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General Principles

Authored by: Owen Feehan


Do not repeat yourself. By eliminating duplication in code, the code becomes better structured and is easier to understand and maintain. SonarQube automatically checks for duplicated code patterns.

Encapsulate enthusiastically

Hide as much internal detail with private methods and classes, so only the necessary external interfaces between components are apparent. The encapsulation should occur on each of a function / class / package level.

Keep functions small

  • Bury detail in private helper functions, which are called from a function expressing higher-level logic.
  • Prefer many small functions to few large functions, but also keep classes small, by factoring out methods to helper classes, and packages small by splitting them up if they grow large.

Strive for high cohesion and low coupling.

Use polymorphism for alternative operations

Avoid switch-cases or flags in favour of abstract-base-classes. Apply SOLID design principles, especially dependency inversion.

Instantiating abstract-base-classes via BeanXML is encouraged to give inversion-of-control and dependency injection, but not for minor detail. Every polymorphic class does not need to be an AnchorBean.


Document parameters to public interfaces rigorously and systematically (not always obeyed at present!), but private functions only partially or not at all, as best judgment allows.

Creating a small function with a clear understandable name is preferable to a comment above several lines of code.

Avoid premature optimization

Parts of the codebase suffer from being in Java instead of native code, or could be made performance at the expense of cleaner code. But these are rare, and should be tackled only when clearly necessary.


The more tests the better, but coverage is currently low on Anchor’s (large) code base. Concentrate and enhance coverage around problematic areas, especially after a bug-fix.


Use Optional instead of nullable variables.

Prefer to avoid variables that can be null in favour of Optional.

Strongly avoid nullable-variables in function interfances (arguments in and out of a function). When deviating from this rule, very clearly document it in the Javadoc.

Prefer functional-style inside classes.

Prefer immutable data structures, and functions without side-effects, unless it clashes with the design of a system component or a third-party library, or creates an impactful performance penalty.

The final keyword can be useful to indicate immutable variables, but it’s good to generally indicate that class/function is immutable in its Javadoc.



Always use Python’s type-hints to document the type of each argument in and out of functions. It helps create understandable code and provides for a certain amount of automated checking at build time.


Use sphinx-style docstrings.

Prefer from package import style for internal modules

Avoid needlessly exposing package-internal functions and classes by:

  • prefixing functions and filenames with _
  • exposing only where needed functions/classes outside the packages via the package’s __init__.py (also in a nested way between hierarchies of sub-packages).
  • __all__ if it helps.

This means internal packages should only ordinarily be imported via from package import and not import package as the former uses the __init__.py.


Use . as a prefix for private functions

The R language does not have any equivalent of private for only-internally-used functions. As a workaround, prefix such a function conventionally with a period. This promises only be called from the current source-file. e.g.

.some_private_function <- function() {
	# Function contents
Tags: architecture