國立虎尾科技大學 |

Applying Natural Language Processing Techniques to Code.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Applying Natural Language Processing Techniques to Code./
作者:	Stein, Aviel J.
面頁冊數:	1 online resource (92 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-02, Section: B.
Contained By:	Dissertations Abstracts International84-02B.
標題:	Information science. -
電子資源:	click for full text (PQDT)
ISBN:	9798837525506

Applying Natural Language Processing Techniques to Code.
Stein, Aviel J.

Applying Natural Language Processing Techniques to Code. - 1 online resource (92 pages)

Source: Dissertations Abstracts International, Volume: 84-02, Section: B.

Thesis (Ph.D.)--Drexel University, 2022.

Includes bibliographical references

Analyzing source code is becoming a helpful method as the amount of code and the number of coders increases. Developing software is a mentally strenuous activity because it involves understanding and formalizing solutions to complex problems. As solutions are adapted and the problem themselves change, the code changes with it. Traditionally, source code analysis (SCA) uses methods and tools that rely on the rigid structure of code to work, and while useful, are not always able to adapt to new information and code. By comparison, the natural language processing (NLP) field leverages naturally occurring patterns within natural language text to help people understand and interpret text robustly on a large scale. This works shows that methods from NLP can be applied to code to extract information automatically in broad and more adaptable ways. We show several examples of how techniques developed for NLP can be successfully applied to software to create source code tools that can help developers improve source code.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798837525506Subjects--Topical Terms:

561178
Information science.
Subjects--Index Terms:

Artificial intelligenceIndex Terms--Genre/Form:

554714
Electronic books.

Applying Natural Language Processing Techniques to Code.
LDR:02439ntm a22004217 4500 001 1147228
005 20240909100731.5
006 m o d
007 cr bn ---uuuuu
008 250605s2022 xx obm 000 0 eng d
020 $a 9798837525506
035 $a (MiAaPQ)AAI29259799
035 $a AAI29259799
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Stein, Aviel J. $3 1472897
245 1 0 $a Applying Natural Language Processing Techniques to Code.
264 0 $c 2022
300 $a 1 online resource (92 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-02, Section: B.
500 $a Advisor: Mancoridis, Spiros.
502 $a Thesis (Ph.D.)--Drexel University, 2022.
504 $a Includes bibliographical references
520 $a Analyzing source code is becoming a helpful method as the amount of code and the number of coders increases. Developing software is a mentally strenuous activity because it involves understanding and formalizing solutions to complex problems. As solutions are adapted and the problem themselves change, the code changes with it. Traditionally, source code analysis (SCA) uses methods and tools that rely on the rigid structure of code to work, and while useful, are not always able to adapt to new information and code. By comparison, the natural language processing (NLP) field leverages naturally occurring patterns within natural language text to help people understand and interpret text robustly on a large scale. This works shows that methods from NLP can be applied to code to extract information automatically in broad and more adaptable ways. We show several examples of how techniques developed for NLP can be successfully applied to software to create source code tools that can help developers improve source code.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Information science. $3 561178
650 4 $a Information technology. $3 559429
650 4 $a Computer engineering. $3 569006
650 4 $a Computer science. $3 573171
653 $a Artificial intelligence
653 $a Computer science
653 $a Deep learning
653 $a Natural language processing
653 $a Source code analysis
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0489
690 $a 0464
690 $a 0723
690 $a 0800
710 2 $a Drexel University. $b Computer Science (College of Computing and Informatics). $3 1195632
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 84-02B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29259799 $z click for full text (PQDT)