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How to evaluate the maintenance cost of Java functions?

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2024-04-19 21:51:01375browse

How to evaluate the maintenance cost of Java functions? Assessing maintenance costs involves the following steps: Code complexity analysis: Measures code complexity such as cyclomatic complexity and cognitive complexity. Testability analysis: Measures how easily a function is testable, such as test coverage and testability metrics. Code quality analysis: Measures how well the code follows specifications, such as line count of source code and code specification checks.

How to evaluate the maintenance cost of Java functions?

#How to evaluate the maintenance cost of Java functions?

The cost of maintaining Java functions is an important consideration in software development because it affects the overall lifecycle cost of the application. Assessing maintenance costs helps determine a function's complexity, testability, and code quality to develop an appropriate maintenance strategy.

Code Complexity Analysis

The code complexity metric measures the complexity of a block of code. Higher complexity indicates that more time and effort are required for maintenance. The following are some commonly used complexity measures:

import com.google.common.collect.Range;
import edu.umd.cs.findbugs.annotations.ExpectWarning;
import java.util.Comparator;

public class ExampleClass {

    @ExpectWarning("NP_METHOD_PARAMETER_TIGHTENS_ANNOTATION")
    public void annotatedExample(Comparable<Integer> i, Comparable<Integer> j) {
        boolean z = i.compareTo(j) == 0;
        Range<Integer> range = Range.closedOpen(0, z ? 1 : 0);
    }

    public static void main(String[] args) {
        Comparator<? super String> comparator = Comparator.comparing(String::toString);
    }
}
  • Cyclomatic complexity (Cyclomatic complexity): Measures the number of paths in a function. Cyclomatic Functions with a complexity greater than 10 are generally considered complex.
  • Cognitive complexity: Measures the cognitive effort required to understand a function. Functions with a cognitive complexity greater than 15 are generally considered difficult to maintain.

Testability analysis

Testability metric measures how easy a function is to test. Functions that are more testable are easier to maintain because test cases can be easily added and executed. Here are some testability metrics:

  • Test Coverage: Measures the ratio of lines of code that were executed to all lines of code. Functions with test coverage above 80% are generally considered testable.
  • Testability Metrics: Measures properties of a function such as number of methods, nesting depth, and dependencies. Functions with higher testability metrics are generally easier to test.

Code Quality Analysis

Code quality metrics measure how code is written and how well it adheres to coding specifications. Functions with high code quality tend to be easier to maintain because they are more organized and easier to read and understand. Here are some code quality metrics:

  • Lines of Source Code (LOC): Measures the number of lines of code in a function. Functions with less LOC are generally easier to maintain.
  • Code specification check: Check whether the function conforms to predefined code specifications, such as indentation, naming conventions and comments. Complying with code standards improves code readability and maintainability.

Practical case

Let us consider the following Java function:

public static int calculateAverage(int[] numbers) {
    int sum = 0;
    for (int number : numbers) {
        sum += number;
    }
    return sum / numbers.length;
}
  • Code complexity: Cyclomatic complexity is 1, Cognitive complexity is 3.
  • Testability: Test coverage is 100%.
  • Code quality: LOC is 8, comply with code specifications.

Based on these metrics, we can estimate that the cost of maintaining this function is relatively low. It's straightforward, easy to test, and adheres to coding standards.

Conclusion

You can understand the maintenance cost of a function by evaluating code complexity, testability, and code quality. Using these metrics, software developers can develop effective maintenance strategies to ensure continued availability and reliability of their applications.

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