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Ning Geng

dblp:209/3323 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2024
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software testing · 75% Concurrent programming · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Concurrent programming
concurrency bugs
0.812024
An Interleaving Guided Metamorphic Testing Approach for Concurrent Programs · ACM Trans. Softw. Eng. Methodol. 2024
Software testing
concurrency testing
0.812024
An Interleaving Guided Metamorphic Testing Approach for Concurrent Programs · ACM Trans. Softw. Eng. Methodol. 2024
Software testing
metamorphic testing
0.812024
An Interleaving Guided Metamorphic Testing Approach for Concurrent Programs · ACM Trans. Softw. Eng. Methodol. 2024
Software testing › test oracle
test oracle problem
0.812024
An Interleaving Guided Metamorphic Testing Approach for Concurrent Programs · ACM Trans. Softw. Eng. Methodol. 2024

Methods — techniques the papers use, named apart from their topics

metamorphic relations · 0.8interleaving-guided testing · 0.8
YearPublicationVenuePosition
2024 CEUS: Comment Emotion and User Stance Fusion Network for Fake News Detection
Ning Geng, Zhenhua Tan, Tao Zhang 0166, Danke Wu
NLPCC (4)1
2024 Domain- and category-style clustering for general fake news detection via contrastive learning
Danke Wu, Zhenhua Tan, Taotao Jiang, Ning Geng
Inf. Process. Manag.5
2024 An Interleaving Guided Metamorphic Testing Approach for Concurrent Programs
abstract
Concurrent programs are normally composed of multiple concurrent threads sharing memory space. These threads are often interleaved, which may lead to some non-determinism in execution results, even for the same program input. This poses huge challenges to the testing of concurrent programs, especially on the test result verification—that is, the prevalent existence of the oracle problem. In this article, we investigate the application of metamorphic testing (MT), a mainstream technique to address the oracle problem, into the testing of concurrent programs. Based on the unique features of interleaved executions in concurrent programming, we propose an extended notion of metamorphic relations, the core part of MT, which are particularly designed for the testing of concurrent programs. A comprehensive testing approach, namely ConMT , is thus developed and a tool is built to automate its implementation on concurrent programs written in Java. Empirical studies have been conducted to evaluate the performance of ConMT, and the experimental results show that in addition to addressing the oracle problem, ConMT outperforms the baseline traditional testing techniques with respect to a higher degree of automation, better bug detection capability, and shorter testing time. It is clear that ConMT can significantly improve the cost-effectiveness for the testing of concurrent programs and thus advances the state of the art in the field. The study also brings novelty into MT, hence promoting the fundamental research of software testing.
Chang-Ai Sun, Hepeng Dai, Ning Geng, Huai Liu, Tsong Yueh Chen, Peng Wu 0002, Yan Cai 0001, Jinqiu Wang
ACM Trans. Softw. Eng. Methodol.3