30,020 Hits in 5.6 sec

Predicting software defects with causality tests

Cesar Couto, Pedro Pires, Marco Tulio Valente, Roberto S. Bigonha, Nicolas Anquetil
2014 Journal of Systems and Software  
., 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

Jawahar SambhajiGawade, Dinesh Bhagwan Hanchate
2014 International Journal of Computer Applications  
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

N. Fenton, M. Neil, W. Marsh, P. Hearty, L. Radlinski, P. Krause
2007 Third International Workshop on Predictor Models in Software Engineering (PROMISE'07: ICSE Workshops 2007)  
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

Rakesh Rana, Miroslaw Staron, Jörgen Hansson, Martin Nilsson
2014 Proceedings of the 9th International Conference on Software Engineering and Applications  
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

Cesar Couto, Christofer Silva, Marco Tulio Valente, Roberto Bigonha, Nicolas Anquetil
2012 2012 16th European Conference on Software Maintenance and Reengineering  
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

S. Santoso, S. Bakhri, J. Situmorang
2019 Atom Indonesia  
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

Norman Fenton, Martin Neil, William Marsh, Peter Hearty, David Marquez, Paul Krause, Rajat Mishra
2007 Information and Software Technology  
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

Norman Fenton, Martin Neil, William Marsh, Peter Hearty, Łukasz Radliński, Paul Krause
2008 Empirical Software Engineering  
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

Norman E. Fenton, Martin Neil
2000 Proceedings of the conference on The future of Software engineering - ICSE '00  
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

Uzma Raja, Joanne Elaine Hale, David Peter Hale
2011 Journal of Software Engineering and Applications  
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

Cesar Couto, Marco Valente, Pedro Pires, Andre Hora, Nicolas Anquetil, Roberto S Bigonha
2014 Journal of Software Engineering Research and Development  
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

N Fenton, M Neil, D Marquez
2008 Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability  
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

Nageswarao M., N. Geethanjali
2016 International Journal of Computer Applications  
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

Ashalatha HS, Prashanth Kumar C P, Nishanth Selvam P, Lavanya A, Nagaveni R, Dr Jayalakshmi, Dr Geetha N
2020 Zenodo  
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

Chenlong Li, Yuyu Yuan, Jincui Yang
2022 Applied Sciences  
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
« Previous Showing results 1 — 15 out of 30,020 results