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Predicting defects using change genealogies

Kim Herzig, Sascha Just, Andreas Rau, Andreas Zeller
2013 2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)  
prediction models not only show better classification accuracies as models based on code complexity, but can also outperform classification models based on code dependency network metrics.  ...  To this end, we group changes into change genealogies, graphs of changes reflecting their mutual dependencies and influences and develop new metrics to capture the spatial and temporal influence of changes  ...  TABLE III STRUCTURAL III HOLES METRICS SIMILAR TO BURT TABLE IV PROJECTS IV USED FOR EXPERIMENTS.  ... 
doi:10.1109/issre.2013.6698911 dblp:conf/issre/HerzigJRZ13 fatcat:vyg7jjib6bdj7dvkweoayuwdci

Predicting Client Satisfaction through (E-Mail) Network Analysis: The Communication Score Card [article]

Dirk Brunberg, Peter A. Gloor, Gianni Giacomelli
2013 arXiv   pre-print
This study seeks to better understand the network characteristics of client support teams by analyzing the teams' e-mail communication networks and comparing it to client organization's satisfaction.  ...  In particular, we found that social network metrics correlate with client satisfaction as measured by Net Promoter Score (NPS).  ...  By continuously tracking changes in network structure and dynamics, service providers might be able to act faster and manage projects more easily.  ... 
arXiv:1308.1164v1 fatcat:jjwrztwhbvetzc4axl3jc5u2ne

Community-Driven Social Influence Analysis and Applications [chapter]

Yang Zhang, Jun Pang
2015 Lecture Notes in Computer Science  
As a next step, we intend to detect users that act as structural hole spanners and analyze their social influence across different communities.  ...  In this PhD project, we aim to study users' social influence at the community level, mainly because users in social networks are naturally organized in communities and communities play fundamental roles  ...  To discover structural hole spanners from the social network, Lou and Tang [9] have proposed two algorithms which are purely based on graph structure.  ... 
doi:10.1007/978-3-319-19890-3_48 fatcat:m27ufbm4p5holbeuw7yl4lflxu

Predicting defects using network analysis on dependency graphs

Thomas Zimmermann, Nachiappan Nagappan
2008 Proceedings of the 13th international conference on Software engineering - ICSE '08  
In this paper, we propose to use network analysis on these dependency graphs. This allows managers to identify central program units that are more likely to face defects.  ...  In our evaluation on Windows Server 2003, we found that the recall for models built from network measures is by 10% points higher than for models built from complexity metrics.  ...  between dependencies and defects.  ... 
doi:10.1145/1368088.1368161 dblp:conf/icse/ZimmermannN08 fatcat:wjsdbofmnve6xgqjv3ryietovm

Standing out in a networked communication context: Toward a network contingency model of public attention

Aimei Yang, Adam J Saffer
2020 New Media & Society  
the network structure of the communication context.  ...  This study takes a strategic network perspective and draws from recent research in network science to propose the network contingency model of public attention.  ...  from acting because of its ties to others), structural hole effectiveness (the effective size of a node's ego network based on redundancy of ties), and structural hole efficiency (the fraction of nodes  ... 
doi:10.1177/1461444820939445 fatcat:ezlotos7gfdtbknwn6k7vuknhq

Innovation networks: the effects of collaboration in the oil and gas industries

Mauro Maia Laruccia, Adonis Pedro Coutinho Barboza
2017 International Journal of Auditing Technology  
collaboration affects patent productivity given network metrics such as centrality, structural holes, and hierarchy.  ...  They are valid and can contribute to management activities, although they cannot predict the productivity of an innovation network.  ...  However, although BP, Shell, Sinopec, and Total are among the seven companies with the greatest revenues, they are insufficient to represent the whole oil and gas industries.  ... 
doi:10.1504/ijaudit.2017.10007797 fatcat:skrnvyjrsfaojor7zxaksbdj6q

Innovation networks: the effects of collaboration in the oil and gas industries

Adonis Pedro Coutinho Barboza, Mauro Maia Laruccia
2017 International Journal of Auditing Technology  
collaboration affects patent productivity given network metrics such as centrality, structural holes, and hierarchy.  ...  They are valid and can contribute to management activities, although they cannot predict the productivity of an innovation network.  ...  However, although BP, Shell, Sinopec, and Total are among the seven companies with the greatest revenues, they are insufficient to represent the whole oil and gas industries.  ... 
doi:10.1504/ijaudit.2017.086747 fatcat:j3uqhfqkabcjvgrlzpfd35q3dy

Probabilistic Community and Role Model for Social Networks

Yu Han, Jie Tang
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
Numerous models have been proposed for modeling social networks to explore their structure or to address application problems, such as community detection and behavior prediction.  ...  In this paper, we propose a unified probabilistic framework, the Community Role Model (CRM), to model a social network.  ...  of structural hole spanner [29] .  ... 
doi:10.1145/2783258.2783274 dblp:conf/kdd/HanT15 fatcat:wvqpsfzmgva35mdydjv424zvhu

Identification of Compromised Nodes in MANETs using Machine Learning Technique

Rodney Sebopelo, Bassey Isong, Naison Gasela
2019 International Journal of Computer Network and Information Security  
To achieve this, we conducted experiments using logistic regression (LR) and a support vector machine (SVM) to choose the best predictive model utilizing the Iris data set.  ...  Mobile ad hoc networks (MANETs) are faced with various security challenges emanating from malicious attacks.  ...  The dependent variable are the values to be predicted. They include the targets (y i ) of MANET data in which class's value depends on the metric (x i ).  ... 
doi:10.5815/ijcnis.2019.01.01 fatcat:ymj2dtkaejdlndxdxjeubjuuky

Downsizing and Structural Holes

ALEX M. SUSSKIND, VERNON D. MILLER, J. DAVID JOHNSON
1998 Communication Research  
Prominence is one of the most frequently used network metrics (Monge & Eisenberg, 1987) .  ...  In addition, the individual relationships of structural hole items and the structural hole index were compared to the dependent variables to assess if the combined index demonstrated greater predictive  ... 
doi:10.1177/009365098025001002 fatcat:qhwhhfpmpjeifdol7jvufi6jni

Deep Neural Network Inverse Design of Integrated Nanophotonic Devices [article]

Mohammad H. Tahersima, Keisuke Kojima, Toshiaki Koike-Akino, Devesh Jha, Bingnan Wang, Chungwei Lin, Kieran Parsons
2018 arXiv   pre-print
Here we use deep learning to predict optical response of artificially engineered nanophotonic devices.  ...  In addition to predicting forward approximation of transmission response for any given topology, this approach allows us to inversely approximate designs for a targeted optical response.  ...  Discussion NNs can be used to take device structure data (shape, depth, and permittivity) to predict the optical response of the nanostructure (forward network).  ... 
arXiv:1809.03555v1 fatcat:mit74oz3y5ajzmplphhqinzzza

A Comparative Study of Target Tracking Approaches in Wireless Sensor Networks

Asmaa Ez-Zaidi, Said Rakrak
2016 Journal of Sensors  
We then analyze them according to several metrics. We also discuss some of the challenges that influence the performance of tracking schemes.  ...  Wireless sensor networks have been the subject of intense research in recent years. Sensor nodes are used in wide range of applications such as security, military, and environmental monitoring.  ...  As shown in Figure 2 , there are six metrics: network structure, prediction-based mechanisms, type of chased object, type of sensor, number of targets, and recovery strategies. 3.1.  ... 
doi:10.1155/2016/3270659 fatcat:g4xz4dizx5eytm74fz5emt4fbq

Deep Neural Network Inverse Design of Integrated Photonic Power Splitters

Mohammad H. Tahersima, Keisuke Kojima, Toshiaki Koike-Akino, Devesh Jha, Bingnan Wang, Chungwei Lin, Kieran Parsons
2019 Scientific Reports  
Here we use deep learning to predict optical response of artificially engineered nanophotonic devices.  ...  It has received some attention in optical community and there has been several recent work on reverse modeling for design of nano-structured optical components using DNN 19-25 , as well as hardware implementation  ...  Discussion NNs can be used to take device structure data (shape, depth, and permittivity) to predict the optical response of the nanostructure (forward network).  ... 
doi:10.1038/s41598-018-37952-2 fatcat:mkzcoip5xzhhjf4mcddcclwmsa

Relating Wikipedia article quality to edit behavior and link structure

Thorsten Ruprechter, Tiago Santos, Denis Helic
2020 Applied Network Science  
Additionally, we build a network of internal Wikipedia hyperlinks between articles. Using this data, we compute parsimonious metrics to quantify editing and linking behavior.  ...  With our network analysis we find evidence indicating that controversial and edit war articles frequently span structural holes in the Wikipedia network.  ...  subgroups due to their occupation of structural holes in the Wikipedia network.  ... 
doi:10.1007/s41109-020-00305-y fatcat:2unnvgtgsbg3fgof6zpdjst54y

Developer social networks in software engineering: construction, analysis, and applications

WeiQiang Zhang, LiMing Nie, He Jiang, ZhenYu Chen, Jia Liu
2014 Science China Information Sciences  
The recorded information can be employed to construct Developer Social Networks (DSNs) for facilitating tasks in software engineering.  ...  During the collaboration, a lot of new information related to software development, including developers' communication and coordination, can be recorded in software repositories.  ...  [77] use a collaboration network derived from bug report repositories of Mozilla Firefox, to predict the risk and vulnerability in organization structures. Amrit et al.  ... 
doi:10.1007/s11432-014-5221-6 fatcat:ulahmalivrbcnhkrrlspogejdq
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