Open Access

ARTICLE

A Data-Semantic-Conflict-Based Multi-Truth Discovery Algorithm for a Programming Site

Haitao Xu¹, Haiwang Zhang¹, Qianqian Li¹, Tao Qin^2,*, Zhen Zhang³

1 University of Science and Technology Beijing, Beijing, 100083, China
2 National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, 100000, China
3 Audio Analytic, 2 Quayside, Cambridge, UK

* Corresponding Author: Tao Qin. Email:

Computers, Materials & Continua 2021, 68(2), 2681-2691. https://doi.org/10.32604/cmc.2021.016188

Received 26 December 2020; Accepted 17 February 2021; Issue published 13 April 2021

Abstract

With the extensive application of software collaborative development technology, the processing of code data generated in programming scenes has become a research hotspot. In the collaborative programming process, different users can submit code in a distributed way. The consistency of code grammar can be achieved by syntax constraints. However, when different users work on the same code in semantic development programming practices, the development factors of different users will inevitably lead to the problem of data semantic conflict. In this paper, the characteristics of code segment data in a programming scene are considered. The code sequence can be obtained by disassembling the code segment using lexical analysis technology. Combined with a traditional solution of a data conflict problem, the code sequence can be taken as the declared value object in the data conflict resolution problem. Through the similarity analysis of code sequence objects, the concept of the deviation degree between the declared value object and the truth value object is proposed. A multi-truth discovery algorithm, called the multiple truth discovery algorithm based on deviation (MTDD), is proposed. The basic methods, such as Conflict Resolution on Heterogeneous Data, Voting-K, and MTRuths_Greedy, are compared to verify the performance and precision of the proposed MTDD algorithm.

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Keywords

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