Modeling open source software bugs with complex networks

Author(s):  
Cheng Nie ◽  
Daniel Zeng ◽  
Xiaolong Zheng ◽  
Fei-Yue Wang ◽  
Huimin Zhao
2008 ◽  
Vol 387 (24) ◽  
pp. 6190-6200 ◽  
Author(s):  
Xiaolong Zheng ◽  
Daniel Zeng ◽  
Huiqian Li ◽  
Feiyue Wang

2019 ◽  
Vol 1 (1) ◽  
pp. 29-36
Author(s):  
Phuc Minh Nhan ◽  
Thien Hoang Duy Nguyen

For open source software such as Firefox, Eclipse, Subversion,. . . they usually have a system for bug management that sent by users. These bug reports help the system identify various software bugs which makes software maintenance better. However, a situation occurs that there are many error reports sent to  the processing repository that these bug reports were previously reported by different users, this is called duplicate bug reports. In this paper, we introduce a multi-feature model combined with weighted improvements from CFC (ClassFeature-Centroid) to detect duplicate bug reportsautomatically. We have experimented on three projects of Mozilla, Eclipse and OpenOffice. The results show that our method can improve 8-12% better as compared to the compared methods.


2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Aihua Gu ◽  
Lu Li ◽  
Shujun Li ◽  
Qifeng Xun ◽  
Jian Dong ◽  
...  

Context. Coupling between classes is an important metric for software complexity in software systems. Objective. In order to overcome the shortcomings of the existing coupling methods and fully investigate the weighted coupling of classes in different cases in large-scale software systems, this study analyzed the relationship between classes at package level, class level, and method level. Method. The software system is considered as a set of special bipartite graphs in complex networks, and an effective method for coupling measurement is proposed as well. Furthermore, this method is theoretically proved to satisfy the mathematical properties of coupling measurement, leading to overcome the disadvantages of the majority of existing methods. In addition, it was revealed that the proposed method was efficient according to the analyses of existing methods for coupling measurement. Eventually, an algorithm was designed and a program was developed to calculate coupling between classes in three open-source software systems. Results. The results indicated the scale-free characteristic of complex networks in the statistical data. Additionally, the calculated power-law value was used as a metric for coupling measurement, so as to calculate coupling of the three open-source software. It indicated that coupling degrees of the open-source software systems contained a certain impact on evaluation of software complexity. Conclusions. It indicated that coupling degrees of the open-source software systems contained a certain impact on evaluation of software complexity. Moreover, statistical characteristics of some complex networks provided a reliable reference for further in-depth study of coupling. The empirical evidence showed that within a certain range, reducing the coupling was helpful to attenuate the complexity of the software, while excessively blindly pursuit of low coupling increases the complexity of software systems.


2017 ◽  
Author(s):  
Selim Kalaycı ◽  
Zeynep H. Gümüş

ABSTRACTBiological networks are becoming increasingly large and complex, pushing the limits of existing 2D tools. iCAVE is an open source software tool for interactive visual explorations of large and complex networks in 3D, stereoscopic 3D or immersive 3D. It introduces new 3D network layout algorithms and 3D-extensions of popular 2D network layout, clustering and edge bundling algorithms to assists researchers in understanding the underlying patterns in large, multi-layered, clustered or complex networks. This protocol aims to guide new users on the basic functions of iCAVE for loading data, laying out networks (single or multi-layered), bundling edges, clustering networks, visualizing clusters, visualizing data attributes and saving output images or videos. It also provides examples on visualizing networks constrained in physical 3D space (e.g. proteins; neurons; brain). It is accompanied with a new version of iCAVE with an enhanced user interface and highlights new features useful for existing users.Significance StatementNetwork representations assist in systems-level data exploration in many research fields, providing valuable insights. However, with the recent advances in experimental technologies, biological networks are becoming increasingly large and complex, necessitating new data visualization solutions. We have recently developed iCAVE (Liluashvili et al., 2017), an open?source software platform that enables 3D (optionally stereoscopic and or immersive) visualizations of complex, dense or multi?layered biological networks. Users can select from several new 3D network layout and clustering algorithms, bundle network edges and customize network attributes to reveal hidden structures within them. This protocol guides new users on loading, navigating, customizing and saving networks in iCAVE and is accompanied by an updated version of the software.


Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 273 ◽  
Author(s):  
Aloisio Cairo ◽  
Glauco Carneiro ◽  
Miguel Monteiro

Context: Code smells are associated to poor design and programming style, which often degrades code quality and hampers code comprehensibility and maintainability. Goal: identify published studies that provide evidence of the influence of code smells on the occurrence of software bugs. Method: We conducted a Systematic Literature Review (SLR) to reach the stated goal. Results: The SLR selected studies from July 2007 to September 2017, which analyzed the source code of open source software projects and several code smells. Based on evidence of 16 studies covered in this SLR, we conclude that 24 code smells are more influential in the occurrence of bugs relative to the remaining smells analyzed. In contrast, three studies reported that at least 6 code smells are less influential in such occurrences. Evidence from the selected studies also point out tools, techniques, and procedures that should be applied to analyze the influence of the smells. Conclusions: To the best of our knowledge, this is the first SLR to target this goal. This study provides an up-to-date and structured understanding of the influence of code smells on the occurrence of software bugs based on findings systematically collected from a list of relevant references in the latest decade.


Author(s):  
Passakorn PHANNACHITTA ◽  
Akinori IHARA ◽  
Pijak JIRAPIWONG ◽  
Masao OHIRA ◽  
Ken-ichi MATSUMOTO

Sign in / Sign up

Export Citation Format

Share Document