Martin J. Shepperd
Brunel University, London, UK
https://orcid.org/0000-0003-1874-6145
https://www.wikidata.org/entity/Q57451968
https://www.researcherid.com/rid/F-9683-2013
Martin J. Shepperd
Fernando Brito e Abreu
Ricardo Pérez-Castillo
Special issue on information systems quality management in practice.
281-282
2022
30
Softw. Qual. J.
2
https://doi.org/10.1007/s11219-022-09584-3
https://www.wikidata.org/entity/Q122749609
db/journals/sqj/sqj30.html#ShepperdAP22
Lucas Gren
Martin J. Shepperd
Problem reports and team maturity in agile automotive software development.
41-45
2022
CHASE@ICSE
https://doi.org/10.1145/3528579.3529173
conf/icse-chase/2022
db/conf/icse-chase/chase2022.html#GrenS22
Lucas Gren
Martin J. Shepperd
Problem reports and team maturity in agile automotive software development.
2022
abs/2204.01285
CoRR
https://doi.org/10.48550/arXiv.2204.01285
db/journals/corr/corr2204.html#abs-2204-01285
Martin J. Shepperd
Leila Yousefi
An analysis of retracted papers in Computer Science.
2022
abs/2206.06706
CoRR
https://doi.org/10.48550/arXiv.2206.06706
db/journals/corr/corr2206.html#abs-2206-06706
Robert D. Macredie
Martin J. Shepperd
Tommaso Turchi
Terry Young
Exploring Student Engagement and Outcomes: Experiences from Three Cycles of an Undergraduate Module.
2022
abs/2212.11682
CoRR
https://doi.org/10.48550/arXiv.2212.11682
db/journals/corr/corr2212.html#abs-2212-11682
Jingxiu Yao
Martin J. Shepperd
The impact of using biased performance metrics on software defect prediction research.
106664
2021
139
Inf. Softw. Technol.
https://doi.org/10.1016/j.infsof.2021.106664
https://www.wikidata.org/entity/Q111926260
db/journals/infsof/infsof139.html#YaoS21
Martin J. Shepperd
Stephen G. MacDonell
Evaluating prediction systems in software project estimation.
2021
abs/2101.05426
CoRR
https://arxiv.org/abs/2101.05426
db/journals/corr/corr2101.html#abs-2101-05426
Jingxiu Yao
Martin J. Shepperd
The impact of using biased performance metrics on software defect prediction research.
2021
abs/2103.10201
CoRR
https://arxiv.org/abs/2103.10201
db/journals/corr/corr2103.html#abs-2103-10201
Ning Li 0022
Martin J. Shepperd
Yuchen Guo
A systematic review of unsupervised learning techniques for software defect prediction.
106287
2020
122
Inf. Softw. Technol.
https://doi.org/10.1016/j.infsof.2020.106287
https://www.wikidata.org/entity/Q113316738
db/journals/infsof/infsof122.html#LiSG20
Andrea Capiluppi
Nemitari Ajienka
Nour Ali
Mahir Arzoky
Steve Counsell
Giuseppe Destefanis
Alina Dana Miron
Bhaveet Nagaria
Rumyana Neykova
Martin J. Shepperd
Stephen Swift
Allan Tucker
Using the Lexicon from Source Code to Determine Application Domain.
110-119
2020
EASE
https://doi.org/10.1145/3383219.3383231
conf/ease/2020
db/conf/ease/ease2020.html#CapiluppiAAACDM20
Jingxiu Yao
Martin J. Shepperd
Assessing software defection prediction performance: why using the Matthews correlation coefficient matters.
120-129
2020
EASE
https://doi.org/10.1145/3383219.3383232
conf/ease/2020
db/conf/ease/ease2020.html#YaoS20
Neil Walkinshaw
Martin J. Shepperd
Reasoning about Uncertainty in Empirical Results.
140-149
2020
EASE
https://doi.org/10.1145/3383219.3383234
conf/ease/2020
db/conf/ease/ease2020.html#WalkinshawS20
Martin J. Shepperd
Fernando Brito e Abreu
Alberto Rodrigues da Silva
Ricardo Pérez-Castillo
Quality of Information and Communications Technology - 13th International Conference, QUATIC 2020, Faro, Portugal, September 9-11, 2020, Proceedings
QUATIC
Springer
2020
Communications in Computer and Information Science
1266
978-3-030-58792-5
978-3-030-58793-2
https://doi.org/10.1007/978-3-030-58793-2
db/conf/quatic/quatic2020.html
Jingxiu Yao
Martin J. Shepperd
Assessing Software Defection Prediction Performance: Why Using the Matthews Correlation Coefficient Matters.
2020
abs/2003.01182
CoRR
https://arxiv.org/abs/2003.01182
db/journals/corr/corr2003.html#abs-2003-01182
Yani Xue
Miqing Li
Martin J. Shepperd
Stasha Lauria
Xiaohui Liu 0001
A novel aggregation-based dominance for Pareto-based evolutionary algorithms to configure software product lines.
32-48
2019
364
Neurocomputing
https://doi.org/10.1016/j.neucom.2019.06.075
https://www.wikidata.org/entity/Q115442057
db/journals/ijon/ijon364.html#XueLSLL19
Tim Menzies
Martin J. Shepperd
"Bad smells" in software analytics papers.
35-47
2019
112
Inf. Softw. Technol.
https://doi.org/10.1016/j.infsof.2019.04.005
https://www.wikidata.org/entity/Q113316832
db/journals/infsof/infsof112.html#MenziesS19
Qinbao Song
Yuchen Guo
Martin J. Shepperd
A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction.
1253-1269
2019
45
IEEE Trans. Software Eng.
12
https://doi.org/10.1109/TSE.2018.2836442
db/journals/tse/tse45.html#SongGS19
Martin J. Shepperd
Yuchen Guo
Ning Li 0022
Mahir Arzoky
Andrea Capiluppi
Steve Counsell
Giuseppe Destefanis
Stephen Swift
Allan Tucker
Leila Yousefi
The Prevalence of Errors in Machine Learning Experiments.
102-109
2019
IDEAL (1)
https://doi.org/10.1007/978-3-030-33607-3_12
conf/ideal/2019-1
db/conf/ideal/ideal2019-1.html#ShepperdGLACCDS19
Ning Li 0022
Martin J. Shepperd
Yuchen Guo
A Systematic Review of Unsupervised Learning Techniques for Software Defect Prediction.
2019
abs/1907.12027
CoRR
http://arxiv.org/abs/1907.12027
db/journals/corr/corr1907.html#abs-1907-12027
Martin J. Shepperd
Yuchen Guo
Ning Li 0022
Mahir Arzoky
Andrea Capiluppi
Steve Counsell
Giuseppe Destefanis
Stephen Swift
Allan Tucker
Leila Yousefi
The Prevalence of Errors in Machine Learning Experiments.
2019
abs/1909.04436
CoRR
http://arxiv.org/abs/1909.04436
db/journals/corr/corr1909.html#abs-1909-04436
Robert Feldt
Thomas Zimmermann 0001
Gunnar R. Bergersen
Davide Falessi
Andreas Jedlitschka
Natalia Juristo
Jürgen Münch
Markku Oivo
Per Runeson
Martin J. Shepperd
Dag I. K. Sjøberg
Burak Turhan
Four commentaries on the use of students and professionals in empirical software engineering experiments.
3801-3820
2018
23
Empir. Softw. Eng.
6
https://doi.org/10.1007/s10664-018-9655-0
https://www.wikidata.org/entity/Q111898985
db/journals/ese/ese23.html#FeldtZBFJJMORSS18
Martin J. Shepperd
Nemitari Ajienka
Steve Counsell
The role and value of replication in empirical software engineering results.
120-132
2018
99
Inf. Softw. Technol.
https://doi.org/10.1016/j.infsof.2018.01.006
https://www.wikidata.org/entity/Q58084137
db/journals/infsof/infsof99.html#ShepperdAC18
Martin J. Shepperd
Tracy Hall
David Bowes
Authors' Reply to "Comments on 'Researcher Bias: The Use of Machine Learning in Software Defect Prediction'".
1129-1131
2018
44
IEEE Trans. Software Eng.
11
https://doi.org/10.1109/TSE.2017.2731308
http://doi.ieeecomputersociety.org/10.1109/TSE.2017.2731308
https://www.wikidata.org/entity/Q111897876
db/journals/tse/tse44.html#ShepperdHB18
Martin J. Shepperd
Replication studies considered harmful.
73-76
2018
ICSE (NIER)
https://doi.org/10.1145/3183399.3183423
https://ieeexplore.ieee.org/document/8444842
conf/icse/2018nier
db/conf/icse/nier2018.html#Shepperd18
Yuchen Guo
Martin J. Shepperd
Ning Li 0022
Bridging effort-aware prediction and strong classification: a just-in-time software defect prediction study.
325-326
2018
ICSE (Companion Volume)
https://doi.org/10.1145/3183440.3194992
https://ieeexplore.ieee.org/document/8449561
conf/icse/2018c
db/conf/icse/icse2018c.html#GuoSL18
Martin J. Shepperd
Carolyn Mair
Magne Jørgensen
An experimental evaluation of a de-biasing intervention for professional software developers.
1510-1517
2018
SAC
https://doi.org/10.1145/3167132.3167293
conf/sac/2018
db/conf/sac/sac2018.html#ShepperdMJ18
Martin J. Shepperd
Replication studies considered harmful.
2018
abs/1802.04580
CoRR
http://arxiv.org/abs/1802.04580
db/journals/corr/corr1802.html#abs-1802-04580
Rahul Krishna
Suvodeep Majumder
Tim Menzies
Martin J. Shepperd
Bad Smells in Software Analytics Papers.
2018
abs/1803.05518
CoRR
http://arxiv.org/abs/1803.05518
db/journals/corr/corr1803.html#abs-1803-05518
Martin J. Shepperd
Carolyn Mair
Magne Jørgensen
An Experimental Evaluation of a De-biasing Intervention for Professional Software Developers.
2018
abs/1804.03919
CoRR
http://arxiv.org/abs/1804.03919
db/journals/corr/corr1804.html#abs-1804-03919
Martin J. Shepperd
Inferencing into the void: problems with implicit populations Comments on 'Empirical software engineering experts on the use of students and professionals in experiments'.
2018
abs/1810.07392
CoRR
http://arxiv.org/abs/1810.07392
db/journals/corr/corr1810.html#abs-1810-07392
Boyce Sigweni
Martin J. Shepperd
Tommaso Turchi
Realistic assessment of software effort estimation models.
41:1-41:6
2016
EASE
https://doi.org/10.1145/2915970.2916005
conf/ease/2016
db/conf/ease/ease2016.html#SigweniST16
Davide Fucci
Giuseppe Scanniello
Simone Romano 0001
Martin J. Shepperd
Boyce Sigweni
Fernando Uyaguari Uyaguari
Burak Turhan
Natalia Juristo
Markku Oivo
An External Replication on the Effects of Test-driven Development Using a Multi-site Blind Analysis Approach.
3:1-3:10
2016
ESEM
https://doi.org/10.1145/2961111.2962592
conf/esem/2016
db/conf/esem/esem2016.html#FucciS0SSUTJO16
Gernot Armin Liebchen
Martin J. Shepperd
Data Sets and Data Quality in Software Engineering: Eight Years On.
7:1-7:4
2016
PROMISE
https://doi.org/10.1145/2972958.2972967
conf/promise/2016
db/conf/promise/promise2016.html#LiebchenS16
Martin J. Shepperd
Replicated results are more trustworthy.
289-293
2016
Perspectives on Data Science for Software Engineering
https://doi.org/10.1016/b978-0-12-804206-9.00052-0
books/el/16/MWZ2016
db/books/collections/MWZ2016.html#Shepperd16
Martin J. Shepperd
How Do I Know Whether to Trust a Research Result?
106-109
2015
32
IEEE Softw.
1
https://doi.org/10.1109/MS.2015.8
http://doi.ieeecomputersociety.org/10.1109/MS.2015.8
db/journals/software/software32.html#Shepperd15
Michael James Scott
Steve Counsell
Stanislao Lauria
Stephen Swift
Allan Tucker
Martin J. Shepperd
Gheorghita Ghinea
Enhancing Practice and Achievement in Introductory Programming With a Robot Olympics.
249-254
2015
58
IEEE Trans. Educ.
4
https://doi.org/10.1109/TE.2014.2382567
https://www.wikidata.org/entity/Q21972816
db/journals/te/te58.html#ScottCLSTSG15
Boyce Sigweni
Martin J. Shepperd
Using blind analysis for software engineering experiments.
32:1-32:6
2015
EASE
https://doi.org/10.1145/2745802.2745832
conf/ease/2015
db/conf/ease/ease2015.html#SigweniS15
Martin J. Shepperd
David Bowes
Tracy Hall
Researcher Bias: The Use of Machine Learning in Software Defect Prediction.
603-616
2014
40
IEEE Trans. Software Eng.
6
https://doi.org/10.1109/TSE.2014.2322358
http://doi.ieeecomputersociety.org/10.1109/TSE.2014.2322358
https://www.wikidata.org/entity/Q58084144
db/journals/tse/tse40.html#ShepperdBH14
Boyce Sigweni
Martin J. Shepperd
Feature weighting techniques for CBR in software effort estimation studies: a review and empirical evaluation.
32-41
2014
PROMISE
https://doi.org/10.1145/2639490.2639508
conf/promise/2014
db/conf/promise/promise2014.html#SigweniS14
Martin J. Shepperd
Cost Prediction and Software Project Management.
51-71
2014
Software Project Management in a Changing World
https://doi.org/10.1007/978-3-642-55035-5_3
books/sp/RW2014
db/books/collections/RW2014.html#Shepperd14
Martin J. Shepperd
Tracy Hall
Ingunn Myrtveit
18th International Conference on Evaluation and Assessment in Software Engineering, EASE '14, London, England, United Kingdom, May 13-14, 2014
ACM
EASE
2014
978-1-4503-2476-2
http://dl.acm.org/citation.cfm?id=2601248
db/conf/ease/ease2014.html
Martin J. Shepperd
Forrest Shull
Guest Editorial for Special Section from Empirical Software Engineering & Measurement (ESEM) 2011.
1277-1278
2013
55
Inf. Softw. Technol.
7
https://doi.org/10.1016/j.infsof.2012.12.008
db/journals/infsof/infsof55.html#ShepperdS13
Ahmed E. Hassan
Abram Hindle
Per Runeson
Martin J. Shepperd
Premkumar T. Devanbu
Sunghun Kim 0001
Roundtable: What's Next in Software Analytics.
53-56
2013
30
IEEE Softw.
4
https://doi.org/10.1109/MS.2013.85
http://doi.ieeecomputersociety.org/10.1109/MS.2013.85
https://www.wikidata.org/entity/Q57726731
db/journals/software/software30.html#HassanHRSDK13
Martin J. Shepperd
Qinbao Song
Zhongbin Sun
Carolyn Mair
Data Quality: Some Comments on the NASA Software Defect Datasets.
1208-1215
2013
39
IEEE Trans. Software Eng.
9
https://doi.org/10.1109/TSE.2013.11
http://doi.ieeecomputersociety.org/10.1109/TSE.2013.11
https://www.wikidata.org/entity/Q122197832
db/journals/tse/tse39.html#ShepperdSSM13
Eisha Hasnain
Tracy Hall
Martin J. Shepperd
Using experimental games to understand communication and trust in Agile software teams.
117-120
2013
CHASE@ICSE
https://doi.org/10.1109/CHASE.2013.6614745
https://doi.ieeecomputersociety.org/10.1109/CHASE.2013.6614745
conf/icse/2013chase
db/conf/icse/chase2013.html#HasnainHS13
Tim Menzies
Martin J. Shepperd
Special issue on repeatable results in software engineering prediction.
1-17
2012
17
Empir. Softw. Eng.
1-2
https://doi.org/10.1007/s10664-011-9193-5
db/journals/ese/ese17.html#MenziesS12
Martin J. Shepperd
Stephen G. MacDonell
Evaluating prediction systems in software project estimation.
820-827
2012
54
Inf. Softw. Technol.
8
https://doi.org/10.1016/j.infsof.2011.12.008
db/journals/infsof/infsof54.html#ShepperdM12
Carolyn Mair
Miriam Martincova
Martin J. Shepperd
An Empirical Study of Software Project Managers Using a Case-Based Reasoner.
1030-1039
2012
HICSS
https://doi.org/10.1109/HICSS.2012.96
https://doi.ieeecomputersociety.org/10.1109/HICSS.2012.96
conf/hicss/2012
db/conf/hicss/hicss2012.html#MairMS12
Martin J. Shepperd
The scientific basis for prediction research.
1-2
2012
PROMISE
https://doi.org/10.1145/2365324.2365326
conf/promise/2012
db/conf/promise/promise2012.html#Shepperd12
Qinbao Song
Martin J. Shepperd
Predicting software project effort: A grey relational analysis based method.
7302-7316
2011
38
Expert Syst. Appl.
6
https://doi.org/10.1016/j.eswa.2010.12.005
db/journals/eswa/eswa38.html#SongS11
Qinbao Song
Zihan Jia
Martin J. Shepperd
Shi Ying
Jin Liu 0016
A General Software Defect-Proneness Prediction Framework.
356-370
2011
37
IEEE Trans. Software Eng.
3
https://doi.org/10.1109/TSE.2010.90
http://doi.ieeecomputersociety.org/10.1109/TSE.2010.90
db/journals/tse/tse37.html#SongJSYL11
Martin J. Shepperd
Group project work from the outset: An in-depth teaching experience report.
361-370
2011
CSEE&T
https://doi.org/10.1109/CSEET.2011.5876107
https://doi.ieeecomputersociety.org/10.1109/CSEET.2011.5876107
conf/csee/2011
db/conf/csee/csee2011.html#Shepperd11
Martin J. Shepperd
Data quality: cinderella at the software metrics ball?
1-4
2011
WETSoM
https://doi.org/10.1145/1985374.1985376
conf/icse/2011wetsom
db/conf/icse/wetsom2011.html#Shepperd11
Carolyn Mair
Martin J. Shepperd
Human judgement and software metrics: vision for the future.
81-84
2011
WETSoM
https://doi.org/10.1145/1985374.1985393
conf/icse/2011wetsom
db/conf/icse/wetsom2011.html#MairS11
Martin J. Shepperd
Combining Evidence and Meta-analysis in Software Engineering.
46-70
2011
ISSSE
https://doi.org/10.1007/978-3-642-36054-1_2
conf/issse/2011
db/conf/issse/issse2011.html#Shepperd11
Emal Nasseri
Steve Counsell
Martin J. Shepperd
Class movement and re-location: An empirical study of Java inheritance evolution.
303-315
2010
83
J. Syst. Softw.
2
https://doi.org/10.1016/j.jss.2009.08.011
db/journals/jss/jss83.html#NasseriCS10
Stephen G. MacDonell
Martin J. Shepperd
Barbara A. Kitchenham
Emilia Mendes
How Reliable Are Systematic Reviews in Empirical Software Engineering?
676-687
2010
36
IEEE Trans. Software Eng.
5
https://doi.org/10.1109/TSE.2010.28
http://doi.ieeecomputersociety.org/10.1109/TSE.2010.28
https://www.wikidata.org/entity/Q57797368
db/journals/tse/tse36.html#MacDonellSKM10
Stephen G. MacDonell
Martin J. Shepperd
Data accumulation and software effort prediction.
2010
ESEM
https://doi.org/10.1145/1852786.1852828
conf/esem/2010
db/conf/esem/esem2010.html#MacDonellS10
Ambikesh Jayal
Martin J. Shepperd
The Problem of Labels in E-Assessment of Diagrams.
2009
8
ACM J. Educ. Resour. Comput.
4
https://doi.org/10.1145/1482348.1482351
db/journals/jeric/jeric8.html#JayalS09
12:1-12:13
Yong Wang
Qinbao Song
Stephen G. MacDonell
Martin J. Shepperd
Junyi Shen
Integrate the GM(1, 1) and Verhulst Models to Predict Software Stage Effort.
647-658
2009
39
IEEE Trans. Syst. Man Cybern. Part C
6
https://doi.org/10.1109/TSMCC.2009.2020690
db/journals/tsmc/tsmcc39.html#WangSMSS09
Carolyn Mair
Miriam Martincova
Martin J. Shepperd
A Literature Review of Expert Problem Solving using Analogy.
2009
EASE
http://ewic.bcs.org/content/ConWebDoc/25031
conf/ease/2009
db/conf/ease/ease2009.html#MairMS09
Qinbao Song
Martin J. Shepperd
Xiangru Chen
Jun Liu
Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation.
2361-2370
2008
81
J. Syst. Softw.
12
https://doi.org/10.1016/j.jss.2008.05.008
db/journals/jss/jss81.html#SongSCL08
Emal Nasseri
Steve Counsell
Martin J. Shepperd
An Empirical Study of Evolution of Inheritance in Java OSS.
269-278
2008
Australian Software Engineering Conference
https://doi.ieeecomputersociety.org/10.1109/ASWEC.2008.78
conf/aswec/2008
db/conf/aswec/aswec2008.html#NasseriCS08
Gernot Armin Liebchen
Martin J. Shepperd
Data sets and data quality in software engineering.
39-44
2008
PROMISE@ICSE
https://doi.org/10.1145/1370788.1370799
conf/promise/2008
db/conf/promise/promise2008.html#LiebchenS08
Qinbao Song
Martin J. Shepperd
Missing Data Imputation Techniques.
261-291
2007
2
Int. J. Bus. Intell. Data Min.
3
https://doi.org/10.1504/IJBIDM.2007.015485
db/journals/ijbidm/ijbidm2.html#SongS07
Claes Wohlin
Sebastian G. Elbaum
Martin J. Shepperd
Most cited journal articles in software engineering.
1
2007
49
Inf. Softw. Technol.
1
https://doi.org/10.1016/j.infsof.2006.08.005
https://www.wikidata.org/entity/Q114261325
db/journals/infsof/infsof49.html#WohlinES07
Qinbao Song
Martin J. Shepperd
A new imputation method for small software project data sets.
51-62
2007
80
J. Syst. Softw.
1
https://doi.org/10.1016/j.jss.2006.05.003
db/journals/jss/jss80.html#SongS07
Magne Jørgensen
Martin J. Shepperd
A Systematic Review of Software Development Cost Estimation Studies.
33-53
2007
33
IEEE Trans. Software Eng.
1
https://doi.org/10.1109/TSE.2007.256943
db/journals/tse/tse33.html#JorgensenS07
Gernot Armin Liebchen
Bhekisipho Twala
Martin J. Shepperd
Michelle Cartwright
Mark Stephens
Filtering, Robust Filtering, Polishing: Techniques for Addressing Quality in Software Data.
99-106
2007
conf/esem/2007
ESEM
db/conf/esem/esem2007.html#LiebchenTSCS07
https://doi.org/10.1109/ESEM.2007.70
https://doi.ieeecomputersociety.org/10.1109/ESEM.2007.70
Stephen G. MacDonell
Martin J. Shepperd
Comparing Local and Global Software Effort Estimation Models - Reflections on a Systematic Review.
401-409
2007
conf/esem/2007
ESEM
db/conf/esem/esem2007.html#MacDonellS07
https://doi.org/10.1109/ESEM.2007.45
https://doi.ieeecomputersociety.org/10.1109/ESEM.2007.45
Martin J. Shepperd
Software project economics: a roadmap.
304-315
2007
FOSE
https://doi.org/10.1109/FOSE.2007.23
https://doi.ieeecomputersociety.org/10.1109/FOSE.2007.23
http://dl.acm.org/citation.cfm?id=1254726
conf/icse/2007fose
db/conf/icse/fose2007.html#Shepperd07
Qinbao Song
Martin J. Shepperd
Mining web browsing patterns for E-commerce.
622-630
2006
57
Comput. Ind.
7
https://doi.org/10.1016/j.compind.2005.11.006
db/journals/cii/cii57.html#SongS06
Qinbao Song
Martin J. Shepperd
Michelle Cartwright
Carolyn Mair
Software Defect Association Mining and Defect Correction Effort Prediction.
69-82
2006
32
IEEE Trans. Software Eng.
2
https://doi.org/10.1109/TSE.2006.1599417
http://doi.ieeecomputersociety.org/10.1109/TSE.2006.19
db/journals/tse/tse32.html#SongSCM06
Bhekisipho Twala
Michelle Cartwright
Martin J. Shepperd
Ensemble of missing data techniques to improve software prediction accuracy.
909-912
2006
conf/icse/2006
ICSE
https://doi.org/10.1145/1134285.1134449
db/conf/icse/icse2006.html#TwalaCS06
Carolyn Mair
Martin J. Shepperd
Looking at Comparisons of Regression and Analogy-based Software Project Cost Prediction.
113-118
2006
conf/serp/2006-1
Software Engineering Research and Practice
db/conf/serp/serp2006-1.html#MairS06
Qinbao Song
Martin J. Shepperd
Michelle Cartwright
A Short Note on Safest Default Missingness Mechanism Assumptions.
235-243
2005
10
Empir. Softw. Eng.
2
https://doi.org/10.1007/s10664-004-6193-8
db/journals/ese/ese10.html#SongSC05
Carolyn Mair
Martin J. Shepperd
Magne Jørgensen
An analysis of data sets used to train and validate cost prediction systems.
1-6
2005
30
ACM SIGSOFT Softw. Eng. Notes
4
https://doi.org/10.1145/1082983.1083166
db/journals/sigsoft/sigsoft30.html#MairSJ05
Ingunn Myrtveit
Erik Stensrud
Martin J. Shepperd
Reliability and Validity in Comparative Studies of Software Prediction Models.
380-391
2005
31
IEEE Trans. Software Eng.
5
https://doi.org/10.1109/TSE.2005.58
http://doi.ieeecomputersociety.org/10.1109/TSE.2005.58
db/journals/tse/tse31.html#MyrtveitSS05
Bhekisipho Twala
Michelle Cartwright
Martin J. Shepperd
Comparison of various methods for handling incomplete data in software engineering databases.
105-114
2005
conf/isese/2005
ISESE
https://doi.org/10.1109/ISESE.2005.1541819
https://doi.ieeecomputersociety.org/10.1109/ISESE.2005.1541819
https://www.wikidata.org/entity/Q59310032
db/conf/isese/isese2005.html#TwalaCS05
Carolyn Mair
Martin J. Shepperd
The consistency of empirical comparisons of regression and analogy-based software project cost prediction.
509-518
2005
conf/isese/2005
ISESE
https://doi.org/10.1109/ISESE.2005.1541858
https://doi.ieeecomputersociety.org/10.1109/ISESE.2005.1541858
db/conf/isese/isese2005.html#MairS05
Martin J. Shepperd
Evaluating Software Project Prediction Systems.
2
2005
conf/metrics/2005
IEEE METRICS
https://doi.org/10.1109/METRICS.2005.22
https://doi.ieeecomputersociety.org/10.1109/METRICS.2005.22
db/conf/metrics/metrics2005.html#Shepperd05
Qinbao Song
Martin J. Shepperd
Carolyn Mair
Using Grey Relational Analysis to Predict Software Effort with Small Data Sets.
35
2005
conf/metrics/2005
IEEE METRICS
https://doi.org/10.1109/METRICS.2005.51
https://doi.ieeecomputersociety.org/10.1109/METRICS.2005.51
db/conf/metrics/metrics2005.html#SongSM05
Rahul Premraj
Martin J. Shepperd
Barbara A. Kitchenham
Pekka Forselius
An Empirical Analysis of Software Productivity over Time.
37
2005
conf/metrics/2005
IEEE METRICS
https://doi.org/10.1109/METRICS.2005.8
https://doi.ieeecomputersociety.org/10.1109/METRICS.2005.8
https://www.wikidata.org/entity/Q57797832
db/conf/metrics/metrics2005.html#PremrajSKF05
Martin J. Shepperd
Michelle Cartwright
A Replication of the Use of Regression towards the Mean (R2M) as an Adjustment to Effort Estimation Models.
38
2005
conf/metrics/2005
IEEE METRICS
https://doi.org/10.1109/METRICS.2005.5
https://doi.ieeecomputersociety.org/10.1109/METRICS.2005.5
db/conf/metrics/metrics2005.html#ShepperdC05
Gernot Armin Liebchen
Martin J. Shepperd
Software Productivity Analysis of a Large Data Set and Issues of Confidentiality and Data Quality.
46
2005
conf/metrics/2005
IEEE METRICS
https://doi.org/10.1109/METRICS.2005.43
https://doi.ieeecomputersociety.org/10.1109/METRICS.2005.43
db/conf/metrics/metrics2005.html#LiebchenS05
Carolyn Mair
Martin J. Shepperd
Magne Jørgensen
An analysis of data sets used to train and validate cost prediction systems.
5:1-5:6
2005
PROMISE@ICSE
https://doi.org/10.1145/1083165.1083166
conf/promise/2005
db/conf/promise/promise2005.html#MairSJ05
Ignatios S. Deligiannis
Ioannis Stamelos
Lefteris Angelis
Manos Roumeliotis
Martin J. Shepperd
A controlled experiment investigation of an object-oriented design heuristic for maintainability.
129-143
2004
72
J. Syst. Softw.
2
https://doi.org/10.1016/S0164-1212(03)00240-1
db/journals/jss/jss72.html#DeligiannisSARS04
John K. Hart
Martin J. Shepperd
The Evolution of Concurrent Control Software Using Genetic Programming.
289-298
https://doi.org/10.1007/978-3-540-24650-3_27
2004
conf/eurogp/2004
EuroGP
db/conf/eurogp/eurogp2004.html#HartS04
John A. Clark
José Javier Dolado
Mark Harman
Robert M. Hierons
Bryan F. Jones
M. Lumkin
Brian S. Mitchell
Spiros Mancoridis
K. Rees
Marc Roper
Martin J. Shepperd
Formulating software engineering as a search problem.
161-175
2003
150
IEE Proc. Softw.
3
db/journals/iee/iee-s150.html#ClarkeDHHJLMMRRS03
https://doi.org/10.1049/ip-sen:20030559
https://www.wikidata.org/entity/Q29030482
Ignatios S. Deligiannis
Martin J. Shepperd
Manos Roumeliotis
Ioannis Stamelos
An empirical investigation of an object-oriented design heuristic for maintainability.
127-139
2003
65
J. Syst. Softw.
2
https://doi.org/10.1016/S0164-1212(02)00054-7
db/journals/jss/jss65.html#DeligiannisSRS03
Stephen G. MacDonell
Martin J. Shepperd
Combining techniques to optimize effort predictions in software project management.
91-98
2003
66
J. Syst. Softw.
2
https://doi.org/10.1016/S0164-1212(02)00067-5
db/journals/jss/jss66.html#MacDonellS03
Martin Lefley
Martin J. Shepperd
Using Genetic Programming to Improve Software Effort Estimation Based on General Data Sets.
2477-2487
2003
conf/gecco/2003-2
GECCO
https://doi.org/10.1007/3-540-45110-2_151
db/conf/gecco/gecco2003-2.html#LefleyS03
Colin Kirsopp
Emilia Mendes
Rahul Premraj
Martin J. Shepperd
An Empirical Analysis of Linear Adaptation Techniques for Case-Based Prediction.
231-245
2003
conf/iccbr/2003
ICCBR
https://doi.org/10.1007/3-540-45006-8_20
db/conf/iccbr/iccbr2003.html#KirsoppMPS03
Ursula Passing
Martin J. Shepperd
An experiment on software project size and effort estimation.
120-131
2003
conf/isese/2003
ISESE
https://doi.org/10.1109/ISESE.2003.1237971
https://doi.ieeecomputersociety.org/10.1109/ISESE.2003.1237971
db/conf/isese/isese2003.html#PassingS03
Stephen G. MacDonell
Martin J. Shepperd
Using Prior-Phase Effort Records for Re-estimation During Software Projects.
73-
2003
conf/metrics/2003
IEEE METRICS
https://doi.org/10.1109/METRIC.2003.1232457
https://doi.ieeecomputersociety.org/10.1109/METRIC.2003.1232457
db/conf/metrics/metrics2003.html#MacDonellS03
Michelle Cartwright
Martin J. Shepperd
Qinbao Song
Dealing with Missing Software Project Data.
154-165
2003
conf/metrics/2003
IEEE METRICS
https://doi.org/10.1109/METRIC.2003.1232464
https://doi.ieeecomputersociety.org/10.1109/METRIC.2003.1232464
db/conf/metrics/metrics2003.html#CartwrightSS03
Ignatios S. Deligiannis
Martin J. Shepperd
Steve Webster
Manos Roumeliotis
A Review of Experimental Investigations into Object-Oriented Technology.
193-231
2002
7
Empir. Softw. Eng.
3
db/journals/ese/ese7.html#DeligiannisSWR02
Colin Kirsopp
Martin J. Shepperd
Making inferences with small numbers of training sets.
123-130
2002
149
IEE Proc. Softw.
5
db/journals/iee/iee-s149.html#KirsoppS02
https://doi.org/10.1049/ip-sen:20020695
Michael Dyer
Martin J. Shepperd
Claes Wohlin
Editorial.
63
2002
44
Inf. Softw. Technol.
2
db/journals/infsof/infsof44.html#DyerSW02
https://doi.org/10.1016/S0950-5849(02)00018-6
John K. Hart
Martin J. Shepperd
Evolving Software with Multiple Outputs and Multiple Populations.
223-227
2002
conf/gecco/2002late
GECCO Late Breaking Papers
db/conf/gecco/gecco2002late.html#HartS02
Colin Kirsopp
Martin J. Shepperd
John K. Hart
Search Heuristics, Case-based Reasoning And Software Project Effort Prediction.
1367-1374
2002
conf/gecco/2002
GECCO
db/conf/gecco/gecco2002.html#KirsoppSH02
Barbara A. Kitchenham
Lesley Pickard
Stephen G. MacDonell
Martin J. Shepperd
What accuracy statistics really measure.
81-85
2001
148
IEE Proc. Softw.
3
db/journals/iee/iee-s148.html#KitchenhamPMS01
https://doi.org/10.1049/ip-sen:20010506
https://www.wikidata.org/entity/Q57798054
Martin J. Shepperd
Michael Dyer
Editorial Note.
813
2001
43
Inf. Softw. Technol.
14
db/journals/infsof/infsof43.html#ShepperdD01
https://doi.org/10.1016/S0950-5849(01)00205-1
Martin J. Shepperd
Michelle Cartwright
Predicting with Sparse Data.
987-998
2001
27
IEEE Trans. Software Eng.
11
https://doi.org/10.1109/32.965339
http://doi.ieeecomputersociety.org/10.1109/32.965339
db/journals/tse/tse27.html#ShepperdC01
Martin J. Shepperd
Gada F. Kadoda
Comparing Software Prediction Techniques Using Simulation.
1014-1022
2001
27
IEEE Trans. Software Eng.
11
https://doi.org/10.1109/32.965341
http://doi.ieeecomputersociety.org/10.1109/32.965341
https://www.wikidata.org/entity/Q60142164
db/journals/tse/tse27.html#ShepperdK01
Gada F. Kadoda
Michelle Cartwright
Martin J. Shepperd
Issues on the Effective Use of CBR Technology for Software Project Prediction.
276-290
2001
conf/iccbr/2001
ICCBR
https://doi.org/10.1007/3-540-44593-5_20
db/conf/iccbr/iccbr2001.html#KadodaCS01
Martin J. Shepperd
Michelle Cartwright
Predicting With Sparse Data.
28-
2001
conf/metrics/2001
IEEE METRICS
https://doi.org/10.1109/METRIC.2001.915513
https://doi.ieeecomputersociety.org/10.1109/METRIC.2001.915513
db/conf/metrics/metrics2001.html#ShepperdC01
Martin J. Shepperd
Gada F. Kadoda
Using Simulation to Evaluate Prediction Techniques.
349-
2001
conf/metrics/2001
IEEE METRICS
https://doi.org/10.1109/METRIC.2001.915542
https://doi.ieeecomputersociety.org/10.1109/METRIC.2001.915542
db/conf/metrics/metrics2001.html#ShepperdK01
Martin J. Shepperd
Michelle Cartwright
Gada F. Kadoda
On Building Prediction Systems for Software Engineers.
175-182
2000
5
Empir. Softw. Eng.
3
db/journals/ese/ese5.html#ShepperdCK00
Keith Phalp
Martin J. Shepperd
Quantitative analysis of static models of processes.
105-112
2000
52
J. Syst. Softw.
2-3
https://doi.org/10.1016/S0164-1212(99)00136-3
db/journals/jss/jss52.html#PhalpS00
Carolyn Mair
Gada F. Kadoda
Martin Lefley
Keith Phalp
Chris Schofield
Martin J. Shepperd
Steve Webster
An investigation of machine learning based prediction systems.
23-29
2000
53
J. Syst. Softw.
1
https://doi.org/10.1016/S0164-1212(00)00005-4
db/journals/jss/jss53.html#MairKLPSSW00
Michelle Cartwright
Martin J. Shepperd
An Empirical Investigation of an Object-Oriented Software System.
786-796
2000
26
IEEE Trans. Software Eng.
8
https://doi.org/10.1109/32.879814
http://doi.ieeecomputersociety.org/10.1109/32.879814
db/journals/tse/tse26.html#CartwrightS00
Shari Lawrence Pfleeger
Martin J. Shepperd
Roseanne Tesoriero
Decisions and Delphi: The Dynamics of Group Estimation.
3-15
2000
SBES
https://doi.org/10.5753/sbes.2000.25916
conf/sbes/2000
db/conf/sbes/sbes2000.html#PfleegerST00
Michael Dyer
Martin J. Shepperd
Perspectives on Information Technology in the New Millennium.
931
1999
41
Inf. Softw. Technol.
14
https://doi.org/10.1016/S0950-5849(99)00066-X
db/journals/infsof/infsof41.html#DyerS99
Austen Rainer
Martin J. Shepperd
Re-Planning for a Successful Project Schedule.
72-81
1999
conf/metrics/1999
IEEE METRICS
https://doi.org/10.1109/METRIC.1999.809728
https://doi.ieeecomputersociety.org/10.1109/METRIC.1999.809728
db/conf/metrics/metrics1999.html#RainerS99
Andrew R. Gray
Stephen G. MacDonell
Martin J. Shepperd
Factors Systematically Associated with Errors in Subjective Estimates of Software Development Effort: The Stability of Expert Judgment.
216-
1999
conf/metrics/1999
IEEE METRICS
https://doi.org/10.1109/METRIC.1999.809743
https://doi.ieeecomputersociety.org/10.1109/METRIC.1999.809743
https://www.wikidata.org/entity/Q60683873
db/conf/metrics/metrics1999.html#GrayMS99
Colin Kirsopp
Martin J. Shepperd
Steve Webster
An Empirical Study into the Use of Measurement to Support OO Design Evaluation.
230-241
1999
conf/metrics/1999
IEEE METRICS
https://doi.org/10.1109/METRIC.1999.809744
https://doi.ieeecomputersociety.org/10.1109/METRIC.1999.809744
db/conf/metrics/metrics1999.html#KirsoppSW99
Rachel Harrison
Lionel C. Briand
John W. Daly
Marc I. Kellner
David Raffo
Martin J. Shepperd
Process Modelling and Empirical Studies of Software Evolution (PMESSE'97) Workshop Report.
381-403
1997
2
Empir. Softw. Eng.
4
https://doi.org/10.1023/A:1009749918745
db/journals/ese/ese2.html#HarrisonBDKRS97
Martin J. Shepperd
Chris Schofield
Estimating Software Project Effort Using Analogies.
736-743
https://doi.org/10.1109/32.637387
http://doi.ieeecomputersociety.org/10.1109/32.637387
1997
23
IEEE Trans. Software Eng.
11
db/journals/tse/tse23.html#ShepperdS97
Rachel Harrison
Martin J. Shepperd
John W. Daly
Workshop Summary: Process Modelling and Empirical Studies of Software Evolution.
675
1997
conf/icse/1997
ICSE
https://doi.org/10.1145/253228.253829
db/conf/icse/icse97.html#HarrisonSD97
Martin J. Shepperd
Chris Schofield
Barbara A. Kitchenham
Effort Estimation Using Analogy.
170-178
1996
conf/icse/1996
ICSE
http://portal.acm.org/citation.cfm?id=227726.227758
db/conf/icse/icse96.html#ShepperdSK96
Martin J. Shepperd
Foundations of software measurement.
I-XII, 1-234
Prentice Hall
1995
978-0-13-336199-5
Michael Dyer
Martin J. Shepperd
Editorial.
3
1995
37
Inf. Softw. Technol.
1
https://doi.org/10.1016/0950-5849(95)90045-4
db/journals/infsof/infsof37.html#DyerS95
Neville I. Churcher
Martin J. Shepperd
Towards a conceptual framework for object oriented software metrics.
69-75
1995
20
ACM SIGSOFT Softw. Eng. Notes
2
https://doi.org/10.1145/224155.224163
db/journals/sigsoft/sigsoft20.html#ChurcherS95
Neville I. Churcher
Martin J. Shepperd
Comments on "A Metrics Suite for Object Oriented Design".
263-265
https://doi.org/10.1109/32.372153
http://doi.ieeecomputersociety.org/10.1109/32.372153
1995
21
IEEE Trans. Software Eng.
3
db/journals/tse/tse21.html#ChurcherS95
Michael Dyer
Martin J. Shepperd
Editorial.
2
1994
36
Inf. Softw. Technol.
1
https://doi.org/10.1016/0950-5849(94)90002-7
db/journals/infsof/infsof36.html#DyerS94
Martin J. Shepperd
Darrel C. Ince
A critique of three metrics.
197-210
1994
26
J. Syst. Softw.
3
https://doi.org/10.1016/0164-1212(94)90011-6
db/journals/jss/jss26.html#ShepperdI94
Keith Phalp
Martin J. Shepperd
A Pragmatic Approach to Process Modelling.
65-68
1994
conf/ewspt/1994
EWSPT
db/conf/ewspt/ewspt1994.html#PhalpS94
https://doi.org/10.1007/3-540-57739-4_9
Martin J. Shepperd
Practical software metrics for project management and process improvement: R Grady Prentice-Hall (1992) £30.95 282 pp ISBN 0 13 720384 5.
701
1993
35
Inf. Softw. Technol.
11-12
https://doi.org/10.1016/0950-5849(93)90091-G
db/journals/infsof/infsof35.html#Shepperd93
Martin J. Shepperd
First International Conference on the Software Process Redondo Beach, CA, USA 21-22 October 1991.
276-277
1992
34
Inf. Softw. Technol.
4
https://doi.org/10.1016/0950-5849(92)90084-3
db/journals/infsof/infsof34.html#Shepperd92
Martin J. Shepperd
Software engineer's reference book J McDermid (ed) Butterworth-Heinemann (1991) £125 hardback ISBN 0-750-61040-9.
419
1992
34
Inf. Softw. Technol.
6
https://doi.org/10.1016/0950-5849(92)90022-H
db/journals/infsof/infsof34.html#Shepperd92a
Martin J. Shepperd
Products, processes and metrics.
674-680
1992
34
Inf. Softw. Technol.
10
https://doi.org/10.1016/0950-5849(92)90072-W
db/journals/infsof/infsof34.html#Shepperd92b
Martin J. Shepperd
Measurement of structure and size of software designs.
756-762
1992
34
Inf. Softw. Technol.
11
https://doi.org/10.1016/0950-5849(92)90170-T
db/journals/infsof/infsof34.html#Shepperd92c
Martin J. Shepperd
System architecture metrics : an evaluation.
1991
Open University, Milton Keynes, UK
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305595
British Library, EThOS
Martin J. Shepperd
Darrel C. Ince
Software Metrics in Software Engineering and Artificial Intelligence.
463-476
1991
1
Int. J. Softw. Eng. Knowl. Eng.
4
https://doi.org/10.1142/S0218194091000305
db/journals/ijseke/ijseke1.html#ShepperdI91
Martin J. Shepperd
Darrel C. Ince
Design metrics and software maintainability: An experimental investigation.
215-232
1991
3
J. Softw. Maintenance Res. Pract.
4
https://doi.org/10.1002/smr.4360030404
db/journals/smr/smr3.html#ShepperdI91
Martin J. Shepperd
Darrel C. Ince
Algebraic Validation of software Metrics.
343-363
1991
conf/esec/1991
ESEC
db/conf/esec/esec91.html#ShepperdI91
https://doi.org/10.1007/3540547428_57
Martin J. Shepperd
Algebraic Models and Metric Validation.
157-175
1991
conf/facs/1991
Formal Aspects of Measurement
db/conf/facs/facs1991.html#Shepperd91
Martin J. Shepperd
Design metrics: an empirical analysis.
3-10
1990
5
Softw. Eng. J.
1
https://doi.org/10.1049/sej.1990.0002
db/journals/iee/iee-sej5.html#Sheppard90
Martin J. Shepperd
Darrel C. Ince
Multi-Dimensional Modelling and Measurement of Software Designs.
76-81
1990
conf/acm/1990
ACM Conference on Computer Science
https://doi.org/10.1145/100348.102090
db/conf/acm/csc90.html#ShepperdI90
Martin J. Shepperd
A critique of cyclomatic complexity as a software metric.
30-36
1988
3
Softw. Eng. J.
2
https://doi.org/10.1049/sej.1988.0003
db/journals/iee/iee-sej3.html#Shepperd88
Fernando Brito e Abreu
Nemitari Ajienka
Nour Ali
Lefteris Angelis
Mahir Arzoky
Gunnar R. Bergersen
David Bowes
Lionel C. Briand
Andrea Capiluppi
Michelle Cartwright
Xiangru Chen
Neville ChurcherNeville I. Churcher
John A. Clark
Steve Counsell
John W. Daly
Ignatios S. Deligiannis
Giuseppe Destefanis
Premkumar T. Devanbu
José Javier Dolado
Michael Dyer
Sebastian G. Elbaum
Davide Falessi
Robert Feldt
Pekka Forselius
Davide Fucci
George GhineaGheorghita Ghinea
Andrew R. Gray
Lucas Gren
Yuchen Guo
Tracy Hall
Mark Harman
Rachel Harrison
John K. Hart
Eisha Hasnain
Ahmed E. Hassan
Robert M. Hierons
Abram Hindle
Darrel C. Ince
Ambikesh Jayal
Andreas Jedlitschka
Zihan Jia
Bryan F. Jones
Magne Jørgensen
Natalia Juristo JuzgadoNatalia Juristo
Gada F. Kadoda
Marc I. Kellner
Sunghun Kim 0001
Colin Kirsopp
Barbara A. Kitchenham
Rahul Krishna
Stanislao Lauria
Stasha Lauria
Martin Lefley
Miqing Li
Ning Li 0022
Gernot Armin Liebchen
Jin Liu 0016
Jun Liu
Xiaohui Liu 0001
Ursula Löbbert-PassingUrsula Passing
M. Lumkin
Stephen G. MacDonell
Robert D. Macredie
Carolyn Mair
Suvodeep Majumder
Spiros Mancoridis
Miriam Martincova
Emilia Mendes
Tim Menzies
Alina Dana Miron
Brian S. Mitchell
Jürgen Münch
Ingunn Myrtveit
Bhaveet Nagaria
Emal Nasseri
Rumyana Neykova
Markku Oivo
Ricardo Pérez-Castillo
Shari Lawrence Pfleeger
Keith Phalp
Lesley Pickard
Rahul Premraj
David Raffo
Austen Rainer
K. Rees
Simone Romano 0001
Marc Roper
Manos Roumeliotis
Per Runeson
Giuseppe Scanniello
Chris Schofield
Michael 'Adrir' ScottMichael James Scott
Junyi Shen
Forrest Shull
Boyce Sigweni
Alberto Rodrigues da Silva
Dag I. K. Sjøberg
Qinbao Song
Ioannis Stamelos
Erik Stensrud
Mark Stephens
Zhongbin Sun
Stephen Swift
Allan Tucker
Tommaso Turchi
Burak Turhan
Roseanne Tesoriero TvedtRoseanne Tesoriero
Bhekisipho Twala
Fernando UyaguariFernando Uyaguari Uyaguari
Neil Walkinshaw
Yong Wang
Steve Webster
Claes Wohlin
Yani Xue
Jingxiu Yao
Shi Ying
Terry Young
Leila Yousefi
Thomas Zimmermann 0001