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Predicting contact-without-connection defects on printed circuit boards employing ball grid array package types: a data analytics case study in the smart manufacturing environment

Phillip M. LaCasse, Wilkistar Otieno, Francisco P. Maturana
2020 SN Applied Sciences  
Models trained on the reduced feature sets provide encouraging initial results, with precision, recall, and f1 score metrics exceeding 0.82, 0.50, and 0.62 respectively for each of two datasets analyzed  ...  Two modeling approaches are explored: one approach to analyze individual solder paste deposits and the other approach to holistically analyze all solder paste deposits on a single PCB location.  ...  Additionally, FM was the interface between the Compliance with ethical standards Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.  ... 
doi:10.1007/s42452-019-1924-z fatcat:af6ksirg7rdyhggqhyckvq634q

Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review

Alia Nabil Mahmoud, Vítor Santos
2021 International Journal of Advanced Computer Science and Applications  
Finally, the accuracy metric and the error rate are among the most important metrics used in comparisons between the efficiency of statistical and intelligent models.  ...  The early revelation of defects in software projects is also tried to avoid failure of those projects, save costs, team effort, and time.  ...  The first part shows the relationships between common terms in intelligence, statistical techniques, and performance metrics used in the previous study.  ... 
doi:10.14569/ijacsa.2021.0121128 fatcat:4q3f7v2uwbgozmrzbwjnp4snja

Software testing optimization by advanced quantitative defect management

Lazic Ljubomir
2010 Computer Science and Information Systems  
Further, we explained how can Quantitative Defect Management Model be enhanced to be practically useful for determining which activities need to be addressed to improve the degree of early and cost-effective  ...  Savings model is offered in this paper.  ...  new test sequence determined by Simulated Defect Removal Cost Savings model.  ... 
doi:10.2298/csis090923008l fatcat:7dpg5itydvf75etpa2vzfvagna

Benchmarking cross-project defect prediction approaches with costs metrics [article]

Steffen Herbold
2018 arXiv   pre-print
In recent years, many researchers focused on the problem of Cross-Project Defect Prediction (CPDP), i.e., the creation of prediction models based on training data from other projects.  ...  However, only few of the published papers evaluate the cost efficiency of predictions, i.e., if they save costs if they are used to guide quality assurance efforts.  ...  ACKNOWLEDGMENTS The authors would like to thank GWDG for the access to the scientific compute cluster used for the training and evaluation of thousands of defect prediction models.  ... 
arXiv:1801.04107v1 fatcat:7e74bef3wjditgc6zyoddxvheu

Clustering static analysis defect reports to reduce maintenance costs

Zachary P. Fry, Westley
2013 2013 20th Working Conference on Reverse Engineering (WCRE)  
Many of these defect reports are conceptually similar, but addressing each report separately costs developer effort and increases the maintenance burden.  ...  We propose to automatically cluster machine-generated defect reports so that similar bugs can be triaged and potentially fixed in aggregate.  ...  ACKNOWLEDGMENTS The authors are sincerely indebted to Andy Chou of Coverity for initial ideas, guidance, and technical support.  ... 
doi:10.1109/wcre.2013.6671303 dblp:conf/wcre/FryW13 fatcat:rzccesx5kbcexmrk7eiqsnyiyy

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction

P. Kumudha, R. Venkatesan
2016 The Scientific World Journal  
Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the  ...  Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities  ...  Metrics Employed for the Prediction Model Metrics play a major role in developing the predictive model and analyzing the performance of the proposed predictors.  ... 
doi:10.1155/2016/2401496 pmid:27738649 pmcid:PMC5050670 fatcat:zqjwfp5qmvfcnfzrrp6qswcosi

Perceptions, Expectations, and Challenges in Defect Prediction

Zhiyuan Wan, Xin Xia, Ahmed E. Hassan, David Lo, Jianwei Yin, Xiaohu Yang
2018 IEEE Transactions on Software Engineering  
evidence regarding defect density distribution and the relationship between file size and defectiveness. 3) 7.2% of the respondents reveal an inconsistency between their behavior and perception regarding  ...  Defect prediction has been an active research area for over four decades. Despite numerous studies on defect prediction, the potential value of defect prediction in practice remains unclear.  ...  ACKNOWLEDGMENTS The authors would like to thank all survey participants for responding our survey.  ... 
doi:10.1109/tse.2018.2877678 fatcat:da5ehjqssjbjpn2jkktfi334za

A Survey of Automatic Software Vulnerability Detection, Program Repair, and Defect Prediction Techniques

Zhidong Shen, Si Chen, Luigi Coppolino
2020 Security and Communication Networks  
vulnerability detection, automated program repair, and automated defect prediction.  ...  The development of deep learning technology has brought new opportunities for the study of potential security issues in software, and researchers have successively proposed many automation methods.  ...  retains the potential relationships of opcodes, operands, and registers. is article explores the impact of different convolution kernel sizes and the number of hidden layers on model performance; Text-CNN  ... 
doi:10.1155/2020/8858010 fatcat:obeiw4p7afan5m24ydmdkmyhbm

Utilizing verification and validation certificates to estimate software defect density

Mark Sherriff
2005 Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering - ESEC/FSE-13  
Our research objective is to build a parametric model which utilizes a persistent record of the validation and verification (V&V) practices used with a program to estimate the defect density of that program  ...  The persistent record of the V&V practices are recorded as certificates which are automatically recorded and maintained with the code.  ...  Further, the Constructive Quality Model (COQUALMO) added defect introduction and defect removal parameters to the COCOMO to help predict potential defect density in a system.  ... 
doi:10.1145/1081706.1081768 dblp:conf/sigsoft/Sherriff05 fatcat:yunrmmtwsrbojovgmvi2y3qwmy

Utilizing verification and validation certificates to estimate software defect density

Mark Sherriff
2005 Software engineering notes  
Our research objective is to build a parametric model which utilizes a persistent record of the validation and verification (V&V) practices used with a program to estimate the defect density of that program  ...  The persistent record of the V&V practices are recorded as certificates which are automatically recorded and maintained with the code.  ...  Further, the Constructive Quality Model (COQUALMO) added defect introduction and defect removal parameters to the COCOMO to help predict potential defect density in a system.  ... 
doi:10.1145/1095430.1081768 fatcat:2cv4mqhmizfg3a7sxfsmu7ypdq

Problems with SZZ and Features: An empirical study of the state of practice of defect prediction data collection [article]

Steffen Herbold, Alexander Trautsch, Fabian Trautsch, Benjamin Ledel
2021 arXiv   pre-print
We also explored the impact of the relatively small set of features that are available in most defect prediction data sets, as there are multiple publications that indicate that, e.g., churn related features  ...  Context: The SZZ algorithm is the de facto standard for labeling bug fixing commits and finding inducing changes for defect prediction data.  ...  We also want to thank the GWDG for the support in using their high performance computing infrastructure, that enabled the collection of the large amounts of software metric data.  ... 
arXiv:1911.08938v3 fatcat:xrj2fi7o6jbdfbym2jdflgeex4

EVOLUTION OF SOCIAL DEVELOPER NETWORK IN OSS: SURVEY

Anil Kumar .
2014 International Journal of Research in Engineering and Technology  
Social Developer Networks are built of complex hierarchical social network which forms relationship information between software entities.  ...  Aim is to present brief survey on the analysis, method, algorithm used in developer social network and techniques and technologies available to analyze performance of the developers associated network.  ...  Nicolas Lopez [5] explored topic-wise model can assist understanding evolution of software system. He studied evolution of topics taking developers relation in account.  ... 
doi:10.15623/ijret.2014.0304074 fatcat:lw5e5tcf3rb6tdc37qoa6sla4y

Effort and Cost in Software Engineering

Hennie Huijgens, Arie van Deursen, Leandro L. Minku, Chris Lokan
2017 Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering - EASE'17  
Objectives: We determine similarities and differences between size, effort, cost, duration, and number of defects of software projects.  ...  Results: We demonstrate a (log)-linear relation between cost on the one hand, and size, duration and number of defects on the other. This justifies conducting linear regression for cost.  ...  ACKNOWLEDGMENTS Our thanks to Tableau for allowing us to use their BI solution to build the EBSPM-tool and ISBSG for allowing us to use their repository for research purposes.  ... 
doi:10.1145/3084226.3084249 dblp:conf/ease/HuijgensDML17 fatcat:tqadwdy4xrdbpp7a4kitoh3s5a

Predictive Models in Software Engineering: Challenges and Opportunities [article]

Yanming Yang, Xin Xia, David Lo, Tingting Bi, John Grundy, Xiaohu Yang
2020 arXiv   pre-print
Predictive models are one of the most important techniques that are widely applied in many areas of software engineering.  ...  We describe the key models and approaches used, classify the different models, summarize the range of key application areas, and analyze research results.  ...  Features, metrics or attributes are crucial for the building of a well-performed defect predictive model.  ... 
arXiv:2008.03656v1 fatcat:fe7ylphujfbobeo3g5yevniiei

Comparative Analysis of Selected Heterogeneous Classifiers for Software Defects Prediction Using Filter-Based Feature Selection Methods

Abimbola G Akintola, Abdullateef Balogun, Fatimah B Lafenwa-Balogun, Hameed A Mojeed
2018 FUOYE Journal of Engineering and Technology  
It can be concluded that feature selection methods are capable of improving the performance of learning algorithms in software defects prediction.  ...  Classification techniques is a popular approach to predict software defects and it involves categorizing modules, which is represented by a set of metrics or code attributes into fault prone (FP) and non-fault  ...  Okutan and Yildiz (2012) , proposed a novel method using Bayesian networks to explore the relationships among software metrics and defect proneness.  ... 
doi:10.46792/fuoyejet.v3i1.178 fatcat:m4cjd63o4jhtjhsbhxd57b5bge
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