GDL

Journal from gdlhub / 2019-09-19 11:23:08
Oleh : Oscar Karnalim, King Saud University
Dibuat : 2019-09-19, dengan 1 file

Keyword : Abstract method linearization, Source code plagiarism, Software engineering, Information retrieval
Url : http://www.sciencedirect.com/science/article/pii/S1319157817305384
Sumber pengambilan dokumen : WEB

According to several works, low-level approach is an effective and efficient solution for detecting source code plagiarism. Instead of relying on source code tokens, it compares the executable form of given code; that form only contains semantic-preserving tokens and is resistant to various plagiarism attacks. However, to our knowledge, an issue about statically linearizing abstract method (i.e. replacing each abstract method invocation with its respective invoked method content without considering invocation semantic) has not been handled comprehensively. Such issue, at some extent, will generate inaccurate plagiarism detection result when handling object-oriented source codes. This paper aims to solve such issue locally per plagiarism-suspected pair. It will generate all possible linearization pair alternatives and select the correct one through IR-based similarity. According to our evaluation regarding the reversed number of mismatched token, the number of false positive, and the number of process, proposed technique is more effective and efficient when compared to state-of-the-art and combinatoric technique. In addition, it is also observed that each IR mechanism used in proposed technique has its own exclusive benefit for selecting the correct linearized forms.

Beri Komentar ?#(0) | Bookmark

Properti	Nilai Properti
ID Publisher	gdlhub
Organisasi	King Saud University
Nama Kontak	Herti Yani, S.Kom
Alamat	Jln. Jenderal Sudirman
Kota	Jambi
Daerah	Jambi
Negara	Indonesia
Telepon	0741-35095
Fax	0741-35093
E-mail Administrator	elibrarystikom@gmail.com
E-mail CKO	elibrarystikom@gmail.com