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Xiao-Ning Shen

dblp:157/5009 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2018
—ORCID · none

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

Databases, data management, data science and information retrieval · 2 · 2 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author

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
Empirical software engineering · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering
software project management
0.212016
Dynamic Software Project Scheduling through a Proactive-Rescheduling Method · IEEE Trans. Software Eng. 2016
Empirical software engineering › software project management
software project scheduling
0.212016
Dynamic Software Project Scheduling through a Proactive-Rescheduling Method · IEEE Trans. Software Eng. 2016

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

proactive rescheduling · 0.2multi-objective evolutionary algorithm · 0.2
YearPublicationVenuePosition
2018 A Q-learning-based memetic algorithm for multi-objective dynamic software project scheduling
Xiao-Ning Shen, Leandro L. Minku, Naresh Marturi, Yinan Guo 0001
Inf. Sci.1
2017 Robustness measures and robust scheduling for multi-objective stochastic flexible job shop scheduling problems
Xiao-Ning Shen, Jing-Zhi Fu
Soft Comput.1
2016 Dynamic Software Project Scheduling through a Proactive-Rescheduling Method
abstract
Software project scheduling in dynamic and uncertain environments is of significant importance to real-world software development. Yet most studies schedule software projects by considering static and deterministic scenarios only, which may cause performance deterioration or even infeasibility when facing disruptions. In order to capture more dynamic features of software project scheduling than the previous work, this paper formulates the project scheduling problem by considering uncertainties and dynamic events that often occur during software project development, and constructs a mathematical model for the resulting multi-objective dynamic project scheduling problem (MODPSP), where the four objectives of project cost, duration, robustness and stability are considered simultaneously under a variety of practical constraints. In order to solve MODPSP appropriately, a multi-objective evolutionary algorithm based proactive-rescheduling method is proposed, which generates a robust schedule predictively and adapts the previous schedule in response to critical dynamic events during the project execution. Extensive experimental results on 21 problem instances, including three instances derived from real-world software projects, show that our novel method is very effective. By introducing the robustness and stability objectives, and incorporating the dynamic optimization strategies specifically designed for MODPSP, our proactive-rescheduling method achieves a very good overall performance in a dynamic environment.
Xiao-Ning Shen, Leandro L. Minku, Rami Bahsoon, Xin Yao 0001
IEEE Trans. Software Eng.1
2015 Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems
Xiao-Ning Shen, Xin Yao 0001
Inf. Sci.1