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Refactoring is usually motivated by noticing a code smell. [2] For example, the method at hand may be very long, or it may be a near duplicate of another nearby method. Once recognized, such problems can be addressed by refactoring the source code, or transforming it into a new form that behaves the same as before but that no longer "smells".
A convolutional code that is terminated is also a 'block code' in that it encodes a block of input data, but the block size of a convolutional code is generally arbitrary, while block codes have a fixed size dictated by their algebraic characteristics. Types of termination for convolutional codes include "tail-biting" and "bit-flushing".
Pylint is a static code analysis tool for the Python programming language. It is named following a common convention in Python of a "py" prefix, and a nod to the C programming lint program. It follows the style recommended by PEP 8, the Python style guide. [4] It is similar to Pychecker and Pyflakes, but includes the following features:
In software engineering, rubber duck debugging (or rubberducking) is a method of debugging code by articulating a problem in spoken or written natural language. The name is a reference to a story in the book The Pragmatic Programmer in which a programmer would carry around a rubber duck and debug their code by forcing themselves to explain it ...
The definition of the term varies depending upon the community using it. In Ruby, [2] Python, [3] and many other dynamic programming languages, the term monkey patch only refers to dynamic modifications of a class or module at runtime, motivated by the intent to patch existing third-party code as a workaround to a bug or feature which does not act as desired.
Automatic bug fixing is made according to a specification of the expected behavior which can be for instance a formal specification or a test suite. [5]A test-suite – the input/output pairs specify the functionality of the program, possibly captured in assertions can be used as a test oracle to drive the search.
These tools look for a very specific set of known problems, some common and some rare, within the source code, concentrating more on the semantics (e.g. data flow) rather than the syntax, as compilers and interpreters do. Both commercial and free tools exist for various languages; some claim to be able to detect hundreds of different problems.
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