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Predicting software defects with causality tests
2014
Journal of Systems and Software
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., Predicting software defects with causality tests. J. Syst. ...
Software (2014), http://dx. a b s t r a c t In this paper, we propose a defect prediction approach centered on more robust evidences towards causality between source code metrics (as predictors) and the ...
., Predicting software defects with causality tests. J. Syst. ...
doi:10.1016/j.jss.2014.01.033
fatcat:tbw3nq7ylrhgriqupimmrnmiai
Prediction of Software Defects in SDLC using BN
2014
International Journal of Computer Applications
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It can be combined with other defect prediction models to predict the number of residual defects of different categories. ...
The model predicts the defects likely to be left in software after testing. The model uses the results of statistical analysis on the Previous software projects. ...
This idea allows a BN for software defect prediction to be tailored to different software development environments. ...
doi:10.5120/17358-7885
fatcat:g3q2at4a4fawpjq5zvymi3mmje
Project Data Incorporating Qualitative Factors for Improved Software Defect Prediction
2007
Third International Workshop on Predictor Models in Software Engineering (PROMISE'07: ICSE Workshops 2007)
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To make accurate predictions of attributes like defects found in complex software projects we need a rich set of process factors. ...
The dataset will be of interest to other researchers evaluating models with similar aims. We make both the dataset and causal model available for research use. ...
Specifically the model predicts, with remarkable accuracy, the number of software defects that will be found in independent testing. ...
doi:10.1109/promise.2007.11
fatcat:va2klwixf5danpdnmbfaae5klu
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
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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. ...
Other methods of software defect predictions require data from the development/testing phase. ...
doi:10.5220/0005099203770382
dblp:conf/icsoft/RanaSHN14
fatcat:axvjeqcdeng5xpzijaphzrib2y
Uncovering Causal Relationships between Software Metrics and Bugs
2012
2012 16th European Conference on Software Maintenance and Reengineering
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Bug prediction is an important challenge for software engineering research. It consist in looking for possible early indicators of the presence of bugs in a software. ...
As its name suggests, Granger Test is a better indication of causality between two variables. ...
We thank Marco D'Ambros for making the dataset with the historical values of the OO metrics publicly available. We also thank Mauro Ferreira for the help with the Granger Test. ...
doi:10.1109/csmr.2012.31
dblp:conf/csmr/CoutoSVBA12
fatcat:mjgqw3ssfnczdo5hnluqb4z4y4
A Bayesian Network Approach to Estimating Software Reliability of RSG-GAS Reactor Protection System
2019
Atom Indonesia
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A Bayesian network (BN) is applied in this research and used to predict the software defect in the operation which represents the software reliability. ...
The improvement of software defect concentration range on the posterior distribution compared with the prior's is also identified. ...
The Bayesian causal network of RPS software consists of eight nodes with the causal diagram presented in Fig. 4. Fig. 4 . ...
doi:10.17146/aij.2019.775
fatcat:w5ix4nnsdjczpgo6uaansdwvpe
Predicting software defects in varying development lifecycles using Bayesian nets
2007
Information and Software Technology
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An important decision in software projects is when to stop testing. ...
For projects within the range of the models, defect predictions are very accurate. This approach enables decision-makers to reason in a way that is not possible with regression-based models. ...
These data were entered into the model to predict the number of defects found in testing. These predictions were then compared with the actual number of defects found in all testing phases. ...
doi:10.1016/j.infsof.2006.09.001
fatcat:dtk2h2fpgjcrlp6wzbsiaqb354
On the effectiveness of early life cycle defect prediction with Bayesian Nets
2008
Empirical Software Engineering
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This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. ...
The approach supports (1) and (2) , does not require (3), yet still makes accurate defect predictions (an R 2 of 0.93 between predicted and actual defects). ...
The Need for Causal Models There have been many non-causal models for software defect prediction and some of these have achieved very good accuracy with few input variables and no qualitative factors. ...
doi:10.1007/s10664-008-9072-x
fatcat:5ijlqsvvx5cntam7xriy7xbge4
Software metrics
2000
Proceedings of the conference on The future of Software engineering - ICSE '00
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Traditional metrics approaches, often driven by regression-based models for cost estimation and defects prediction, provide little support for managers wishing to use measurement to analyse and minimise ...
Yet traditional metrics approaches, often driven by regression-based models for cost estimation and defects prediction, provide little support for managers wishing to use measurement to analyse and minimise ...
The amount of testing is therefore a very simple explanatory factor that must be incorporated into any predictive model of defects. ...
doi:10.1145/336512.336588
dblp:conf/icse/FentonN00
fatcat:qw6a2v6h2ffw7aezrkchnaicte
Temporal Patterns of Software Evolution Defects: A Comparative Analysis of Open Source and Closed Source Projects
2011
Journal of Software Engineering and Applications
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Across all sampled projects, the ARIMA time series modeling technique provides accurate estimates of reported defects during software maintenance, with organizationally dependent parameterization. ...
In contrast to causal models that require extraction of source-code level metrics, this approach is based on readily available defect report data and is less computation intensive. ...
Such causal predictive models of defects identify the factors that impact software defects, thus serving both predictive and explanatory roles regarding what factors could be controlled to manage future ...
doi:10.4236/jsea.2011.48058
fatcat:wt3qzstx7zf6jkqmk6dnb57e7i
BugMaps-Granger: a tool for visualizing and predicting bugs using Granger causality tests
2014
Journal of Software Engineering Research and Development
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bugs and (b) improving unit tests coverage in classes with more bugs. ...
For this purpose, we relied on the Granger Causality Test to evaluate whether past changes to a given time series of source code metrics can be used to forecast changes in a time series of defects. ...
It is worth mentioning that we previously performed an extensive study to evaluate the application of Granger Causality Test on software defects prediction . ...
doi:10.1186/2195-1721-2-1
fatcat:3hlazyditndjdd6jpdh3in5lai
Using Bayesian networks to predict software defects and reliability
2008
Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability
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This paper reviews the use of Bayesian networks (BNs) in predicting software defects and software reliability. ...
The approach allows analysts to incorporate causal process factors as well as combine qualitative and quantitative measures, hence overcoming some of the wellknown limitations of traditional software metrics ...
A SIMPLE CAUSAL MODEL FOR SOFTWARE DEFECT PREDICTION A BN is a directed graph (such as that shown in Fig. 1 ) together with a set of probability distributions. ...
doi:10.1243/1748006xjrr161
fatcat:4yrbct64lfhlpitnxrebtdkaa4
A Survey of Bayesian Network Models for Decision Making System in Software Engineering
2016
International Journal of Computer Applications
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Bayesian network model is used to predict the defect correction at various levels of the software development. ...
Defect prediction and assessment are the essential steps in large organizations and industries where the software complexity is growing exponentially. ...
SUMMARY OF BAYESIAN
NETWORKS IN SOFTWARE
ENGINEERING
Source
Problems Investigated
[2]
Coupling
[4]
Defects
[5]
Defects
[6]
Effort
[7]
Dynamic testing
[8]
Requirement review
[9] ...
doi:10.5120/ijca2016906330
fatcat:cq45rwqsubaadfwszki26bap6q
A Novel Approach towards Understanding Adoption of Prediction Models in SDLC in IT SME's
2020
Zenodo
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Several software defect forecast datasets, methods and system are published differently and complex, therefore a full view of the current state of defect prediction research is lacking. ...
Recent studies of software failure projection usually generate datasets, methods and frames that allow software engineers to concentrate on defect-prone code creation operation, thereby enhancing software ...
Inside the blessing work, bundle adjustment measurements are utilized for defect Journal of Advancement in Software Engineering and Testing Volume 3 Issue 3 prediction. ...
doi:10.5281/zenodo.4394341
fatcat:elyeu2zfcvca5obncujocuzzcy
Causally Remove Negative Confound Effects of Size Metric for Software Defect Prediction
2022
Applied Sciences
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Software defect prediction technology can effectively detect potential defects in the software system. ...
The size metric has unexpected correlations with other software metrics and introduces biases into prediction results. ...
Software defect prediction is an effective means to discover potential software defects. ...
doi:10.3390/app12031387
fatcat:346574vlhvdnvhxydzm5ttqvqy
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