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Semantic ScholarDavid Bowes
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- affiliation: University of Hertfordshire, UK
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2010 – today
- 2019
[j13]Thomas Shippey, David Bowes, Tracy Hall:
Automatically identifying code features for software defect prediction: Using AST N-grams. Information & Software Technology 106: 142-160 (2019)- 2018
- [j12]Zaheed Mahmood, David Bowes, Tracy Hall, Peter C. R. Lane, Jean Petric:
Reproducibility and replicability of software defect prediction studies. Information & Software Technology 99: 148-163 (2018) - [j11]David Bowes, Tracy Hall, Jean Petric:
Software defect prediction: do different classifiers find the same defects? Software Quality Journal 26(2): 525-552 (2018) - [j10]Martin J. Shepperd, Tracy Hall, David Bowes:
Authors' Reply to "Comments on 'Researcher Bias: The Use of Machine Learning in Software Defect Prediction'". IEEE Trans. Software Eng. 44(11): 1129-1131 (2018) - [c26]Thomas Shippey, David Bowes, Steve Counsell, Tracy Hall:
Code Cleaning for Software Defect Prediction: A Cautionary Tale. SEAA 2018: 239-243 - [c25]Giuseppe Destefanis, Marco Ortu, David Bowes, Michele Marchesi, Roberto Tonelli:
On measuring affects of github issues' commenters. SEmotion@ICSE 2018: 14-19 - [c24]Jean Petric, Tracy Hall, David Bowes:
How Effectively Is Defective Code Actually Tested?: An Analysis of JUnit Tests in Seven Open Source Systems. PROMISE 2018: 42-51 - [c23]Marco Ortu, Tracy Hall, Michele Marchesi, Roberto Tonelli, David Bowes, Giuseppe Destefanis:
Mining Communication Patterns in Software Development: A GitHub Analysis. PROMISE 2018: 70-79 - [c22]Giuseppe Destefanis, S. Qaderi, David Bowes, J. Petric, Marco Ortu:
A Longitudinal Study of Anti Micro Patterns in 113 versions of Tomcat. PROMISE 2018: 90-93 - [c21]Serkan Kirbas, Bora Caglayan, Tracy Hall, Steve Counsell, David Bowes, Alper Sen, Ayse Bener:
The relationship between evolutionary coupling and defects in large industrial software (journal-first abstract). SANER 2018: 471 - 2017
- [j9]Sarah Beecham, David Bowes, Klaas-Jan Stol:
Introduction to the EASE 2016 special section: Evidence-based software engineering: Past, present, and future. Information & Software Technology 89: 14-18 (2017) - [j8]Serkan Kirbas, Bora Caglayan, Tracy Hall, Steve Counsell, David Bowes, Alper Sen, Ayse Bener:
The relationship between evolutionary coupling and defects in large industrial software. Journal of Software: Evolution and Process 29(4) (2017) - [c20]David Bowes, Tracy Hall, Jean Petric, Thomas Shippey, Burak Turhan:
How Good Are My Tests? WETSoM@ICSE 2017: 9-14 - [c19]Steve Counsell, Tracy Hall, Thomas Shippey, David Bowes, Amjed Tahir, Stephen G. MacDonell:
Assert Use and Defectiveness in Industrial Code. ISSRE Workshops 2017: 20-23 - [c18]David Bowes, Steve Counsell, Tracy Hall, Jean Petric, Thomas Shippey:
Getting Defect Prediction Into Industrial Practice: the ELFF Tool. ISSRE Workshops 2017: 44-47 - [e1]Burak Turhan, David Bowes, Emad Shihab:
Proceedings of the 13th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2017, Toronto, Canada, November 8, 2017. ACM 2017, ISBN 978-1-4503-5305-2 [contents] - 2016
- [c17]Jean Petric, David Bowes, Tracy Hall, Bruce Christianson, Nathan Baddoo:
The jinx on the NASA software defect data sets. EASE 2016: 13:1-13:5 - [c16]Thomas Shippey, Tracy Hall, Steve Counsell, David Bowes:
So You Need More Method Level Datasets for Your Software Defect Prediction?: Voilà! ESEM 2016: 12:1-12:6 - [c15]Jean Petric, David Bowes, Tracy Hall, Bruce Christianson, Nathan Baddoo:
Building an Ensemble for Software Defect Prediction Based on Diversity Selection. ESEM 2016: 46:1-46:10 - [c14]David Bowes, Tracy Hall, Mark Harman, Yue Jia, Federica Sarro, Fan Wu:
Mutation-aware fault prediction. ISSTA 2016: 330-341 - 2015
- [c13]David Bowes, Tracy Hall, Jean Petric:
Different Classifiers Find Different Defects Although With Different Level of Consistency. PROMISE 2015: 3:1-3:10 - [c12]Zaheed Mahmood, David Bowes, Peter C. R. Lane, Tracy Hall:
What is the Impact of Imbalance on Software Defect Prediction Performance? PROMISE 2015: 4:1-4:4 - 2014
- [j7]David Bowes, Tracy Hall, David Gray:
DConfusion: a technique to allow cross study performance evaluation of fault prediction studies. Autom. Softw. Eng. 21(2): 287-313 (2014) - [j6]Tracy Hall, Min Zhang, David Bowes, Yi Sun:
Some Code Smells Have a Significant but Small Effect on Faults. ACM Trans. Softw. Eng. Methodol. 23(4): 33:1-33:39 (2014) - [j5]Martin J. Shepperd, David Bowes, Tracy Hall:
Researcher Bias: The Use of Machine Learning in Software Defect Prediction. IEEE Trans. Software Eng. 40(6): 603-616 (2014) - 2013
- [b1]David Bowes:
Factors affecting the performance of trainable models for software defect prediction. University of Hertfordshire, UK 2013 - [c11]David Bowes, David Randall, Tracy Hall:
The inconsistent measurement of Message Chains. WETSoM 2013: 62-68 - 2012
- [j4]D. Gray, David Bowes, Neil Davey, Y. Sun, Bruce Christianson:
Reflections on the NASA MDP data sets. IET Software 6(6): 549-558 (2012) - [j3]Tracy Hall, Sarah Beecham, David Bowes, David Gray, Steve Counsell:
A Systematic Literature Review on Fault Prediction Performance in Software Engineering. IEEE Trans. Software Eng. 38(6): 1276-1304 (2012) - [c10]Thomas Shippey, David Bowes, Bruce Christianson, Tracy Hall:
A mapping study of software code cloning. EASE 2012: 274-278 - [c9]Tracy Hall, David Bowes:
The State of Machine Learning Methodology in Software Fault Prediction. ICMLA (2) 2012: 308-313 - [c8]David Bowes, Tracy Hall, David Gray:
Comparing the performance of fault prediction models which report multiple performance measures: recomputing the confusion matrix. PROMISE 2012: 109-118 - 2011
- [j2]Tracy Hall, Sarah Beecham, David Bowes, David Gray, Steve Counsell:
Developing Fault-Prediction Models: What the Research Can Show Industry. IEEE Software 28(6): 96-99 (2011) - [c7]David Bowes, Tracy Hall, Andrew Kerr:
Program slicing-based cohesion measurement: the challenges of replicating studies using metrics. WETSoM 2011: 75-80 - 2010
- [j1]Steve Counsell, Tracy Hall, David Bowes:
A Theoretical and Empirical Analysis of Three Slice-Based Metrics for Cohesion. International Journal of Software Engineering and Knowledge Engineering 20(5): 609-636 (2010) - [c6]Steve Counsell, Tracy Hall, Emal Nasseri, David Bowes:
An Analysis of the "Inconclusive' Change Report Category in OSS Assisted by a Program Slicing Metric. EUROMICRO-SEAA 2010: 283-286 - [c5]David Gray, David Bowes, Neil Davey, Yi Sun, Bruce Christianson:
Software defect prediction using static code metrics underestimates defect-proneness. IJCNN 2010: 1-7 - [c4]Tracy Hall, David Bowes, Gernot Armin Liebchen, Paul Wernick:
Evaluating Three Approaches to Extracting Fault Data from Software Change Repositories. PROFES 2010: 107-115
2000 – 2009
- 2009
- [c3]David Gray, David Bowes, Neil Davey, Yi Sun, Bruce Christianson:
Using the Support Vector Machine as a Classification Method for Software Defect Prediction with Static Code Metrics. EANN 2009: 223-234 - [c2]Sue Black, Steve Counsell, Tracy Hall, David Bowes:
Fault Analysis in OSS Based on Program Slicing Metrics. EUROMICRO-SEAA 2009: 3-10 - [c1]David Bowes, Rod Adams, Lola Cañamero, Volker Steuber, Neil Davey:
The role of lateral inhibition in the sensory processing in a simulated spiking neural controller for a robot. ALIFE 2009: 179-183
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