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Ayse Basar – Ayse Bener
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2020 – today
- 2023
[j57]Sanaz Mohammadjafari, Mucahit Cevik
, Ayse Basar:
VARGAN: variance enforcing network enhanced GAN. Appl. Intell. 53(1): 69-95 (2023)- [i20]Savas Yildirim, Mucahit Cevik, Devang Parikh, Ayse Basar:
Adaptive Fine-tuning for Multiclass Classification over Software Requirement Data. CoRR abs/2301.00495 (2023) - [i19]Garima Malik, Savas Yildirim, Mucahit Cevik, Ayse Bener, Devang Parikh:
Transfer learning for conflict and duplicate detection in software requirement pairs. CoRR abs/2301.03709 (2023) - 2022
- [j56]Eray Mert Kavuk, Ayse Tosun, Mucahit Cevik, Aysun Bozanta, Sibel B. Sonuc, Mehmetcan Tutuncu, Bilgin Kosucu, Ayse Basar:
Order dispatching for an ultra-fast delivery service via deep reinforcement learning. Appl. Intell. 52(4): 4274-4299 (2022) - [j55]Aysun Bozanta, Mucahit Cevik, Can Kavaklioglu, Eray Mert Kavuk, Ayse Tosun, Sibel B. Sonuc, Alper Duranel, Ayse Basar:
Courier routing and assignment for food delivery service using reinforcement learning. Comput. Ind. Eng. 164: 107871 (2022) - [j54]Parisa Lak, Aysun Bozanta, Can Kavaklioglu, Mucahit Cevik, Ayse Basar, Martin Petitclerc, Graham J. Wills:
A replication study on implicit feedback recommender systems with application to the data visualization recommendation. Expert Syst. J. Knowl. Eng. 39(4) (2022) - [j53]Hadi Jahanshahi, Mucahit Cevik, José Navas-Sú, Ayse Basar, Antonio González Torres:
Wayback Machine: A tool to capture the evolutionary behavior of the bug reports and their triage process in open-source software systems. J. Syst. Softw. 189: 111308 (2022) - [j52]Hadi Jahanshahi, Aysun Bozanta, Mucahit Cevik, Eray Mert Kavuk, Ayse Tosun, Sibel B. Sonuc, Bilgin Kosucu, Ayse Basar:
A deep reinforcement learning approach for the meal delivery problem. Knowl. Based Syst. 243: 108489 (2022) - [j51]Ozan Ozyegen, Sanaz Mohammadjafari, Mucahit Cevik, Karim El Mokhtari, Jonathan Ethier, Ayse Basar:
An Empirical Study on Using CNNs for Fast Radio Signal Prediction. SN Comput. Sci. 3(2): 131 (2022) - [c140]Garima Malik, Mucahit Cevik, Swayami Bera, Savas Yildirim, Devang Parikh, Ayse Basar:
Software requirement specific entity extraction using transformer models. AI 2022 - [i18]Aysun Bozanta, Sean Berry, Mucahit Cevik, Beste Bulut, Deniz Yigit, Fahrettin F. Gonen, Ayse Basar:
Time Series Clustering for Grouping Products Based on Price and Sales Patterns. CoRR abs/2204.08334 (2022) - [i17]Garima Malik, Mucahit Cevik, Devang Parikh, Ayse Basar:
Identifying the requirement conflicts in SRS documents using transformer-based sentence embeddings. CoRR abs/2206.13690 (2022) - [i16]Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar:
Improved α-GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning. CoRR abs/2207.11223 (2022) - [i15]Ozan Ozyegen, Nicholas Prayogo, Mucahit Cevik, Ayse Basar:
Interpretable Time Series Clustering Using Local Explanations. CoRR abs/2208.01152 (2022) - [i14]Hadi Jahanshahi, Mucahit Cevik, Kianoush Mousavi, Ayse Basar:
ADPTriage: Approximate Dynamic Programming for Bug Triage. CoRR abs/2211.00872 (2022) - 2021
- [j50]Sanaz Mohammadjafari, Ozan Ozyegen, Mucahit Cevik, Emir Kavurmacioglu, Jonathan Ethier, Ayse Basar:
Designing mm-wave electromagnetic engineered surfaces using generative adversarial networks. Neural Comput. Appl. 33(17): 11309-11323 (2021) - [j49]Beyza Eken, Francis Palma, Ayse Basar, Ayse Tosun:
An empirical study on the effect of community smells on bug prediction. Softw. Qual. J. 29(1): 159-194 (2021) - [c139]Derya Kici, Garima Malik, Mucahit Cevik, Devang Parikh, Ayse Basar:
A BERT-based transfer learning approach to text classification on software requirements specifications. Canadian Conference on AI 2021 - [c138]Garima Malik, Mucahit Cevik, Yusef Khedr, Devang Parikh, Ayse Basar:
Named Entity Recognition on Software Requirements Specification Documents. Canadian Conference on AI 2021 - [c137]Sanaz Mohammadjafari, Mucahit Cevik, Mathusan Thanabalasingam, Ayse Basar, Alzheimer's Disease Neuroimaging Initiative:
Using ProtoPNet for Interpretable Alzheimer's Disease Classification. Canadian Conference on AI 2021 - [c136]Hadi Jahanshahi, Ozan Ozyegen, Mucahit Cevik, Beste Bulut, Deniz Yigit, Fahrettin F. Gonen, Ayse Basar:
Text classification for predicting multi-level product categories. CASCON 2021: 33-42 - [c135]Derya Kici, Aysun Bozanta, Mucahit Cevik, Devang Parikh, Ayse Basar:
Text classification on software requirements specifications using transformer models. CASCON 2021: 163-172 - [c134]Mucahit Cevik, Savas Yildirim, Ayse Basar:
Natural language processing for software requirement specifications. CASCON 2021: 308-309 - [c133]Hadi Jahanshahi, Kritika Chhabra, Mucahit Cevik, Ayse Basar:
DABT: A Dependency-aware Bug Triaging Method. EASE 2021: 221-230 - [c132]Aysun Bozanta, Sabrina Angco, Mucahit Cevik, Ayse Basar:
Sentiment Analysis of StockTwits Using Transformer Models. ICMLA 2021: 1253-1258 - [i13]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Moving from Cross-Project Defect Prediction to Heterogeneous Defect Prediction: A Partial Replication Study. CoRR abs/2103.03490 (2021) - [i12]Hadi Jahanshahi, Dhanya Jothimani, Ayse Basar, Mucahit Cevik:
Does chronology matter in JIT defect prediction? A Partial Replication Study. CoRR abs/2103.03506 (2021) - [i11]Hadi Jahanshahi, Aysun Bozanta, Mucahit Cevik, Eray Mert Kavuk, Ayse Tosun, Sibel B. Sonuc, Bilgin Kosucu, Ayse Basar:
A Deep Reinforcement Learning Approach for the Meal Delivery Problem. CoRR abs/2104.12000 (2021) - [i10]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Predicting the Number of Reported Bugs in a Software Repository. CoRR abs/2104.12001 (2021) - [i9]Hadi Jahanshahi, Kritika Chhabra, Mucahit Cevik, Ayse Basar:
DABT: A Dependency-aware Bug Triaging Method. CoRR abs/2104.12744 (2021) - [i8]Hadi Jahanshahi, Ozan Ozyegen, Mucahit Cevik, Beste Bulut, Deniz Yigit, Fahrettin F. Gonen, Ayse Basar:
Text Classification for Predicting Multi-level Product Categories. CoRR abs/2109.01084 (2021) - [i7]Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar:
VARGAN: Variance Enforcing Network Enhanced GAN. CoRR abs/2109.02117 (2021) - 2020
- [j48]Shirin Akbarinasaji, Can Kavaklioglu, Ayse Basar, Adam Neal:
Partially observable Markov decision process to generate policies in software defect management. J. Syst. Softw. 163: 110518 (2020) - [j47]Ashok Bhowmick, Mucahit Cevik, Ayse Basar:
Analyzing Intracranial EEG in Pharmacoresistant Epilepsy Patients Using Hidden Markov Models and Time Series Forecasting Methods. SN Comput. Sci. 1(6): 325 (2020) - [j46]Ozan Ozyegen, Sanaz Mohammadjafari, Emir Kavurmacioglu, John Maidens, Ayse Basar Bener:
Experimental Results on the Impact of Memory in Neural Networks for Spectrum Prediction in Land Mobile Radio Bands. IEEE Trans. Cogn. Commun. Netw. 6(2): 771-782 (2020) - [j45]Sanaz Mohammadjafari, Sophie Roginsky, Emir Kavurmacioglu, Mucahit Cevik, Jonathan Ethier, Ayse Basar Bener:
Machine Learning-Based Radio Coverage Prediction in Urban Environments. IEEE Trans. Netw. Serv. Manag. 17(4): 2117-2130 (2020) - [c131]Karim El Mokhtari, Mucahit Cevik, Ayse Basar:
Using Topic Modelling to Improve Prediction of Financial Report Commentary Classes. Canadian Conference on AI 2020: 201-207 - [c130]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Predicting the Number of Reported Bugs in a Software Repository. Canadian Conference on AI 2020: 309-320 - [c129]Sukhjit Singh Sehra, Tamer Abdou, Ayse Basar, Sumeet Kaur Sehra:
Amalgamated Models for Detecting Duplicate Bug Reports. Canadian Conference on AI 2020: 470-482 - [c128]Hadi Jahanshahi, Mucahit Cevik, Ayse Basar:
Moving from cross-project defect prediction to heterogeneous defect prediction: a partial replication study. CASCON 2020: 133-142 - [c127]Jingli Wang, Ashok Bhowmick, Mucahit Cevik, Ayse Basar:
Deep learning approaches to classify the relevance and sentiment of news articles to the economy. CASCON 2020: 207-216 - [i6]Ozan Ozyegen, Sanaz Mohammadjafari, Karim El Mokhtari, Mucahit Cevik, Jonathan Ethier, Ayse Basar:
Deep learning approaches for fast radio signal prediction. CoRR abs/2006.09245 (2020) - [i5]Hadi Jahanshahi, Mucahit Cevik, José Navas-Sú, Ayse Basar, Antonio González Torres:
Wayback Machine: Capturing the evolutionary behaviour of the bug dependency graph in open-source software systems. CoRR abs/2011.05382 (2020)
2010 – 2019
- 2019
- [c126]Karim El Mokhtari, John Maidens, Ayse Bener:
Predicting Commentaries on a Financial Report with Recurrent Neural Networks. Canadian Conference on AI 2019: 531-542 - [c125]Nicolas Ewen, Tamer Abdou, Ayse Bener:
Applications of Feature Selection Techniques on Large Biomedical Datasets. Canadian Conference on AI 2019: 543-548 - [c124]Savas Yildirim, Dhanya Jothimani, Can Kavaklioglu, Ayse Basar:
Deep Learning Approaches for Sentiment Analysis on Financial Microblog Dataset. IEEE BigData 2019: 5581-5584 - [c123]Abel Ag Rb Guimaraes, Tamer Abdou, Ayse Basar:
Deep learning brain regions in Harvard-Oxford atlas using SegNet model. CASCON 2019: 120-129 - [c122]Ozan Ozyegen, Emir Kavurmacioglu, Jonathan Ethier, Ayse Basar:
Generative adversarial networks in designing electromagnetic engineered surfaces for mm-Wave band spectrum environments. CASCON 2019: 148-155 - [c121]Karim El Mokhtari, Ben Peachey Higdon, Ayse Basar:
Interpreting financial time series with SHAP values. CASCON 2019: 166-172 - [c120]Ronnie E. S. Santos, Ayse Basar Bener, Maria Teresa Baldassarre, Cleyton V. C. de Magalhães, Jorge S. Correia Neto, Fabio Q. B. da Silva:
Mind the gap: are practitioners and researchers in software testing speaking the same language? CESSER-IP@ICSE 2019: 10-17 - [c119]Sanaz Mohammadjafari, Emir Kavurmacioglu, John Maidens, Ayse Bener:
Neural Network Based Spectrum Prediction in Land Mobile Radio Bands for IoT deployments. IM 2019: 31-36 - [c118]Sravya Polisetty, Andriy V. Miranskyy, Ayse Basar:
On Usefulness of the Deep-Learning-Based Bug Localization Models to Practitioners. PROMISE 2019: 16-25 - [c117]Hadi Jahanshahi, Dhanya Jothimani, Ayse Basar, Mucahit Cevik:
Does chronology matter in JIT defect prediction?: A Partial Replication Study. PROMISE 2019: 90-99 - [c116]Dhanya Jothimani, Ayse Basar:
Stock Index Forecasting Using Time Series Decomposition-Based and Machine Learning Models. SGAI Conf. 2019: 283-292 - [c115]Ben Peachey Higdon, Karim El Mokhtari, Ayse Basar:
Time-Series-Based Classification of Financial Forecasting Discrepancies. SGAI Conf. 2019: 474-479 - [i4]Sravya Polisetty, Andriy V. Miranskyy, Ayse Bener:
On Usefulness of the Deep-Learning-Based Bug Localization Models to Practitioners. CoRR abs/1907.08588 (2019) - 2018
- [j44]Hongyu Zhang, Andriy V. Miranskyy, Ayse Basar Bener:
Editorial: Special Section on Best Papers of PROMISE 2016. Inf. Softw. Technol. 95: 295 (2018) - [j43]Shirin Akbarinasaji, Bora Caglayan, Ayse Bener:
Predicting bug-fixing time: A replication study using an open source software project. J. Syst. Softw. 136: 173-186 (2018) - [j42]Andriy V. Miranskyy, Zainab Al-zanbouri, David Godwin, Ayse Basar Bener:
Database engines: Evolution of greenness. J. Softw. Evol. Process. 30(4) (2018) - [j41]Leandro L. Minku, Ayse Basar Bener, Burak Turhan:
Guest editorial: special issue on predictive models for software quality. Softw. Qual. J. 26(2): 521-523 (2018) - [j40]Mayy Habayeb, Syed Shariyar Murtaza, Andriy V. Miranskyy, Ayse Basar Bener:
On the Use of Hidden Markov Model to Predict the Time to Fix Bugs. IEEE Trans. Software Eng. 44(12): 1224-1244 (2018) - [c114]Steven Young, Tamer Abdou, Ayse Bener:
Deep Super Learner: A Deep Ensemble for Classification Problems. Canadian Conference on AI 2018: 84-95 - [c113]Saeede Sadat Asadi Kakhki, Can Kavaklioglu, Ayse Bener:
Topic Detection and Document Similarity on Financial News. Canadian Conference on AI 2018: 322-328 - [c112]Dhanya Jothimani, Can Kavaklioglu, Ayse Basar:
Financial Networks: A Study of the Toronto Stock Exchange. IEEE BigData 2018: 4684-4691 - [c111]Savas Yildirim, Dhanya Jothimani, Can Kavaklioglu, Ayse Basar:
Classification of "Hot News" for Financial Forecast Using NLP Techniques. IEEE BigData 2018: 4719-4722 - [c110]Ashok Bhowmick, Tamer Abdou, Ayse Bener:
Predictive analytics in healthcare epileptic seizure recognition. CASCON 2018: 323-330 - [c109]Steven Young, Tamer Abdou, Ayse Bener:
A Replication Study: Just-in-Time Defect Prediction with Ensemble Learning. RAISE@ICSE 2018: 42-47 - [c108]Mayy Habayeb, Syed Shariyar Murtaza, Andriy V. Miranskyy, Ayse Basar Bener:
On the use of hidden Markov model to predict the time to fix bugs. ICSE 2018: 700 - [c107]Sedef Akinli Koçak, Gülfem Isiklar Alptekin, Andriy V. Miranskyy, Ayse Bener, Enzo Cialini:
An Empirical Evaluation of Database Software Features on Energy Consumption. ICT4S 2018: 1-19 - [c106]Francis Palma, Tamer Abdou, Ayse Bener, John Maidens, Stella Liu:
An Improvement to Test Case Failure Prediction in the Context of Test Case Prioritization. PROMISE 2018: 80-89 - [c105]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 - [i3]Steven Young, Tamer Abdou, Ayse Bener:
Deep Super Learner: A Deep Ensemble for Classification Problems. CoRR abs/1803.02323 (2018) - 2017
- [j39]Rachel Harrison, Ayse Basar Bener, Çetin Meriçli, Burak Turhan:
Guest editorial: special issue on realising artificial intelligence synergies in software engineering. Autom. Softw. Eng. 24(4): 789-790 (2017) - [j38]Carlos Henrique C. Duarte, Andreas Jedlitschka, Ayse Bener:
4th International Workshop on Conducting Empirical Studies in Industry (CESI 2016): Post-workshop Report. ACM SIGSOFT Softw. Eng. Notes 42(2): 15-18 (2017) - [j37]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. J. Softw. Evol. Process. 29(4) (2017) - [j36]Agusti Solanas, Jens H. Weber, Ayse Basar Bener, Frank van der Linden, Rafael Capilla:
Recent Advances in Healthcare Software: Toward Context-Aware and Smart Solutions. IEEE Softw. 34(6): 36-40 (2017) - [j35]Ayse Tosun, Ayse Basar Bener, Shirin Akbarinasaji:
A systematic literature review on the applications of Bayesian networks to predict software quality. Softw. Qual. J. 25(1): 273-305 (2017) - [c104]Parisa Lak, Can Kavaklioglu, Mefta Sadat, Martin Petitclerc, Graham J. Wills, Andriy V. Miranskyy, Ayse Basar Bener:
A probabilistic approach for modelling user preferences in recommender systems: a case study on IBM watson analytics. CASCON 2017: 38-47 - [c103]Andreas Jedlitschka, Ayse Bener, Fabio Silva, He Zhang:
5th International Workshop on Conducting Empirical Studies in Industry (CESI 2017). CESI@ICSE 2017: 1 - [c102]Shirin Akbarinasaji, Ayse Bener, Adam Neal:
A Heuristic for Estimating the Impact of Lingering Defects: Can Debt Analogy Be Used as a Metric? WETSoM@ICSE 2017: 36-42 - [c101]Mefta Sadat, Ayse Basar Bener, Andriy V. Miranskyy:
Rediscovery datasets: connecting duplicate reports. MSR 2017: 527-530 - [c100]Ceni Babaoglu, Uzair Ahmad, Afsah Durrani, Ayse Bener:
Predictive modeling of lapse risk: An international financial services case study. SMC 2017: 16-21 - [e4]Ayse Bener, Burak Turhan, Stefan Biffl:
2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2017, Toronto, ON, Canada, November 9-10, 2017. IEEE Computer Society 2017, ISBN 978-1-5090-4039-1 [contents] - [i2]Andriy V. Miranskyy, Zainab Al-zanbouri, David Godwin, Ayse Basar Bener:
Database Engines: Evolution of Greenness. CoRR abs/1701.02344 (2017) - [i1]Mefta Sadat, Ayse Basar Bener, Andriy V. Miranskyy:
Rediscovery Datasets: Connecting Duplicate Reports. CoRR abs/1703.06337 (2017) - 2016
- [j34]Syed Shariyar Murtaza, Wael Khreich, Abdelwahab Hamou-Lhadj, Ayse Basar Bener:
Mining trends and patterns of software vulnerabilities. J. Syst. Softw. 117: 218-228 (2016) - [j33]Bora Çaglayan, Ayse Basar Bener:
Effect of developer collaboration activity on software quality in two large scale projects. J. Syst. Softw. 118: 288-296 (2016) - [j32]Ian Gorton, Ayse Basar Bener, Audris Mockus:
Software Engineering for Big Data Systems. IEEE Softw. 33(2): 32-35 (2016) - [c99]Mayy Habayeb, Behjat Soltanifar, Bora Caglayan, Ayse Basar Bener:
A Novel Point of Interest (POI) Location Based Recommender System Utilizing User Location and Web Interactions. BigDataService 2016: 121-130 - [c98]Parisa Lak, Mefta Sadat, Carl Julien Barrelet, Martin Petitclerc, Andriy V. Miranskyy, Craig Statchuk, Ayse Basar Bener:
Preliminary investigation on user interaction with IBM watson analytics. CASCON 2016: 218-225 - [c97]Behjat Soltanifar, Atakan Erdem, Ayse Bener:
Predicting Defectiveness of Software Patches. ESEM 2016: 22:1-22:10 - [c96]Tamer Abdou, Ayse Bener:
A Replication Study: Where and When Should Defects be Re-Assigned. SEAA 2016: 368-371 - [c95]Syed Shariyar Murtaza, Parisa Lak, Ayse Basar Bener, Armen Pischdotchian:
How to Effectively Train IBM Watson: Classroom Experience. HICSS 2016: 1663-1670 - [c94]Jeffrey C. Carver, Morgan Burcham, Sedef Akinli Koçak, Ayse Bener, Michael Felderer, Matthias Gander, Jason King, Jouni Markkula, Markku Oivo, Clemens Sauerwein, Laurie A. Williams:
Establishing a baseline for measuring advancement in the science of security: an analysis of the 2015 IEEE security & privacy proceedings. HotSoS 2016: 38-51 - [c93]Shirin Akbarinasaji, Ayse Basar Bener, Atakan Erdem:
Measuring the principal of defect debt. RAISE@ICSE 2016: 1-7 - [c92]Syed Shariyar Murtaza, Ayse Bener, Jeremy Petch, Muhammad Mamdani:
An empirical investigation of the evaluators' scoring of vendors' responses to an RFP of a large healthcare system. SEHS@ICSE 2016: 33-38 - [c91]Shirin Akbarinasaji, Behjat Soltanifar, Bora Çaglayan, Ayse Basar Bener, Andriy V. Miranskyy, Asli Filiz, Bryan M. Kramer, Ayse Tosun:
A metric suite proposal for logical dependency. WETSoM@ICSE 2016: 57-63 - [c90]Shirin Akbarinasaji, Ayse Bener:
Adjusting the Balance Sheet by Appending Technical Debt. MTD@ICSME 2016: 36-39 - [c89]Tamer Abdou, Behjat Soltanifar, Ayse Bener, Adam Neal:
What is the Cause for a Defect to be Re-Assigned? ICSME 2016: 502-508 - [c88]Behjat Soltanifar, Shirin Akbarinasaji, Bora Caglayan, Ayse Basar Bener, Asli Filiz, Bryan M. Kramer:
Software Analytics in Practice: A Defect Prediction Model Using Code Smells. IDEAS 2016: 148-155 - [c87]Soroosh Nalchigar, Ingmar Weber, Parisa Lak, Ayse Bener:
A Large-Scale Study of Online Shopping Behavior. IDEAS 2016: 290-295 - [c86]Carl Julien Barrelet, Sebnem Sahin Kuzulugil, Ayse Basar Bener:
The Twitter Bullishness Index: A Social Media Analytics Indicator for the Stock Market. IDEAS 2016: 394-395 - [c85]Parisa Lak, Ceni Babaoglu, Ayse Basar Bener, Pawel Pralat:
News Article Position Recommendation Based on the Analysis of Article's Content - Time Matters. CBRecSys@RecSys 2016: 11-14 - [c84]Tamer Abdou, Atakan Erdem, Ayse Bener, Adam Neal:
A replication study: mining a proprietary temporal defect dataset. SWAN@SIGSOFT FSE 2016: 15-21 - [p4]Ayse Bener, Burak Turhan, Ayse Tosun, Bora Caglayan, Ekrem Kocaguneli:
A success story in applying data science in practice. Perspectives on Data Science for Software Engineering 2016: 85-90 - [p3]Ayse Bener, Ayse Tosun:
If it is software engineering, it is (probably) a Bayesian factor. Perspectives on Data Science for Software Engineering 2016: 187-191 - 2015
- [j31]Bora Caglayan, Ayse Tosun Misirli, Ayse Basar Bener, Andriy V. Miranskyy:
Predicting defective modules in different test phases. Softw. Qual. J. 23(2): 205-227 (2015) - [j30]Gul Calikli, Ayse Bener:
Empirical analysis of factors affecting confirmation bias levels of software engineers. Softw. Qual. J. 23(4): 695-722 (2015) - [c83]Bora Caglayan, Burak Turhan, Ayse Basar Bener, Mayy Habayeb, Andriy V. Miranskyy, Enzo Cialini:
Merits of Organizational Metrics in Defect Prediction: An Industrial Replication. ICSE (2) 2015: 89-98 - [c82]Burak Turhan, Ayse Basar Bener, Rachel Harrison, Andriy V. Miranskyy, Çetin Meriçli, Leandro L. Minku:
4th International Workshop on Realizing AI Synergies in Software Engineering (RAISE 2015). ICSE (2) 2015: 991-992 - [c81]Parisa Lak, Akin Kocak, Pawel Pralat, Ayse Bener, Akram Samarikhalaj:
Towards dynamic pricing for digital billboard advertising network in smart cities. ISC2 2015: 1-6 - [c80]Mayy Habayeb, Andriy V. Miranskyy, Syed Shariyar Murtaza, Leotis Buchanan, Ayse Bener:
The Firefox Temporal Defect Dataset. MSR 2015: 498-501 - [c79]Sedef Akinli Koçak, Gülfem Isiklar Alptekin, Ayse Basar Bener:
Integrating Environmental Sustainability in Software Product Quality. RE4SuSy@RE 2015: 17-24 - [c78]Sedef Akinli Koçak, Gülfem Isiklar Alptekin, Ayse Basar Bener:
Bir Yazılımın Çevre ve Kalite Açısından Değerlendirilmesi için Önerilmiş Karar Alma Modeli. UYMS 2015 - [p2]