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 David Bowes
 d.h.bowesatherts.ac.uk

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Bibliometrics: publication history
Average citations per article8.83
Citation Count159
Publication count18
Publication years2009-2017
Available for download10
Average downloads per article258.20
Downloads (cumulative)2,582
Downloads (12 Months)968
Downloads (6 Weeks)105
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18 results found Export Results: bibtexendnoteacmrefcsv

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1
May 2017 WETSoM '17: Proceedings of the 8th Workshop on Emerging Trends in Software Metrics
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 15,   Downloads (12 Months): 74,   Downloads (Overall): 74

Full text available: PDFPDF
Background: Test quality is a prerequisite for achieving production system quality. While the concept of quality is multidimensional, most of the effort in testing context has been channelled towards measuring test effectiveness. Objective: While effectiveness of tests is certainly important, we aim to identify a core list of testing principles ...
Keywords: metrics, test quality, unit testing

2
April 2017 Journal of Software: Evolution and Process: Volume 29 Issue 4, April 2017
Publisher: John Wiley & Sons, Inc.
Bibliometrics:
Citation Count: 0

Evolutionary coupling EC is defined as the implicit relationship between 2 or more software artifacts that are frequently changed together. Changing software is widely reported to be defect-prone. In this study, we investigate the effect of EC on the defect proneness of large industrial software systems and explain why the ...
Keywords: legacy software, software defects, industrial software, mining software repositories, evolutionary coupling, measurement

3 published by ACM
September 2016 ESEM '16: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 11,   Downloads (12 Months): 121,   Downloads (Overall): 182

Full text available: PDFPDF
Background: Ensemble techniques have gained attention in various scientific fields. Defect prediction researchers have investigated many state-of-the-art ensemble models and concluded that in many cases these outperform standard single classifier techniques. Almost all previous work using ensemble techniques in defect prediction rely on the majority voting scheme for combining prediction ...
Keywords: Software defect prediction, ensembles of learning machines, software faults, stacking, diversity

4 published by ACM
September 2016 ESEM '16: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 19,   Downloads (12 Months): 182,   Downloads (Overall): 281

Full text available: PDFPDF
Context: Defect prediction research is based on a small number of defect datasets and most are at class not method level. Consequently our knowledge of defects is limited. Identifying defect datasets for prediction is not easy and extracting quality data from identified datasets is even more difficult. Goal: Identify open ...
Keywords: Defect linking, Defects, Data Mining, Defect Prediction, Boa

5 published by ACM
July 2016 ISSTA 2016: Proceedings of the 25th International Symposium on Software Testing and Analysis
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 9,   Downloads (12 Months): 103,   Downloads (Overall): 163

Full text available: PDFPDF
We introduce mutation-aware fault prediction, which leverages additional guidance from metrics constructed in terms of mutants and the test cases that cover and detect them. We report the results of 12 sets of experiments, applying 4 different predictive modelling techniques to 3 large real-world systems (both open and closed source). ...
Keywords: Empirical Study, Mutation Testing, Software Fault Prediction, Software Defect Prediction, Software Metrics

6 published by ACM
June 2016 EASE '16: Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering
Publisher: ACM
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 12,   Downloads (12 Months): 80,   Downloads (Overall): 132

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Background: The NASA datasets have previously been used extensively in studies of software defects. In 2013 Shepperd et al. presented an essential set of rules for removing erroneous data from the NASA datasets making this data more reliable to use. Objective: We have now found additional rules necessary for removing ...
Keywords: software defect prediction, data quality, machine learning

7 published by ACM
October 2015 PROMISE '15: Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 3,   Downloads (12 Months): 36,   Downloads (Overall): 123

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BACKGROUND -- During the last 10 years hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. OBJECTIVE -- We investigate the individual defects ...

8 published by ACM
October 2015 PROMISE '15: Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 6,   Downloads (12 Months): 64,   Downloads (Overall): 196

Full text available: PDFPDF
Software defect prediction performance varies over a large range. Menzies suggested there is a ceiling effect of 80% Recall [8]. Most of the data sets used are highly imbalanced. This paper asks, what is the empirical effect of using different datasets with varying levels of imbalance on predictive performance? We ...
Keywords: Defect Prediction, Machine Learning, Data Imbalance

9 published by ACM
September 2014 ACM Transactions on Software Engineering and Methodology (TOSEM) - Special Issue International Conference on Software Engineering (ICSE 2012) and Regular Papers: Volume 23 Issue 4, August 2014
Publisher: ACM
Bibliometrics:
Citation Count: 12
Downloads (6 Weeks): 12,   Downloads (12 Months): 167,   Downloads (Overall): 762

Full text available: PDFPDF
We investigate the relationship between faults and five of Fowler et al.'s least-studied smells in code: Data Clumps, Switch Statements, Speculative Generality, Message Chains, and Middle Man. We developed a tool to detect these five smells in three open-source systems: Eclipse, ArgoUML, and Apache Commons. We collected fault data from ...
Keywords: defects, Software code smells

10
April 2014 Automated Software Engineering: Volume 21 Issue 2, April 2014
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 3

There are many hundreds of fault prediction models published in the literature. The predictive performance of these models is often reported using a variety of different measures. Most performance measures are not directly comparable. This lack of comparability means that it is often difficult to evaluate the performance of one ...
Keywords: Machine learning, Confusion matrix, Fault

11
December 2012 ICMLA '12: Proceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 02
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

The aim of this paper is to investigate the quality of methodology in software fault prediction studies using machine learning. Over two hundred studies of fault prediction have been published in the last 10 years. There is evidence to suggest that the quality of methodology used in some of these ...
Keywords: machine learning, experimental techniques, methodology, fault prediction, software engineering

12
November 2012 IEEE Transactions on Software Engineering: Volume 38 Issue 6, November 2012
Publisher: IEEE Press
Bibliometrics:
Citation Count: 125

Background: The accurate prediction of where faults are likely to occur in code can help direct test effort, reduce costs, and improve the quality of software. Objective: We investigate how the context of models, the independent variables used, and the modeling techniques applied influence the performance of fault prediction models. ...
Keywords: Predictive models,Context modeling,Software testing,Data models,Systematics,Analytical models,Fault diagnosis,software fault prediction,Systematic literature review

13 published by ACM
September 2012 EAST '12: Proceedings of the 2nd international workshop on Evidential assessment of software technologies
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 17,   Downloads (12 Months): 129,   Downloads (Overall): 552

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Background : Systematic literature reviews are increasingly used in software engineering. Most systematic literature reviews require several hundred papers to be examined and assessed. This is not a trivial task and can be time consuming and error-prone. Aim: We present SLuRp - our open source web enabled database that supports ...
Keywords: systematic literature review tool

14
November 2011 IEEE Software: Volume 28 Issue 6, November 2011
Publisher: IEEE Computer Society Press
Bibliometrics:
Citation Count: 1

A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software ...
Keywords: fault-prediction models

15 published by ACM
May 2011 WETSoM '11: Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 12,   Downloads (Overall): 117

Full text available: PDFPDF
It is important to develop corpuses of data to test out the efficacy of using metrics. Replicated studies are an important contribution to corpuses of metrics data. There are few replicated studies using metrics reported in software engineering. To contribute more data to the body of evidence on the use ...
Keywords: data quality, empirical software engineering, slicing metrics

16
September 2010 SEAA '10: Proceedings of the 2010 36th EUROMICRO Conference on Software Engineering and Advanced Applications
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

In this paper, we investigate the Barcode open-source system (OSS) using one of Weiser’s original slice-based metrics (Tightness) as a basis. In previous work, low numerical values of this slice-based metric were found to indicate fault-free (as opposed to fault-prone) functions. In the same work, we deliberately excluded from our ...
Keywords: OSS, slicing, cohesion, fault

17
June 2010 PROFES'10: Proceedings of the 11th international conference on Product-Focused Software Process Improvement
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 1

Software products can only be improved if we have a good understanding of the faults they typically contain. Code faults are a significant source of software product problems which we currently do not understand sufficiently. Open source change repositories are potentially a rich and valuable source of fault data for ...
Keywords: software, data, prediction, fault

18
August 2009 SEAA '09: Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 3

In this paper, we investigate the Barcode OSS using two of Weiser’s original slice-based metrics (Tightness and Overlap) as a basis, complemented with fault data extracted from multiple versions of the same system. We compared the values of the metrics in functions with at least one reported fault with fault-free ...



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