team

Hayk Aslanyan

Ph.D. in Physical and Mathematical Sciences, Associate Professor.

About

Information on education and professional experience

2013-present - Senior researcher, team leader, CAST (Center of Advanced Software Technologies, former SPLab).
2016-present - Associate professor. System Programming Department, Institute of Mathematics and Informatics, Russian - Armenian University.
2019 - Ph.D. in Physical and Mathematical Sciences, "Development of static analysis methods for detecting defects in program executable code"}, Ivannikov Institute for System Programming of the Russian Academy of Sciences.
2016 – 2019 - Postgraduate education, Russian-Armenian University, Mathematical and software development of computing machines, complexes, systems and networks.
2014 – 2016 - Master’s Degree, Yerevan State University, Informatics and applied mathematics.
2010 – 2014 - Bachelor's degree, Yerevan State University, Informatics and applied Mathematics.

Patents

  1. LibraryIdentifier, RU 2021665076 — issued 17.09.2021.
  2. ISP Genes, RU 2020663670 — issued 01.10.2020.
  3. patchAnalysis, RU 2019661049 — issued 16.08.2019.
  4. BinSide, RU 2019660611 — issued 09.08.2019.
  5. BINCCD, RU 2019661048 — issued 01.08.2019.

Scientific interests

  • Code Analysis
  • Error Detection

List of publications

  • 1. “Automatic unit-test generation based on symbolic execution,” in 2026 6th International Conference on Electrical, Computer and Energy Technologies (ICECET), 2026, pp. 1–5. doi: 10.1109/ICECET65726.2026.11632856
  • 2. “Assessing software weakness detection capabilities: An empirical study of ikos,” in 2026 28th International Conference on Advanced Communications Technology (ICACT), 2026, pp. 97–101. doi: 10.23919/ICACT68090.2026.11431352
  • 3. “Autotuning function-level compiler optimizations for performance improvement,” in 2026 6th International Conference on Electrical, Computer and Energy Technologies (ICECET), 2026, pp. 1–6. doi: 10.1109/ICECET65726.2026.11633097
  • 4. “Symbolic execution for control flow path feasibility,” in 2026 28th International Conference on Advanced Communications Technology (ICACT), 2026, pp. 92–96. doi: 10.23919/ICACT68090.2026.11431363
  • 5. “Accurate code fragment clone detection and its application in identifying known CVE clones,” International Journal of Information Security, 2025. doi: 10.1007/s10207-024-00968-z
  • 6. “Method for identifying changes between program versions,” in 2025 35th International Conference on Computer Theory and Applications (ICCTA), 2025, pp. 107–112. doi: 10.1109/ICCTA68914.2025.11520031
  • 7. “Automatic recognition and replacement of cyclic redundancy checks for program optimization,” IEEE Access, 2024. doi: 10.1109/ACCESS.2024.3518953
  • 8. “Combining static analysis with directed symbolic execution for scalable and accurate memory leak detection,” IEEE Access, 2024. doi: 10.1109/ACCESS.2024.3409838
  • 9. “Static analysis methods for memory leak detection: A survey,” 2022 Ivannikov Memorial Workshop (IVMEM), 2022. doi: 10.1109/IVMEM57067.2022.9983955
  • 10. “A method to evaluate binary code comparison tools,” 2021 Ivannikov Memorial Workshop (IVMEM), 2021. doi: 10.1109/IVMEM53963.2021.00006
  • 11. “Bin2Source: Matching binary to source code,” 2021 Ivannikov Ispras Open Conference (ISPRAS), 2021. doi: 10.1109/ISPRAS53967.2021.00006
  • 12. “Binside static analysis framework for defects detection in binary code,” 2020 Ivannikov Memorial Workshop (IVMEM), 2020. doi: 10.1109/IVMEM51402.2020.00007
  • 13. “GENES ISP: Code analysis platform,” 2020 Ivannikov Ispras Open Conference (ISPRAS), 2020. doi: 10.1109/ISPRAS51486.2020.00012
  • 14. “Analysis of program patches nature and searching for unpatched code fragments,” 2019 Ivannikov Memorial Workshop (IVMEM), 2019. doi: 10.1109/IVMEM.2019.00014
  • 15. Scalable framework for accurate binary code comparison,” 2017 Ivannikov ISPRAS Open Conference (ISPRAS), 2017. doi: 10.1109/ISPRAS.2017.00013

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