invoked at least one time. 
    •  Example: In a calculator application, function coverage would make sure that at least the addition, subtraction, multiplication or division are executed at least once. 

  •  Statement Coverage 
    •  Ensures that every statement in the computational code is executed, and in the best possible order. 
    •  Example: In an if-else statement, the if and else blocks should run through their codes normally they should be executed. 

  •  Branch Coverage 
    •  Verifies that all possible branches of a decision point (true/false) are run. 
    •  Example: **Branch coverage** In a decision point like if (x > 0), branch coverage would test both when x >  0 and when x is not. 

  •  Condition Coverage 
    •  Guarantees that each of the boolean expressions is evaluated at least to true and to false. 
    •  Example: In a condition like if (a && b), the condition coverage would act like if both are true, both are false, a is true while b is false or vice versa. 

  •  Path Coverage 
    •  Confirms that each statement in a condense form goes through unit testing. 
    •  Example: In a function with many if-else structures, path coverage checks all paths of its execution.

Extended Types of Code Coverage Tests :

  •  Loop Coverage 
    •  Definition: Checks that loops in the code should run zero times, once, or many times. 
    •  Example: And if the loop is of the type for (int i = 0; i < n; i++) then loop coverage would provide test cases with n as 0, 1 and more than 1. 
  •  Parameter Value Coverage 
    •  Definition: It makes a guarantee that those functions or methods are run through a range of test data or parameter, especially those in boundaries. 
    •  Example: Regarding the function calculate_discount(price, discount_rate), parameter value coverage would include testing with the values on the border of the range of rates, such as 0 %, 100 %, and average intermediate values. 
  •  Multiple Condition Coverage 
    •  Definition: This increases coverage by making sure that in decision statements all combinations of conditions are tested for the condition outcomes they contain. 
    •  Example: When it comes to a condition such as if (a && (b || c)) the multiple condition coverage would check all possibilities of a, b and c being either true or false. 
  •  State Coverage 
    •  Definition: It means that all the states possible in a state machine or state diagram or all paths need to have the testing done on it. 
    •  Example: State coverage would then validate all the states including; “logged out”, “logged in”, “password reset”, and “account locked”. 
  •  Exception Coverage 
    •  Definition: Fulfills the stewardship of checking for all possible scapegoats as well as rearing up to ascertain that all conceivable error circumstances are garnered and addressed competently. 
    •  Example: In the case of a function that reads a file, then the exception coverage would include the situation where the file does not exist, or the file is in a format that the function cannot read or the function does not have the right to access the file.

General Approaches to Increasing the Code Coverage :

  •  Test-Driven Development (TDD) 
    •  Pretend tests before the actual codes guarantee that every new code is going to be tested. 
    •  As to the performed comparison, it can be stated that it stimulates better design and contributes to higher coverage from the initial stage. 
  •  Behavior-Driven Development (BDD) 
    •  Thorough testing of the behavior of an application without the main concern being the details of its implementation. 
    •  Interacts in plain natural language to describe tests making it easier to ensure that tests are well covered. 
  •  Code Reviews 
    •  Code reviews cover respective part of the code functions in intervals until one realizes that some parts of the code are not covered. 
    •  Another advantage of getting peer reviews is that the peers can speak about other exceptional circumstances that we might not have considered and additional scenarios that we should test. 
  •  Continuous Integration (CI) 
    •  By including code coverage tools in the CI, it becomes a requirement to always check the coverage every time there is a build. 
    •  Notifications also keep coverage >95% in the long run, and reports are provided by the system.

Coverage Metrics Used in Assessing the Degree of Code Testing :

  •  Coverage Percentage 
    •  The simplest one, which is considered to be the ratio of the tested lines of code to the total number of lines of code. 
    •  Example: 85% statement coverage means that 85% of all the statements in source code which have the potential of being executed are, during the testing process, exercised at least once. 
  •  Coverage Gaps 
    •  Determines segments of the code that are left uncovered when only the corresponding tests are run. 
    •  Assists in identifying precise lines or functions that require more tests. 
  •  Cyclomatic Complexity 
    •  Assesses the levels of complexity in a code by the counting the number of possibilities that one can have while moving through the code. 
    •  It is rather clear that more cyclomatic complexity is associated with more testing paths and possibly areas that could require refactoring. 
  •  Mutation Testing 
    •  Changed in small and constant<|reserved_special_token_263|> with the help of mutations and tests to observe whether they identify it or not. 
    •  Supports the tests and makes certain that any errors are not going to go unnoticed.

Tools for Code Coverage:

Several gear facilitate code coverage evaluation, including :-

  • JaCoCo (Java Code Coverage)
  • Cobertura (Java)
  • Istanbul (JavaScript)
  • Coverage.py (Python)
  • gcov (C/C++)

Advantages of Using Code Coverage:

  • Determines software overall performance and first-class.
  • Evaluates quantitative measures of code insurance.
  • Facilitates smooth renovation of the codebase.
  • Assesses the nice and comprehensiveness of the take a look at suite.
  • Exposes horrific, lifeless, and unused code.
  • Helps in growing extra check cases to beautify coverage.
  • Increases productiveness and efficiency in software program improvement.
  • Measures the effectiveness of test implementation.
  • Identifies uncovered regions for new test instances.

Disadvantages of Using Code Coverage:

  • May fail to cover code completely and as it should be.
  • Does not guarantee testing of all possible feature values.
  • Cannot make sure perfect code coverage.
  • Requires extra mock statistics for some take a look at documents.
  • Difficult to cowl check instances for occasion-handling functions.
  • Complex code may require a large number of take a look at instances to increase coverage.
  • Requires developers to own sturdy understanding of writing unit test cases to cowl all viable scenarios.

Example of Code Coverage Testing:

Consider a simple function that checks if a number is prime:
def is_prime(n):
    if n <= 1:
        return False
    for i in range(2, n):
        if n % i == 0:
            return False
    return True
To achieve complete code coverage, we need to ensure all paths and conditions within this function are tested. Here's how we can do that:
  • Test Case for Non-Prime Number
    • Input: 4
    • Expected Output: False
  • Test Case for Prime Number
    • Input: 5
    • Expected Output: True
  • Test Case for Number Less Than or Equal to 1
    • Input: 1
    • Expected Output: False
    • Input: 0
    • Expected Output: False
    • Input: -5
    • Expected Output: False

Here's the reference video for you to watch and better understand the topic:

Conclusion:

Code coverage is a valuable tool in software program checking out, presenting insights into the thoroughness of checking out efforts and the first-rate of the software product. However, it's far important to apprehend its limitations and supplement it with other trying out methodologies for comprehensive software validation.

Code coverage testing obviously remains an important practice in the software development processes. It gives a numerical figure to the amount of testing done to your code and checks every line of your code for execution. Code coverage assists the developer in finding more undiscovered code, getting better quality assessment of the tests run, executing better measures in defining dead code, and providing proper testing for all aspects of the code. Introduction of code coverage testing into the development process makes the software of better quality, improves the efficiency of tests and, in general, provide more effective and confident releases.

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