Difference between revisions of "Code Auto-Completion System"

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== References ==
 
== References ==
  
=== 2019 ===
+
=== 2019a ===
 
* (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Autocomplete#In_source_code_editors Retrieved:2019-10-11.
 
* (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Autocomplete#In_source_code_editors Retrieved:2019-10-11.
 
** Autocomplete of source code is also known as '''code completion'''. In a [[source code editor]] autocomplete is greatly simplified by the regular structure of the [[programming language]]s. There are usually only a limited number of words meaningful in the current context or [[namespace]], such as names of variables and functions. An example of code completion is [[Microsoft]]'s [[IntelliSense]] design. It involves showing a pop-up list of possible completions for the current input prefix to allow the user to choose the right one. This is particularly useful in [[object-oriented programming]] because often the programmer will not know exactly what members a particular [[class (computer science)|class]] has. Therefore, autocomplete then serves as a form of convenient documentation as well as an input method. Another beneficial feature of autocomplete for source code is that it encourages the programmers to use longer, more descriptive variable names incorporating both lower and upper case letters ([[CamelCase]]), hence making the [[source code]] more readable. Typing large words with many mixed cases like "numberOfWordsPerParagraph" can be difficult, but Autocomplete allows one to complete typing the word using a fraction of the keystrokes.
 
** Autocomplete of source code is also known as '''code completion'''. In a [[source code editor]] autocomplete is greatly simplified by the regular structure of the [[programming language]]s. There are usually only a limited number of words meaningful in the current context or [[namespace]], such as names of variables and functions. An example of code completion is [[Microsoft]]'s [[IntelliSense]] design. It involves showing a pop-up list of possible completions for the current input prefix to allow the user to choose the right one. This is particularly useful in [[object-oriented programming]] because often the programmer will not know exactly what members a particular [[class (computer science)|class]] has. Therefore, autocomplete then serves as a form of convenient documentation as well as an input method. Another beneficial feature of autocomplete for source code is that it encourages the programmers to use longer, more descriptive variable names incorporating both lower and upper case letters ([[CamelCase]]), hence making the [[source code]] more readable. Typing large words with many mixed cases like "numberOfWordsPerParagraph" can be difficult, but Autocomplete allows one to complete typing the word using a fraction of the keystrokes.
 
+
=== 2019b ===
 +
* (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Autocomplete#In_command-line_interpreters Retrieved:2019-10-12.
 +
** In a [[command-line interpreter]], such as [[Unix]]'s [[Bourne shell|sh]] or [[Bash (Unix shell)|bash]], or [[Microsoft Windows|Windows]]'s [[cmd.exe]] or [[PowerShell]], or in similar [[command line interface]]s, autocomplete of command names and file names may be accomplished by keeping track of all the possible names of things the user may access. Here autocomplete is usually done by pressing the [[Tab key|Tab key]] key after typing the first several letters of the word. For example, if the only file in the current directory that starts with x is xLongFileName, the user may prefer to type x and autocomplete to the complete name. If there were another file name or command starting with x in the same scope, the user would type more letters or press the Tab key repeatedly to select the appropriate text.
 
=== 2018a ===
 
=== 2018a ===
 
* ([[2018_ASurveyofMachineLearningforBigC|Allamanis et al., 2018]]) ⇒ [[author::Miltiadis Allamanis]], [[author::Earl T. Barr]], [[author::Premkumar Devanbu]], and [[author::Charles Sutton]]. ([[year::2018]]). “[https://arxiv.org/pdf/1709.06182.pdf A Survey of Machine Learning for Big Code and Naturalness].” In: ACM Computing Surveys (CSUR) Journal, 51(4). [http://dx.doi.org/10.1145/3212695 doi:10.1145/3212695]  
 
* ([[2018_ASurveyofMachineLearningforBigC|Allamanis et al., 2018]]) ⇒ [[author::Miltiadis Allamanis]], [[author::Earl T. Barr]], [[author::Premkumar Devanbu]], and [[author::Charles Sutton]]. ([[year::2018]]). “[https://arxiv.org/pdf/1709.06182.pdf A Survey of Machine Learning for Big Code and Naturalness].” In: ACM Computing Surveys (CSUR) Journal, 51(4). [http://dx.doi.org/10.1145/3212695 doi:10.1145/3212695]  
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[[Category:Computational Linguistics]]
 
[[Category:Computational Linguistics]]
 
__NOTOC__
 
__NOTOC__
 
=== 2019 ===
 
* (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Autocomplete#In_command-line_interpreters Retrieved:2019-10-12.
 
** In a [[command-line interpreter]], such as [[Unix]]'s [[Bourne shell|sh]] or [[Bash (Unix shell)|bash]], or [[Microsoft Windows|Windows]]'s [[cmd.exe]] or [[PowerShell]], or in similar [[command line interface]]s, autocomplete of command names and file names may be accomplished by keeping track of all the possible names of things the user may access. Here autocomplete is usually done by pressing the [[Tab key|Tab key]] key after typing the first several letters of the word. For example, if the only file in the current directory that starts with x is xLongFileName, the user may prefer to type x and autocomplete to the complete name. If there were another file name or command starting with x in the same scope, the user would type more letters or press the Tab key repeatedly to select the appropriate text.
 

Revision as of 06:08, 12 October 2019

A Code Auto-Completion System is an Auto-Completion System that can solve a Code Auto-Completion Task by implementing a Code Auto-Completion Algorithm.



References

2019a

  • (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Autocomplete#In_source_code_editors Retrieved:2019-10-11.
    • Autocomplete of source code is also known as code completion. In a source code editor autocomplete is greatly simplified by the regular structure of the programming languages. There are usually only a limited number of words meaningful in the current context or namespace, such as names of variables and functions. An example of code completion is Microsoft's IntelliSense design. It involves showing a pop-up list of possible completions for the current input prefix to allow the user to choose the right one. This is particularly useful in object-oriented programming because often the programmer will not know exactly what members a particular class has. Therefore, autocomplete then serves as a form of convenient documentation as well as an input method. Another beneficial feature of autocomplete for source code is that it encourages the programmers to use longer, more descriptive variable names incorporating both lower and upper case letters (CamelCase), hence making the source code more readable. Typing large words with many mixed cases like "numberOfWordsPerParagraph" can be difficult, but Autocomplete allows one to complete typing the word using a fraction of the keystrokes.

2019b

  • (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Autocomplete#In_command-line_interpreters Retrieved:2019-10-12.
    • In a command-line interpreter, such as Unix's sh or bash, or Windows's cmd.exe or PowerShell, or in similar command line interfaces, autocomplete of command names and file names may be accomplished by keeping track of all the possible names of things the user may access. Here autocomplete is usually done by pressing the Tab key key after typing the first several letters of the word. For example, if the only file in the current directory that starts with x is xLongFileName, the user may prefer to type x and autocomplete to the complete name. If there were another file name or command starting with x in the same scope, the user would type more letters or press the Tab key repeatedly to select the appropriate text.

2018a

  1. See https://qz.com/1034972/ for a popular account of the effect of large-scale datasets in computer Vision.

2018b

2009