PlanningValidator::isAllValid increases in cyclomatic complexity from 16 to 17, threshold = 9

A Complex Method has a high cyclomatic complexity. The recommended threshold for the C++ language is a cyclomatic complexity lower than 9.

There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using EXTRACT FUNCTION. Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the DECOMPOSE CONDITIONAL refactoring.

PlanningValidator::checkTrajectoryShift has a cyclomatic complexity of 13, threshold = 9

A Complex Method has a high cyclomatic complexity. The recommended threshold for the C++ language is a cyclomatic complexity lower than 9.

There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using EXTRACT FUNCTION. Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the DECOMPOSE CONDITIONAL refactoring.

PlanningValidator::checkValidLongitudinalDistanceDeviation has a cyclomatic complexity of 10, threshold = 9

A Complex Method has a high cyclomatic complexity. The recommended threshold for the C++ language is a cyclomatic complexity lower than 9.

There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using EXTRACT FUNCTION. Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the DECOMPOSE CONDITIONAL refactoring.

PlanningValidator::publishTrajectory has a cyclomatic complexity of 10, threshold = 9

A Complex Method has a high cyclomatic complexity. The recommended threshold for the C++ language is a cyclomatic complexity lower than 9.

There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using EXTRACT FUNCTION. Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the DECOMPOSE CONDITIONAL refactoring.

PlanningValidator::setupDiag has 90 lines, threshold = 70

Overly long functions make the code harder to read. The recommended maximum function length for the C++ language is 70 lines of code. Severity: Brain Method - Complex Method - Long Method.

We recommend to be careful here -- just splitting long functions don't necessarily make the code easier to read. Instead, look for natural chunks inside the functions that expresses a specific task or concern. Often, such concerns are indicated by a Code Comment followed by an if-statement. Use the EXTRACT FUNCTION refactoring to encapsulate that concern.

PlanningValidator::setupParameters has 71 lines, threshold = 70

Overly long functions make the code harder to read. The recommended maximum function length for the C++ language is 70 lines of code. Severity: Brain Method - Complex Method - Long Method.

We recommend to be careful here -- just splitting long functions don't necessarily make the code easier to read. Instead, look for natural chunks inside the functions that expresses a specific task or concern. Often, such concerns are indicated by a Code Comment followed by an if-statement. Use the EXTRACT FUNCTION refactoring to encapsulate that concern.

PlanningValidator::checkValidLongitudinalDistanceDeviation has 2 blocks with nested conditional logic. Any nesting of 2 or deeper is considered. Threshold is one single, nested block per function

A Bumpy Road is a function that contains multiple chunks of nested conditional logic inside the same function. The deeper the nesting and the more bumps, the lower the code health.

A bumpy code road represents a lack of encapsulation which becomes an obstacle to comprehension. In imperative languages there’s also an increased risk for feature entanglement, which leads to complex state management. CodeScene considers the following rules for the code health impact: 1) The deeper the nested conditional logic of each bump, the higher the tax on our working memory. 2) The more bumps inside a function, the more expensive it is to refactor as each bump represents a missing abstraction. 3) The larger each bump – that is, the more lines of code it spans – the harder it is to build up a mental model of the function. The nesting depth for what is considered a bump is levels of conditionals.

Bumpy Road implementations indicate a lack of encapsulation. Check out the detailed description of the Bumpy Road code health issue.

A Bumpy Road often suggests that the function/method does too many things. The first refactoring step is to identify the different possible responsibilities of the function. Consider extracting those responsibilities into smaller, cohesive, and well-named functions. The EXTRACT FUNCTION refactoring is the primary response.

This module has a mean cyclomatic complexity of 4.52 across 29 functions. The mean complexity threshold is 4

Overall Code Complexity is measured by the mean cyclomatic complexity across all functions in the file. The lower the number, the better.

Cyclomatic complexity is a function level metric that measures the number of logical branches (if-else, loops, etc.). Cyclomatic complexity is a rough complexity measure, but useful as a way of estimating the minimum number of unit tests you would need. As such, prefer functions with low cyclomatic complexity (2-3 branches).

You address the overall cyclomatic complexity by a) modularizing the code, and b) abstract away the complexity. Let's look at some examples:

Modularizing the Code: Do an X-Ray and inspect the local hotspots. Are there any complex conditional expressions? If yes, then do a DECOMPOSE CONDITIONAL refactoring. Extract the conditional logic into a separate function and put a good name on that function. This clarifies the intent and makes the original function easier to read. Repeat until all complex conditional expressions have been simplified.

In this module, 38.2% of all function arguments are primitive types, threshold = 30.0%

Code that uses a high degree of built-in, primitives such as integers, strings, floats, lacks a domain language that encapsulates the validation and semantics of function arguments. Primitive Obsession has several consequences: 1) In a statically typed language, the compiler will detect less erroneous assignments. 2) Security impact since the possible value range of a variable/argument isn't retricted.

In this module, 38 % of all functions have primitive types as arguments.

Primitive Obsession indicates a missing domain language. Introduce data types that encapsulate the details and constraints of your domain. For example, instead of int userId, consider User clicked.

generateShiftedTrajectory has 1 complex conditionals with 2 branches, threshold = 2

A complex conditional is an expression inside a branch such as an if-statmeent which consists of multiple, logical operations. Example: if (x.started() && y.running()).Complex conditionals make the code even harder to read, and contribute to the Complex Method code smell. Encapsulate them.

Apply the DECOMPOSE CONDITIONAL refactoring so that the complex conditional is encapsulated in a separate function with a good name that captures the business rule. Optionally, for simple expressions, introduce a new variable which holds the result of the complex conditional.

getNodeOptionsWithDefaultParams has 75 lines, threshold = 70

Overly long functions make the code harder to read. The recommended maximum function length for the C++ language is 70 lines of code. Severity: Brain Method - Complex Method - Long Method.

We recommend to be careful here -- just splitting long functions don't necessarily make the code easier to read. Instead, look for natural chunks inside the functions that expresses a specific task or concern. Often, such concerns are indicated by a Code Comment followed by an if-statement. Use the EXTRACT FUNCTION refactoring to encapsulate that concern.

The ratio of primitive types in function arguments decreases from 81.48% to 77.42%, threshold = 30.0%