A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Filters
Defect Prediction using Combined Product and Project Metrics - A Case Study from the Open Source "Apache" MyFaces Project Family
2008
Proceedings of the EUROMICRO Conference
Preserved Fulltext
Only few prediction models consider information on the development process (project metrics) that seems relevant to quality improvement of the software product. ...
In this paper, we investigate defect prediction with data from a family of widely used OSS projects based both on product and project metrics as well as on combinations of these metrics. ...
To validate our prediction models we fit the model to historical data of releases, we use the average relative error (ARE) to evaluate forecast accuracy. ...
doi:10.1109/seaa.2008.36
dblp:conf/seaa/WahyudinSWTB08
fatcat:lbuhlkwhpvdzrbkviejjwr2j5y
Software Project Management Using Machine Learning Technique—A Review
2021
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
an alternative way to efficiently reduce the project failure probabilities, and increasing the output ratio for growth, and it also facilitates analysis on software fault prediction based on accuracy. ...
used in machine-learning management and the final classes of the results from the study, contribution of studies in the production, and the promotion of machine-learning project prediction. ...
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app11115183
fatcat:e7cfhrwyunfeld7cpngu4uifl4
Application of Artificial Neural Network for Software Reliability Growth Modeling with Testing Effort
2016
Indian Journal of Science and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The proposed ANN based model provides consistent performance for both exponential and S-shaped growth of mean value functions witnessed in software projects. ...
Background/Objectives: To design a relatively simple Software Reliability Growth Model (SRGM) with testing effort function using Artificial Neural Network approach. ...
In 12 evaluated SRGMs by improving their predictive accuracy using historical projects failure data. Traditional parametric SRGMs have two characteristics in common. ...
doi:10.17485/ijst/2016/v9i29/90093
fatcat:irf34rrhlfb2jfyhame2tctw64
Evaluating long-term predictive power of standard reliability growth models on automotive systems
2013
2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Software Reliability Growth Models (SRGMs) have been long used to assess the reliability of software systems; they are also used for predicting the defect inflow in order to allocate maintenance resources ...
Although a number of models have been proposed and evaluated, much of the assessment of their predictive ability is studied for short term (e.g. last 10% of data). ...
ACKNOWLEDGMENT The research presented here is done under the VISEE project which is funded by Vinnova and Volvo Cars jointly under the FFI programme (VISEE, Project No: DIARIENR: 2011-04438). ...
doi:10.1109/issre.2013.6698922
dblp:conf/issre/RanaSBHNT13
fatcat:2a4cm2jwvndg3iazkqzvp74luq
Software Reliability Modeling using Soft Computing Techniques: Critical Review
2015
International Journal of Information Technology and Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Software reliability models assess the reliability by predicting faults for the software. Reliability is a real world phenomenon with many associated real-time problems. ...
and can be used globally. ...
They found that their models are better prediction models than some other statistical models [16] . Used connectionist models for software reliability prediction. ...
doi:10.5815/ijitcs.2015.07.10
fatcat:ab7t7unlcnhmtm6vad3ymvtlvy
A Study On Software Engineering Defect Prediction
2022
Data Analytics and Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Dependent and independent variable are considered in Software bug prediction. To prevent defect based on software metrics software prediction model are used. ...
M any data mining techniques and dataset repository are available to predict the software defects. Bug prediction technique is an important part in software engineering area for last one decade. ...
Using firm and well known data mining techniques, researchers and specialists have started exploring their precious data in order to manage their projects in an improved and professional manner and produce ...
doi:10.46632/daai/2/1/1
fatcat:25anbqvp3vg4fjeutyfccly5ya
Defect Prediction Leads to High Quality Product
2011
Journal of Software Engineering and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
So, defect prediction is very important in the field of software quality and software reliability. This paper gives you a vivid description about software defect prediction. ...
Defect prediction is relatively a new research area of software quality assurance. A project team always aims to produce a quality product with zero or few defects. ...
the insignificant predictors to form a reliability growth model. ...
doi:10.4236/jsea.2011.411075
fatcat:4myguuo6gngzfczxm6je4snxy4
Software Reliability Modeling using Soft Computing Techniques: Critical Review
2015
Journal of Information Technology & Software Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Further to this, we have also compared soft computing techniques in terms of software reliability modeling capabilities. ...
In this paper, we have provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability. ...
[25] proposed an artificial neural network model to improve the early reliability prediction for current projects/releases by reusing the failure data from past projects/releases. ...
doi:10.4172/2165-7866.1000144
fatcat:mar6yvi7ejenzhwa3bgmwkxheq
Using hybrid algorithm to estimate and predicate based on software reliability model
2019
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
This paper uses five classic sets of software failure data to estimate the GO model parameters and make predictions and performs a variety of comparisons of the algorithm results. ...
The software reliability is mainly obtained through modeling and estimating. The existing software reliability models are nonlinear, and the parameter estimation of these models is difficult. ...
The parameters a and b of the G-O model, their selection will affect the accuracy of the model prediction.
B. ...
doi:10.1109/access.2019.2917828
fatcat:j7cduzjhdngidjx52o472fra2q
Software Reliability Modeling with Test Coverage: Experimentation and Measurement with A Fault-Tolerant Software Project
2007
The 18th IEEE International Symposium on Software Reliability (ISSRE '07)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Traditional software reliability growth models use the execution time during testing for reliability estimation. ...
Although testing time is an important factor in reliability, it is likely that the prediction accuracy of such models can be further improved by adding other parameters which affect the final software ...
Acknowledgement The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CUHK4150/07E). ...
doi:10.1109/issre.2007.17
dblp:conf/issre/CaiL07
fatcat:dvf33ji54bc4rcjb7snrqvm6di
A Distribution-Level Combinational Model to Improve Reliability Prediction Accuracy
2017
International Journal of Performability Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We use mean squared error (MSE) to evaluate the historical predictive validity. The results show that our model is consistently stable and has lower MSE. ...
To evaluate the effectiveness of the proposed model, we use the failure data sets (21 projects) available in public sources. ...
Jinhee uses decision tree to select base models and to decide the weights according to the prediction accuracies of the selected base models [21] . ...
doi:10.23940/ijpe.17.06.p5.832843
fatcat:52dlphtij5clfljta4ydvx4fxe
Predict the number of remaining faults during inspection using actual inspection data, where as Stranded predict which files will contain the most faults in the next release
IJARCCE - Computer and Communication Engineering
2014
IJARCCE
IJARCCE - Computer and Communication Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Software reliability growth models (SRGMs) are also used to estimate the total number of faults to measure software reliability. ...
Zhang and Mockus use data collected from previous projects to estimate the number of faults in a new project. ...
Software reliability growth models (SRGMs) are also used to estimate the total number of faults to measure software reliability. ...
doi:10.17148/ijarcce.2014.31124
fatcat:ev4zoon5trc55erjjtrken27my
Predicting the Popularity of GitHub Repositories
2016
Proceedings of the The 12th International Conference on Predictive Models and Data Analytics in Software Engineering - PROMISE 2016
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2016 pre-print arXiv:1607.04342v1 fatcat:6sbqcod2tvfmzmdl5xxkib3cgm
Furthermore, specific models---generated using data from repositories that share the same growth trends---are recommended for repositories with slow growth and/or for repositories with less stars. ...
These predictions are useful both to repository owners and clients, who usually want to know how their projects are performing in a competitive open source development market. ...
We also found that specific models, i.e., models produced using repositories that share the same growth trend, can reduce the average prediction error and produce reliable predictions using less data. ...
doi:10.1145/2972958.2972966
dblp:conf/promise/BorgesHV16
fatcat:jw4s44bp65dqtgme2xlyj3lani
Real-Time High-Load Infrastructure Transaction Status Output Prediction Using Operational Intelligence and Big Data Technologies
2020
Electronics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
and operations, taking into account the exponential growth of information and the growing trend of Big Data-based projects. ...
The methods used in the study include machine learning models, data preprocessing, missing data imputation, SRE (site reliability engineering) indicators computation, quantitative research, and a qualitative ...
Particular methods include traditional data preprocessing: data ranges of certain features; normalization as a way to improve model accuracy, PCA (principal component analysis) used to select the best ...
doi:10.3390/electronics9040668
fatcat:vwmlmlqkhvejpbdxmdtwqw4rqq
Defect Prediction over Software Life Cycle in Automotive Domain - State of the Art and Road Map for Future
2014
Proceedings of the 9th International Conference on Software Engineering and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Methods of software defect predictions provide useful information for optimal resource allocation and release planning; they also help track and model software and system reliability. ...
In this paper we present an overview of defect prediction methods and their applicability in different software lifecycle phases in the automotive domain. ...
ACKNOWLEDGEMENTS The research presented here is done under the VISEE project which is funded by Vinnova and Volvo Cars jointly under the FFI programme (VISEE, Project No: DIARIENR: 2011-04438). ...
doi:10.5220/0005099203770382
dblp:conf/icsoft/RanaSHN14
fatcat:axvjeqcdeng5xpzijaphzrib2y
« Previous
Showing results 1 — 15 out of 38,435 results