2025 | |
|
[76]
|
Liliana Pasquale, Antonino Sabetta, Marcelo d’Amorim, Péter Hegedűs,
Mehdi Tarrit Mirakhorli, Hamed Okhravi, Mathias Payer, Awais Rashid, Joanna
C. S. Santos, Jonathan M. Spring, Lin Tan, and Katja Tuma.
Challenges to using large language models in code generation and
repair.
IEEE Security & Privacy, 23(2):81-88, 2025.
[ bib ]
|
2024 | |
|
[75]
|
Zoltan Sagodi, Peter Hegedus, and Rudolf Ferenc.
Increased software security with large language models.
ERCIM NEWS, (139), OCT 2024.
[ bib ]
|
|
[74]
|
Gábor Antal, Norbert Vándor, István Kolláth, Balázs Mosolygó,
Péter Hegedűs, and Rudolf Ferenc.
PyBugHive: A Comprehensive Database of Manually Validated,
Reproducible Python Bugs.
IEEE Access, 12, 2024.
[ bib ]
|
|
[73]
|
Norbert Vándor, Gábor Antal, Péter Hegedűs, and Rudolf Ferenc.
On the Usefulness of Python Structural Pattern Matching: An
Empirical Study.
In 2024 IEEE International Conference on Software Analysis,
Evolution and Reengineering (SANER), pages 501-511, 2024.
[ bib ]
|
|
[72]
|
Róbert Rajkó, István Siket, Péter Hegedűs, and Rudolf Ferenc.
Development of partial least squares regression with discriminant
analysis for software bug prediction.
HELIYON, 10:1-15, 2024.
[ bib ]
|
|
[71]
|
Amirreza Bagheri and Péter Hegedűs.
Towards a block-level conformer-based python vulnerability detection.
Software, 3:310-327, 2024.
[ bib ]
|
|
[70]
|
Amirreza Bagheri and Péter Hegedűs.
Towards a Block-Level ML-Based Python Vulnerability Detection Tool.
ACTA CYBERNETICA, 26:323-371, 2024.
[ bib ]
|
|
[69]
|
Zoltán Ságodi, Gábor Antal, Bence Bogenfürst, Martin Isztin,
Péter Hegedűs, and Rudolf Ferenc.
Reality Check: Assessing GPT-4 in Fixing Real-World Software
Vulnerabilities.
In Proceedings of the 28th International Conference on
Evaluation and Assessment in Software Engineering, EASE '24, pages 252-261.
ACM, 2024.
[ bib |
http ]
|
|
[68]
|
Antonino Sabetta, Serena Elisa Ponta, Rocio Cabrera Lozoya, Michele Bezzi,
Tommaso Sacchetti, Matteo Greco, Gergő Balogh, Péter Hegedűs,
Rudolf Ferenc, Ranindya Paramitha, Ivan Pashchenko, Aurora Papotti, Ákos
Milánkovich, and Fabio Massacci.
Known vulnerabilities of open source projects: Where are the fixes?
IEEE Security & Privacy, pages 2-12, 2024.
[ bib ]
|
|
[67]
|
Tamás Aladics, Péter Hegedűs, and Rudolf Ferenc.
A Comparative Study of Commit Representations for JIT Vulnerability
Prediction.
Computers, 13(1):22, January 2024.
[ bib |
http ]
|
2023 | |
|
[66]
|
Yue Sun, Sandor Brockhauser, Péter Hegedűs, Christian Plückthun,
Luca Gelisio, and Danilo Enoque Ferreira de Lima.
Application of self-supervised approaches to the classification of
X-ray diffraction spectra during phase transitions.
Scientific Reports, 13(1):9370, 2023.
[ bib ]
|
|
[65]
|
Tamás Aladics, Péter Hegedűs, and Rudolf Ferenc.
An AST-Based Code Change Representation and Its Performance in
Just-in-Time Vulnerability Prediction.
In Hans-Georg Fill, Marten van Sinderen, and Leszek A. Maciaszek,
editors, Software Technologies, pages 169-186, Cham, 2023. Springer
Nature Switzerland.
[ bib ]
|
|
[64]
|
Gábor Antal, Péter Hegedűs, Zoltán Herczeg, Gábor Lóki, and
Rudolf Ferenc.
Is JavaScript Call Graph Extraction Solved Yet? A Comparative Study
of Static and Dynamic Tools.
IEEE Access, 11:25266-25284, 2023.
[ bib ]
|
2022 | |
|
[63]
|
Judit Jász, Péter Hegedűs, Ákos Milánkovich, and Rudolf Ferenc.
An End-to-End Framework for Repairing Potentially Vulnerable Source
Code.
In 2022 IEEE 22nd International Working Conference on Source
Code Analysis and Manipulation (SCAM), pages 242-247, 2022.
[ bib ]
|
|
[62]
|
Yue Sun, Sándor Brockhauser, and Péter Hegedűs.
Self-Supervised Relational Reasoning framework for Spectra
Classification.
In The 13th Conference of PhD Students in Computer Science :
Volume of Short Papers, pages 187-191. University of Szeged, 2022.
[ bib ]
|
|
[61]
|
Amirreza Bagheri and Péter Hegedűs.
Towards a Block-Level ML-Based Python Vulnerability Detection Tool.
In The 13th Conference of PhD Students in Computer Science :
Volume of Short Papers, pages 17-20. University of Szeged, 2022.
[ bib ]
|
|
[60]
|
Balázs Mosolygó, Norbert Vándor, Péter Hegedűs, and
Rudolf Ferenc.
A Line-Level Explainable Vulnerability Detection Approach for Java.
In Computational Science and Its Applications - ICCSA 2022
Workshops, pages 106-122, Cham, 2022. Springer International Publishing.
[ bib ]
|
|
[59]
|
Norbert Vándor, Balázs Mosolygó, and Péter Hegelűs.
Comparing ML-Based Predictions and Static Analyzer Tools for
Vulnerability Detection.
In Computational Science and Its Applications - ICCSA 2022
Workshops, pages 92-105, Cham, 2022. Springer International Publishing.
[ bib ]
|
|
[58]
|
Amirreza Bagheri and Péter Hegedűs.
Is Refactoring Always a Good Egg? Exploring the Interconnection
Between Bugs and Refactorings.
In 2022 IEEE/ACM 19th International Conference on Mining
Software Repositories (MSR), pages 117-121, 2022.
[ bib ]
|
|
[57]
|
Tamás Aladics, Péter Hegedűs, and Rudolf Ferenc.
A Vulnerability Introducing Commit Dataset for Java: An Improved SZZ
based Approach.
In Proceedings of the 17th International Conference on Software
Technologies - ICSOFT, pages 68-78. INSTICC, SciTePress, 2022.
[ bib ]
|
|
[56]
|
Péter Hegedűs and Rudolf Ferenc.
Static Code Analysis Alarms Filtering Reloaded: A New Real-World
Dataset and its ML-Based Utilization.
IEEE Access, 10:55090-55101, 2022.
[ bib ]
|
2021 | |
|
[55]
|
Yue Sun, Sandor Brockhauser, and Péter Hegedűs.
Comparing End-to-End Machine Learning Methods for Spectra
Classification.
Applied Sciences, 11(23), 2021.
[ bib |
http ]
|
|
[54]
|
Bagheri Amirreza and Péter Hegedűs.
A Comparison of Different Source Code Representation Methods for
Vulnerability Prediction in Python.
In Proceedings of the 14th International Conference on the
Quality of Information and Communications Technology (QUATIC 2021), 2021.
[ bib ]
|
|
[53]
|
Tamás Viszkok, Péter Hegedűs, and Rudolf Ferenc.
Improving Vulnerability Prediction of JavaScript Functions Using
Process Metrics.
In Proceedings of the 16th International Conference on Software
Technologies (ICSOFT 2021), 2021.
[ bib ]
|
|
[52]
|
Gábor Antal, Zoltán Gábor Tóth, Péter Hegedűs, and Rudolf Ferenc.
Enhanced Bug Prediction in JavaScript Programs with Hybrid
Call-Graph Based Invocation Metrics.
Technologies, 9:3, 2021.
[ bib ]
|
|
[51]
|
B. Mosolygó, N. Vándor, Gábor Antal, Péter Hegedűs, and Rudolf
Ferenc.
Towards a prototype based explainable javascript vulnerability
prediction model.
In 1st International Conference on Code Quality, ICCQ 2021,
pages 15-25, 2021.
[ bib ]
|
|
[50]
|
Balázs Mosolygó, Norbert Vándor, Gábor Antal, and Péter Hegedűs.
On the Rise and Fall of Simple Stupid Bugs: a Life-Cycle Analysis of
SStuBs.
In Proceedings of the 2021 2021 IEEE/ACM 18th International
Conference on Mining Software Repositories (MSR). (2021), pages 495-499,
2021.
[ bib ]
|
2020 | |
|
[49]
|
Rudolf Ferenc, Tamás Viszkok, Tamás Aladics, Judit Jász, and
Péter Hegedűs.
Deep-water framework: The swiss army knife of humans working with
machine learning models.
SoftwareX, 12:100551, 2020.
[ bib |
http ]
|
|
[48]
|
László Vidács, Márk Jelasity, László Tóth, Péter Hegedűs, and
Rudolf Ferenc.
A mesterséges intelligencia néhány biztonsági vetülete.
SCIENTIA ET SECURITAS, 1:29-34, 2020.
[ bib ]
|
|
[47]
|
Péter Hegedűs.
Inspecting JavaScript Vulnerability Mitigation Patches with
Automated Fix Generation in Mind.
In Computational Science and Its Applications - ICCSA 2020,
pages 975-988, 2020.
[ bib ]
|
|
[46]
|
Gábor Antal, Balázs Mosolygó, Norbert Vándor, and Péter Hegedűs.
A Data-Mining Based Study of Security Vulnerability Types and Their
Mitigation in Different Languages.
In Computational Science and Its Applications - ICCSA 2020,
pages 1019-1034, 2020.
[ bib ]
|
|
[45]
|
Rudolf Ferenc, István Siket, Péter Hegedűs, and Róbert Rajkó.
Employing Partial Least Squares Regression with Discriminant
Analysis for Bug Prediction.
Technical report, 2020.
[ bib |
http ]
|
|
[44]
|
Gábor Antal, Márton Keleti, and Péter Hegedűs.
Exploring the Security Awareness of the Python and JavaScript Open
Source Communities.
In Proceedings of the 17th International Conference on Mining
Software Repositories (MSR), pages 16-20. IEEE/ACM, 2020.
[ bib ]
|
2019 | |
|
[43]
|
Rudolf Ferenc, Péter Hegedűs, Péter Gyimesi, Gábor Antal,
Dénes Bán, and Tibor Gyimóthy.
Challenging Machine Learning Algorithms in Predicting Vulnerable
JavaScript Functions.
In Proceedings of the 7th International Workshop on Realizing
Artificial Intelligence Synergies in Software Engineering, pages 8-14. IEEE
Press, 2019.
[ bib ]
|
|
[42]
|
Péter Hegedűs.
Towards analyzing the complexity landscape of solidity based ethereum
smart contracts.
Technologies, 7(1), 2019.
[ bib |
http ]
|
2018 | |
|
[41]
|
Gábor Antal, Péter Hegedűs, Zoltán Tóth, Rudolf Ferenc,
and Tibor Gyimóthy.
Static JavaScript Call Graphs: a Comparative Study.
In Proceedings of the 18th IEEE International Working Conference
on Source Code Analysis and Manipulation, pages 177-187. IEEE, 2018.
[ bib ]
|
|
[40]
|
Csaba Faragó and Péter Hegedűs.
Developer Focus: Lack of Impact on Maintainability.
In Proceedings of the International Conference on Computational
Science and Its Applications - ICCSA 2018, volume 10964, pages 391-402.
Springer International Publishing, 2018.
[ bib ]
|
|
[39]
|
Gábor Antal, Alex Szarka, and Péter Hegedűs.
A Hands-on OpenStack Code Refactoring Experience Report.
In Proceedings of the International Conference on Computational
Science and Its Applications - ICCSA 2018, volume 10964, pages 464-480.
Springer International Publishing, 2018.
[ bib ]
|
|
[38]
|
Péter Hegedűs.
Towards Analyzing the Complexity Landscape of Solidity Based
Ethereum Smart Contracts.
In Proceedings of the 1st International Workshop on Emerging
Trends in Software Engineering for Blockchain, WETSEB, pages 35-39.
ACM/IEEE, 2018.
[ bib |
.pdf ]
|
|
[37]
|
Péter Hegedűs, István Kádár, Rudolf Ferenc, and Tibor
Gyimóthy.
Empirical evaluation of software maintainability based on a manually
validated refactoring dataset.
Information and Software Technology, 95:313-327, 2018.
[ bib |
http ]
|
2016 | |
|
[36]
|
István Kádár, Péter Hegedűs, Rudolf Ferenc, and Tibor
Gyimóthy.
A Manually Validated Code Refactoring Dataset and Its Assessment
Regarding Software Maintainability.
In Proceedings of the 12th International Conference on
Predictive Models and Data Analytics in Software Engineering, PROMISE 2016,
pages 10:1-10:4, New York, NY, USA, 2016. ACM.
[ bib |
http ]
|
|
[35]
|
István Kádár, Péter Hegedűs, Rudolf Ferenc, and Tibor
Gyimóthy.
Assessment of the Code Refactoring Dataset Regarding the
Maintainability of Methods, pages 610-624.
Springer International Publishing, Cham, 2016.
[ bib |
http ]
|
|
[34]
|
István Kádár, Péter Hegedűs, Rudolf Ferenc, and Tibor Gyimóthy.
A Code Refactoring Dataset and Its Assessment Regarding Software
Maintainability.
In Proceedings of the 23rd IEEE International Conference on
Software Analysis, Evolution, and Reengineering (SANER), volume 1, pages
599-603. IEEE, March 2016.
[ bib ]
|
2015 | |
|
[33]
|
Csaba Faragó, Péter Hegedűs, Gergely Ladányi, and Rudolf Ferenc.
Impact of Version History Metrics on Maintainability.
In Proceedings of the 2015 International Conference on Advanced
Software Engineering & Its Applications, pages 30-35. IEEE CPS.
[ bib ]
|
|
[32]
|
Péter Hegedűs.
Advances in Software Product Quality Measurement and Its
Applications in Software Evolution.
In Proceedings of the International Conference on Software
Maintenance and Evolution, pages 590-593. IEEE, 2015.
[ bib ]
|
|
[31]
|
Gábor Szőke, Csaba Nagy, Péter Hegedűs, Rudolf Ferenc, and Tibor
Gyimóthy.
Do Automatic Refactorings Improve Maintainability? An Industrial
Case Study.
In Proceedings of the 31st International Conference on Software
Maintenance and Evolution - ICSME'15, pages 429-438. IEEE, September 2015.
[ bib ]
|
|
[30]
|
Csaba Faragó, Péter Hegedűs, and Rudolf Ferenc.
Cumulative Code Churn: Impact on Maintainability.
In Proceedings of the 15th IEEE International Working Conference
on Source Code Analysis and Manipulation (SCAM), pages 141-150. IEEE,
September 2015.
[ bib ]
|
|
[29]
|
István Kádár, Péter Hegedűs, and Rudolf Ferenc.
Adding Constraint Building Mechanisms to a Symbolic Execution Engine
Developed for Detecting Runtime Errors.
In Proceedings of the International Conference on Computational
Science and Its Applications - ICCSA 2015, volume 9159 of Lecture Notes
in Computer Science, pages 20-35. Springer International Publishing, 2015.
[ bib |
http ]
|
|
[28]
|
Csaba Faragó, Péter Hegedűs, and Rudolf Ferenc.
Code Ownership: Impact on Maintainability.
In Proceedings of the International Conference on Computational
Science and Its Applications - ICCSA 2015, volume 9159 of Lecture Notes
in Computer Science, pages 3-19. Springer International Publishing, 2015.
[ bib |
http ]
|
|
[27]
|
Péter Hegedűs.
Advances in Software Product Quality Measurement and its
Applications in Software Evolution.
PhD thesis, University of Szeged, 2015.
[ bib |
http ]
|
2014 | |
|
[26]
|
Csaba Faragó, Péter Hegedűs, Ádám Zoltán Végh, and Rudolf
Ferenc.
Connection Between Version Control Operations and Quality Change of
the Source Code.
Acta Cybernetica, 21(4):585-607, 2014.
[ bib ]
|
|
[25]
|
Csaba Faragó, Péter Hegedűs, and Rudolf Ferenc.
The Impact of Version Control Operations on the Quality Change of
the Source Code.
In Proceedings of the International Conference on Computational
Science and Its Applications-ICCSA 2014, pages 353-369. Springer, 2014.
[ bib ]
|
|
[24]
|
István Kádár, Péter Hegedűs, and Rudolf Ferenc.
Runtime Exception Detection in Java Programs Using Symbolic
Execution.
Acta Cybernetica, 21(3):331-352, 2014.
[ bib ]
|
|
[23]
|
Gergely Ladányi, Péter Hegedűs, Rudolf Ferenc, István Siket, and
Tibor Gyimóthy.
The Connection of the Bug Density and Maintainability of Classes.
In 8th International Workshop on Software Quality and
Maintainability, SQM, 2014 (presentation only).
http://sqm2014.sig.eu/?page=program.
[ bib ]
|
|
[22]
|
Rudolf Ferenc, Péter Hegedűs, and Tibor Gyimóthy.
Software Product Quality Models.
In Tom Mens, Alexander Serebrenik, and Anthony Cleve, editors,
Evolving Software Systems, pages 65-100. Springer Berlin Heidelberg,
2014.
[ bib |
http ]
|
|
[21]
|
Tibor Bakota, Péter Hegedűs, István Siket, Gergely Ladányi, and
Rudolf Ferenc.
QualityGate SourceAudit: a Tool for Assessing the Technical Quality
of Software.
In Proceedings of the CSMR-WCRE 2014 Software Evolution Week
(Merger of the 18th IEEE European Conference on Software Maintenance and
Reengineering & 21st IEEE Working Conference on Reverse Engineering -
CSMR-WCRE 2014), pages 440-445. IEEE, February 2014.
[ bib ]
|
2013 | |
|
[20]
|
Péter Hegedűs.
Revealing the Effect of Coding Practices on Software
Maintainability.
In Proceedings of the 29th IEEE International Conference on
Software Maintenance, ICSM '13, pages 578-581, 2013.
[ bib ]
|
|
[19]
|
Péter Hegedűs, Tibor Bakota, Gergely Ladányi, Csaba Faragó, and
Rudolf Ferenc.
A Drill-Down Approach for Measuring Maintainability at Source Code
Element Level.
Electronic Communications of the EASST, 60, 2013.
[ bib |
http ]
|
|
[18]
|
I. Kádár, P. Hegedűs, and R. Ferenc.
Runtime Exception Detection in Java Programs Using Symbolic
Execution.
In Proceedings of the 13th Symposium on Programming Languages
and Software Tools, SPLST '13, pages 215-229, 2013.
[ bib ]
|
|
[17]
|
P. Hegedűs, T. Bakota, G. Ladányi, Cs. Faragó, and R. Ferenc.
A Drill-Down Approach for Measuring Maintainability at Source Code
Element Level.
In Proceedings of the Seventh International Workshop on Software
Quality and Maintainability, SQM '13, 2013.
[ bib ]
|
|
[16]
|
Péter Hegedűs.
A Probabilistic Quality Model for C# - an Industrial Case Study.
Acta Cybernetica, 21(1):135-147, 2013.
[ bib ]
|
|
[15]
|
L. Schrettner B. Csaba, A. Beszédes, J. Jász, P. Hegedűs, and
T. Gyimóthy.
Relating Clusterization Measures and Software Quality.
In Proceedings of the 2013 European Conference on Software
Maintenance and Reengineering (CSMR'13), CSMR '13. IEEE Computer Society,
2013.
[ bib ]
|
2012 | |
|
[14]
|
P. Hegedűs, G. Ladányi, I. Siket, and R. Ferenc.
Towards Building Method Level Maintainability Models Based on Expert
Evaluations.
In FGIT-ASEA/DRBC/EL, volume 340 of Communications in
Computer and Information Science, pages 146-154. Springer, 2012.
[ bib ]
|
|
[13]
|
P. Hegedűs, D. Bán, R. Ferenc, and T. Gyimóthy.
Myth or Reality? Analyzing the Effect of Design Patterns on Software
Maintainability.
In FGIT-ASEA/DRBC/EL, volume 340 of Communications in
Computer and Information Science, pages 138-145. Springer, 2012.
[ bib ]
|
|
[12]
|
Péter Hegedűs.
A Probabilistic Software Quality Model for C# – an Industrial
Case Study.
In Proceedings of the 10th Conference of PhD Students in
Computer Science, page 23, June 2012.
[ bib ]
|
|
[11]
|
Tibor Bakota, Péter Hegedűs, Gergely Ladányi, Péter
Körtvélyesi, Rudolf Ferenc, and Tibor Gyimóthy.
A Cost Model Based on Software Maintainability.
In Proceedings of the 28th IEEE International Conference on
Software Maintenance (ICSM 2012), pages 316-325, Riva del Garda, Italy,
September 2012. IEEE Computer Society.
[ bib ]
|
2011 | |
|
[10]
|
P. Hegedűs, T. Bakota, L. Illés, G. Ladányi, R. Ferenc, and
T. Gyimóthy.
Source Code Metrics and Maintainability: A Case Study.
In Tai-Hoon Kim, Hojjat Adeli, Haeng-Kon Kim, Heau-Jo Kang,
Kyung Jung Kim, Akingbehin Kiumi, and Byeong Ho Kang, editors,
FGIT-ASEA/DRBC/EL, volume 257 of Communications in Computer and
Information Science, pages 272-284. Springer, 2011.
[ bib |
http ]
|
|
[9]
|
T. Bakota, P. Hegedűs, P. Kortvélyesi, R. Ferenc, and
T. Gyimóthy.
A Probabilistic Software Quality Model.
In Software Maintenance (ICSM), 2011 27th IEEE International
Conference on, pages 243-252, September 2011.
[ bib ]
|
2010 | |
|
[8]
|
G. Tóth, P. Hegedűs, J. Jász, Á. Beszédes, and
T. Gyimóthy.
Comparison of Different Impact Analysis Methods and Programmer's
Opinion - an Empirical Study.
In Proceedings of the 8th International Conference on the
Principles and Practice of Programming in Java (PPPJ'10), pages 109-118.
ACM, September 2010.
[ bib ]
|
|
[7]
|
L. Schrettner, P. Hegedűs, R. Ferenc, L. J. Fülöp, and T. Bakota.
Development of a Methodology, Software - Suite and Service for
Supporting Software Architecture Reconstruction.
In Proceedings of the 2010 14th European Conference on Software
Maintenance and Reengineering, CSMR '10, pages 190-193, Washington, DC,
USA, 2010. IEEE Computer Society.
[ bib |
http ]
|
|
[6]
|
G. Kniesel, A. Binun, P. Hegedűs, L. J. Fülöp, A. Chatzigeorgiou,
Y.-G. Gueheneuc, and N. Tsantalis.
DPDX - A Common Exchange Format for Design Pattern Detection Tools.
In 14th European Conference on Software Maintenance and
Reengineering (CSMR 2010), pages 232-235, March 2010.
[ bib ]
|
2009 | |
|
[5]
|
G. Kniesel, A. Binun, P. Hegedűs, L. J. Fülöp, A. Chatzigeorgiou,
Y.-G. Gueheneuc, and N. Tsantalis.
A Common Exchange Format for Design Pattern Detection Tools.
Technical report, 2009.
IAI-TR-2009-03.
[ bib ]
|
|
[4]
|
L. J. Fülöp, Á. Ilia, Á. Z. Végh, P. Hegedűs, and
R. Ferenc.
Comparing and Evaluating Design Pattern Miner Tools.
In Annales Universitatis Scientiarum Budapestinensis de Rolando
Eotvos Nominatae Sectio Computarotica, volume 31, pages 167-184. Department
of Computer Algebra, Eötvös Loránd University, 2009.
[ bib ]
|
2008 | |
|
[3]
|
L. J. Fülöp, P. Hegedűs, and R. Ferenc.
Introducing a Benchmark for Evaluating Reverse Engineering Tools.
In Proceedings of the Sixth Conference of PhD Students in
Computer Science, page 25, July 2008.
[ bib ]
|
|
[2]
|
L. J. Fülöp, P. Hegedűs, and R. Ferenc.
BEFRIEND - a Benchmark for Evaluating Reverse Engineering Tools.
Periodica Polytechnica - Electrical Engineering,
52(3-4):153-162, 2008.
[ bib ]
|
|
[1]
|
L. J. Fülöp, P. Hegedűs, R. Ferenc, and T. Gyimóthy.
Towards a Benchmark for Evaluating Reverse Engineering Tools.
In Tool Demonstrations of the 15th Working Conference on Reverse
Engineering (WCRE 2008), pages 335-336, October 2008.
[ bib ]
|