Associate Professor
Department of Computer Science
Ryerson University

LinkedIn : profile


Important I am currently taking on undergraduate and graduate students with interests or expertise in my research areas. If you would like to work with me, please make an appropriate note in your application to the graduate school; see Yeates School of Graduate Studies web site for detailed information about the application process. In addition, please contact me directly. Note that funding is available to exceptionally qualified candidates.

Research Interests

My main research interest lies in the area of quantifying and mitigating risks (in the broadest sense) in Software Engineering, focusing on large-scale software systems, especially those that process and analyze Big Data. Examples of risks are numerous:

  • Related to very large databases for Big Data that have been tested improperly, resulting in defect escapes and unplanned outages;

  • Tied to non-scalable algorithms for which it is impossible to determine a root cause of system failure fast enough to preclude prolonged outages and customer dissatisfaction;

  • Connected with requirements creeping in late in the development cycle, overrunning original budget and schedule;

  • Linked to spikes in the number of defects rediscovered by clients, overloading support and maintenance personnel.

In our work, we leverage a plethora of “tools” ranging from data mining, machine learning (including deep learning), simulation, and information theory, to blockchain, Quantum, High Performance Computing, and Cloud computing.

Research Partners & Funding Agencies

Selected Publications

You can find a complete list of publications on DBLP. A selected list of papers is given below.

  • W. Pourmajidi, L. Zhang, J. Steinbacher, T. Erwin, A. Miranskyy, Immutable Log Storage as a Service, in Proceedings of the International Conference on Software Engineering (ICSE’19), accepted

  • A. Miranskyy, L. Zhang, On Testing Quantum Programs, in Proceedings of the International Conference on Software Engineering (ICSE’19), accepted, preprint

  • L. Zhang, D. Lai, A. Miranskyy, The Impact of Position Errors on Crowd Simulation, Simulation Modelling Practice and Theory, accepted : link, preprint

  • W. Pourmajidi, A. Miranskyy, Logchain: Blockchain-assisted Log Storage, IEEE Cloud 2018, accepted : preprint

  • S. Hoque, A.Miranskyy, Online and Offline Analysis of Streaming Data, International Conference On Software Architecture (ICSA 2018), accepted : preprint

  • S. Hoque, A.Miranskyy, Architecture for Analysis of Streaming Data, 6th IEEE International Conference on Cloud Engineering (IC2E’18), accepted : preprint

  • M. Sultan, A.Miranskyy, Ordering Stakeholder Viewpoint Concerns for Holistic Enterprise Architecture, 33rd ACM Symposium on Applied Computing (SAC’18), accepted

  • M. Habayeb, S.S. Murtaza, A. Miranskyy, A. Bener, On the Use of Hidden Markov Model to Predict the Time to Fix Bugs, IEEE Transactions on Software Engineering, accepted : link. Presented at the International Conference on Software Engineering (ICSE’18), journal-first track.

  • W. Pourmajidi, T. Erwin, J. Steinbacher, A.Miranskyy, On Challenges of Cloud Monitoring, 2017 Conference of the Center for Advanced Studies on Collaborative Research: Meeting of Minds (CASCON’17), 2017, 259-265 : link

  • A.V. Miranskyy, Z. Al-zanbouri, D. Godwin, and A.B. Bener, Database Engines: Evolution of Greenness, Journal of Software: Evolution and Process, accepted : link, preprint

  • M. Sadat, A. Bener, A. Miranskyy, Rediscovery Datasets: Connecting Duplicate Reports, 14th International Conference on Mining Software Repositories (MSR’17), 2017, 527-530 : link, preprint, dataset

  • D. Curro, K.G. Derpanis, and A.V. Miranskyy Building Usage Profiles Using Deep Neural Nets, in Proceedings of the International Conference on Software Engineering (ICSE’17), 2017, 43-46 : link, preprint, dataset

  • A.V. Miranskyy, W. Hamou-Lhadj, E. Cialini, and A. Larsson, Operational-Log Analysis for Big Data Systems: Challenges and Solutions, IEEE Software, 33, 2, 2016, 52-59 : link

  • N.H. Madhavji, A. Miranskyy, and K. Kontogiannis, Big Picture of Big Data Software Engineering, in Proceedings of the 1st International Workshop on Big Data Software Engineering (BIGDSE), 2015, 11-14 : link, preprint

  • M. Sultan and A.V. Miranskyy, Ordering Interrogative Questions for Effective Requirements Engineering: The W6H Pattern, In Proceedings of the 5th International Workshop on Requirements Patterns (RePa’15), 2015, 1-8 : link, preprint

  • M. Habayeb, A. Miranskyy, S.S. Murtaza, L. Buchanan, and A. Bener, The Firefox Temporal Defect Dataset, in Proceedings of the 12th Working Conference on Mining Software Repositories (MSR’15), 2015, : link, preprint, dataset

  • B. Caglayan, B. Turhan, A. Bener, M. Habayeb, A. Miranskyy, and E. Cialini, Merits of Organizational Metrics in Defect Prediction: An Industrial Replication, in Proceedings of the International Conference on Software Engineering (ICSE’15), 2015 : link, preprint

  • A.B. Bener, M. Morisio, and A. Miranskyy, Green Software: Guest Editors’ Introduction, IEEE Software, 31, 3, (2014), 36-39 : link

  • B. Caglayan, A. Bener, and A. Miranskyy, Emergence of Developer Teams In The Collaboration Network, in Proceedings of the Sixth International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE 2013) : link

  • A.V. Miranskyy, S.A. Kocak, E. Cialini, and A.B. Bener, DB2 Data Compression Feature: Energy Saver, IBM developerWorks (2013) : link

  • S.A. Kocak, A.V. Miranskyy, G.I. Alptekin, A.B. Bener, and E. Cialini, The Impact of Improving Software Functionality on Environmental Sustainability, in Proceedings of the First International Conference on Information and Communication Technologies for Sustainability (ICT4S), (2012), 95-100 : link

  • B. Caglayan, A.T. Misirli, A. Miranskyy, B. Turhan, and A. Bener. Factors characterizing reopened issues: a case study, in Proceedings of the 8th International Conference on Predictive Models in Software Engineering (PROMISE '12), (2012), 1-10 : link

  • A.V. Miranskyy, M. Davison, M. Reesor, and S.S. Murtaza: Using entropy measures for comparison of software traces, Information Sciences, 203, no. 25, (2012), 59-72 : link

  • E. Cialini and A.V. Miranskyy, Scaling of DB2 for Linux, UNIX, and Windows memory-related configuration parameters on a test system, IBM developerWorks (2011): link

  • C. Taylor, A.V. Miranskyy and N.H. Madhavji, Request implementation ratio as an indicator for prioritization bias, in Proceedings of Fifth International Workshop on Software Product Management (IWSPM), 2011, 3-6 : link

  • B. Caglayan, A. Tosun, A.V. Miranskyy, A. Bener, and N. Ruffolo. Usage of multiple prediction models based on defect categories. In Proceedings of the 6th International Conference on Predictive Models in Software Engineering (PROMISE '10). Article 8, (2010), 9 pages : link

  • A.V. Miranskyy, E. Cialini, and D. Godwin. Selection of customers for operational and usage profiling, in Proceedings of the Second International Workshop on Testing Database Systems (DBTest '09). Article 7, (2009), 6 pages : link

  • A.V. Miranskyy, N.H. Madhavji, M.S. Gittens, M. Davison, M. Wilding, and D. Godwin, C.A. Taylor, SIFT: A Scalable Iterative-Unfolding Technique for Filtering Execution Traces, in Proceedings of the 2008 Conference of the Center For Advanced Studies on Collaborative Research: Meeting of Minds (CASCON '08), (2008), 15 pages : link

Patents & IP

  • A.V. Miranskyy and E. Cialini, Calculation of the amount of changes made to a software source code at the function and block level of granularity, IPCOM 000225653D, (2013) (IP publication) : link

  • A.V. Miranskyy, E. Cialini, and D. Godwin, Selection of Customers for Operational and Usage Profiling, IPCOM 000203574D, (2011) (IP publication) : link

  • A.V. Miranskyy, D. Godwin, E. Cialini, A technique for estimation of confidence interval for probability of defect rediscovery, United States Patent & Trademark Office’s Patent # 8392763, (2009) : link

  • A.V. Miranskyy and D. Godwin, Trend change analysis using inflection points detection, IPCOM 000177081D, (2008) (IP publication) : link

  • M. Davison, M.S. Gittens, D. Godwin, N.H. Madhavji, A. Miranskyy, and M. Wilding, Computer Software Test Coverage Analysis, United States Patent & Trademark Office’s Patent # 7793267, (2006) : link


  • Rediscovery Datasets: Connecting Duplicate Reports of Apache, Eclipse, and KDE. external repository (180MB)

  • User-Profiling Dataset. external repository (32GB)

  • The Firefox Temporal Defect Dataset (FTDD). zip (10MB)


  • Models, Techniques, and Metrics for Managing Risk in Software Engineering, Ph.D. Dissertation, Applied Mathematics, Scientific Computing, University of Western Ontario, London, Canada, 2011 : pdf

  • Pricing Defaultable Bonds and Options in a CIR Risk & Default Framework, M.Sc. Dissertation, Applied Mathematics, Quantitative Finance, University of Western Ontario, London, Canada, 2004


Current Group Members

  • Janusan Baskararajah, MSc candidate

  • Mohammad Saiful Islam, MSc candidate

  • Sheik Mamun, PhD candidate

  • William Pourmajidi, PhD candidate

  • Iwona Sokalska, PhD candidate

  • Mujahid Sultan, PhD candidate

  • Lei Zhang, Post-doctoral researcher


  • Kristie House-Senapati, MSc (DS), 2019

    • Thesis Title: The Use of Recommender Systems for Defect Rediscoveries

  • Iwona Sokalska, MSc (DS), 2019

    • Thesis Title: Boosting Bug Localization with Visual Input and Self-Attention

  • William Pourmajidi, MSc (CS), 2018

    • Thesis Title: Scalable Blockchain-assisted Log Storage System for Cloud-generated Logs

  • Sravya Polisetty, MSc (CS), 2018

    • Thesis Title: On Empirically Examining The Effectiveness Of Deep Learning-Based Bug Localization Models

  • Sedef Akinli Kocak, PhD (ENSCIMAN), 2017

    • Dissertation Title: Software Energy Consumption Prediction Using Software Code Metrics

  • Jorge Lopez, MSc (CS), 2017

    • Thesis Title: Speeding up calibration of Latent Dirichlet Allocation model to improve topic analysis in Software Engineering

  • Muad Abu-Ata, MSc (DS), 2017

    • Project Title: Optimization of Decision Model Microsimulation in Health Care

  • Mefta Sadat, MSc (CS), 2017

    • Thesis Title: On Predicting Rediscoveries of Software Defects

  • Sokratis Tsakiltsidis, MSc (CS), 2016

    • Thesis Title: Predicting the time-to-deliver of software changes

  • Zainab Al-zanbouri, MSc (CS), 2015

    • Thesis Title: Database Engines: Evolution of Greenness

  • Mayy Habayeb, MEng (MIE), 2015

    • Thesis Title: On the Use of Hidden Markov Model to Predict the Time to Fix Bugs


  • CPS406 - Introduction to Software Engineering

  • CPS731 - Software Engineering I

  • CPS847 - Software Tools for Startups

  • CPS888 - Software Engineering

  • CP8102 & CP9102 - Computer Science Seminar

  • CP8302 - Software Metrics

  • DS8001 - Designs of Algorithms and Programming for Massive Data

Contact me

  • Email : avm <at> scs.ryerson.ca

  • LinkedIn : profile

  • Phone : +1 (416) 979-5000 ext. 7208

  • Mail :
    Department of Computer Science
    Ryerson University
    350 Victoria St.
    Toronto, Ontario, M5B 2K3