Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Technological Means for Automatic Programs Construction in LuNA System. / Malyshkin, Victor; Perepelkin, Vladislav; Parfenov, Denis et al.
Parallel Computing Technologies. ed. / Victor Malyshkin. Springer, 2026. p. 105-123 8 (Lecture Notes in Computer Science; Vol. 16185).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Technological Means for Automatic Programs Construction in LuNA System
AU - Malyshkin, Victor
AU - Perepelkin, Vladislav
AU - Parfenov, Denis
AU - Sinyukov, Valeriy
AU - Spirin, Vitaly
AU - Ivanchenko, Danila
AU - Nushtaev, Yuri
N1 - Conference code: 18
PY - 2025/10/1
Y1 - 2025/10/1
N2 - Automation of high-performance programs construction is a relevant and challenging problem. Automatic construction of programs that are suitable (e.g. efficient-enough) for practical use within reasonable time critically depends on peculiarities of the target subject domain. Because of this dependency general approaches fail, explaining the diversity of languages, systems and tools developed for automating program construction in specific subject domains. To overcome these limitations, the active knowledge concept, a methodology for automatic program synthesis, proposes employing an active knowledge base—a machine-oriented formal description of a subject domain that captures its peculiarities. Using an active knowledge base significantly reduces the complexity of program construction automation while improving the quality of the resulting programs. Implementation of the active knowledge concept ideas in practice raises a number of technological issues. In the paper we present how we resolve them within the framework of the LuNA system for automatic program construction, which is based on the active knowledge concept.
AB - Automation of high-performance programs construction is a relevant and challenging problem. Automatic construction of programs that are suitable (e.g. efficient-enough) for practical use within reasonable time critically depends on peculiarities of the target subject domain. Because of this dependency general approaches fail, explaining the diversity of languages, systems and tools developed for automating program construction in specific subject domains. To overcome these limitations, the active knowledge concept, a methodology for automatic program synthesis, proposes employing an active knowledge base—a machine-oriented formal description of a subject domain that captures its peculiarities. Using an active knowledge base significantly reduces the complexity of program construction automation while improving the quality of the resulting programs. Implementation of the active knowledge concept ideas in practice raises a number of technological issues. In the paper we present how we resolve them within the framework of the LuNA system for automatic program construction, which is based on the active knowledge concept.
UR - https://www.scopus.com/pages/publications/105019533486
UR - https://www.mendeley.com/catalogue/793ea80f-bc4c-3b6b-9f3d-a7f3da45a656/
U2 - 10.1007/978-3-032-06751-7_8
DO - 10.1007/978-3-032-06751-7_8
M3 - Conference contribution
SN - 978-3-032-06750-0
T3 - Lecture Notes in Computer Science
SP - 105
EP - 123
BT - Parallel Computing Technologies
A2 - Malyshkin, Victor
PB - Springer
T2 - 18th International Conference on Parallel Computing Technologies
Y2 - 6 October 2025 through 10 October 2025
ER -
ID: 71479425