# Structure, Dynamics, and Applications of Complex Networks in Software Engineering

Authors: Weifeng Pan; Hua Ming; Chunlai Chai
Journal: Mathematical Problems in Engineering
 (2021)

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## Body

## 1. Object-Oriented Software Systems

Five papers focus on the research topics in traditional object-oriented software systems, i.e., software metrics, bug report classification, software defect prediction, and bug triage. Li et al. [3] reviewed the interdisciplinary research work between the fields of complex networks and software engineering. These papers are published in the last seven years (2013 to 2019) and mainly focus on three different research directions, i.e., modeling, analysis, and applications of software networks. Gu et al. [4] analyzed the coupling between classes at different levels and used a set of bipartite software networks to represent them. Finally, they proposed metrics to characterize the coupling between classes. Guo et al. [5] proposed a novel approach to solve the bug report classification problem, which combines several imbalanced learning strategies and multiclass classification methods together. Shi et al. [6] proposed a novel software defect prediction model, which leverages a convolutional neural network to learn semantic features from the source code and applies network embedding to learn structural features from software networks at the class level. Ge et al. [7] proposed an improved bug triage approach for newly reported bugs, which removes the low-quality bug reports and considers the influence of the engagement of developers on their final ranking.


## 2. Service-Oriented Software Systems

Five papers focus on the research topics in service-oriented software systems, i.e., service clustering, service recommendation, service discovery, service selection, and service quality measurement. Zhou and Wang [8] proposed an approach to organize API services into different clusters. Their approach applies structural metrics built from service networks where APIs and Mashups are nodes, and their couplings are edges. Xiong et al. [9] applied NLP and graph embedding techniques to recommend APIs for Mashup developers. They extracted structural semantics from a two-mode graph of Mashups, APIs, and their relations. Sun et al. [10] proposed an improved web service discovery approach, which integrates labels of web services using a neural topic model as external semantics for these web services. Jiang et al. [11] proposed a novel API selection approach for Mashup development. Their approach extracted similarities from the profile of APIs and Mashups. Yang and Wang [12] proposed a hierarchical aggregation model to accurately aggregate the ratings of services.


## 3. Others

This SI also contains three papers which are not related to the topic of this SI, i.e., [13, 14], and [15]. These papers are handled by the editors from the editorial board of Mathematical Problems in Engineering.



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*Source: 6734248-2021-02-16.xml*