AssetsController::PlateLayout#good_well_at? performs a nil-check Open
%i[request asset].all? { |field| not well[field].nil? }
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A NilCheck
is a type check. Failures of NilCheck
violate the "tell, don't ask" principle.
Additionally, type checks often mask bigger problems in your source code like not using OOP and / or polymorphism when you should.
Example
Given
class Klass
def nil_checker(argument)
if argument.nil?
puts "argument isn't nil!"
end
end
end
Reek would emit the following warning:
test.rb -- 1 warning:
[3]:Klass#nil_checker performs a nil-check. (NilCheck)
AssetsController::PlateLayout#bad_well_at? performs a nil-check Open
not well[:error].nil?
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- Exclude checks
A NilCheck
is a type check. Failures of NilCheck
violate the "tell, don't ask" principle.
Additionally, type checks often mask bigger problems in your source code like not using OOP and / or polymorphism when you should.
Example
Given
class Klass
def nil_checker(argument)
if argument.nil?
puts "argument isn't nil!"
end
end
end
Reek would emit the following warning:
test.rb -- 1 warning:
[3]:Klass#nil_checker performs a nil-check. (NilCheck)
AssetsController::PlateLayout takes parameters ['column', 'row'] to 6 methods Open
def cell_name_for_well_at(row, column)
Map.find_by(location_id: ((row * width) + column + 1), asset_size: size).description
end
def location_for_well_at(row, column)
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In general, a Data Clump
occurs when the same two or three items frequently appear together in classes and parameter lists, or when a group of instance variable names start or end with similar substrings.
The recurrence of the items often means there is duplicate code spread around to handle them. There may be an abstraction missing from the code, making the system harder to understand.
Example
Given
class Dummy
def x(y1,y2); end
def y(y1,y2); end
def z(y1,y2); end
end
Reek would emit the following warning:
test.rb -- 1 warning:
[2, 3, 4]:Dummy takes parameters [y1, y2] to 3 methods (DataClump)
A possible way to fix this problem (quoting from Martin Fowler):
The first step is to replace data clumps with objects and use the objects whenever you see them. An immediate benefit is that you'll shrink some parameter lists. The interesting stuff happens as you begin to look for behavior to move into the new objects.