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Knowledge Discovery for Software Eng...

Kirnapci, Dilara,

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Knowledge Discovery for Software Engineering Using Sequential Pattern Mining = = Yazilim Muhendisligi Icin Sirali Oruntu Madenciligi ile Bilgi Kesfi /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Knowledge Discovery for Software Engineering Using Sequential Pattern Mining =/ Dilara Kirnapci.
Reminder of title:	Yazilim Muhendisligi Icin Sirali Oruntu Madenciligi ile Bilgi Kesfi /
Author:	Kirnapci, Dilara,
Description:	1 electronic resource (55 pages)
Notes:	Source: Masters Abstracts International, Volume: 85-08.
Contained By:	Masters Abstracts International85-08.
Subject:	Use statistics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30834079
ISBN:	9798381578157

Knowledge Discovery for Software Engineering Using Sequential Pattern Mining = = Yazilim Muhendisligi Icin Sirali Oruntu Madenciligi ile Bilgi Kesfi /
Kirnapci, Dilara,

Knowledge Discovery for Software Engineering Using Sequential Pattern Mining =Yazilim Muhendisligi Icin Sirali Oruntu Madenciligi ile Bilgi Kesfi /Dilara Kirnapci. - 1 electronic resource (55 pages)

Source: Masters Abstracts International, Volume: 85-08.

Discovering sequential patterns in source codes is an important issue in software engineering since it can provide useful knowledge to help in a variety of tasks such as code completion, code refactoring, developer profiling, and code complexity measurement. This paper proposes a new framework, called Source Code Miner(SCodeMiner), which discovers frequent sequential rules within a software project. The proposed framework firstly transforms a Java code into a sequence data and then applies a sequential pattern mining (SPM) algorithm. This study is also original in that it compares four SPM algorithms in terms of computational time, including sequential pattern discovery using equivalence classes (SPADE), prefix-projected sequential pattern mining (PrefixSpan), bi-directional extension (BIDE+), and last position induction (LAPIN). The experiments that carried out on an open-source software project showed that the proposed SCodeMiner framework is an effective mining tool in identifying coding patterns.

English

ISBN: 9798381578157Subjects--Topical Terms:

3562063
Use statistics.

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