OPTIMISATION OF THE PROCESS OF SEARCHING FOR MEMORY SEGMENTS: MATHEMATICAL MODELLING AND EXPERIMENTAL EVALUATION OF THE COMPLETENESS OF INFORMATION CONTENT WITH FIXED MEMORY VOLUMES

The paper investigates the problem of excessive use of RAM in software systems, in particular when storing data in the form of System.Byte[] arrays. In conditions of limited resources and high loads, there is a need for efficient use of available memory without involving additional computing power. The paper proposes a mathematical model based on the analysis of memory snapshots and a methodology for determining arrays with low information density that are candidates for compression. To reduce the amount of memory occupied, the LZ4 algorithm is used, which ensures the preservation of information content while reducing the physical size of arrays. The study was implemented on the .NET platform using the ClrMD library for software analysis of memory snapshots. A series of experiments on snapshots of industrial systems have been conducted to confirm the effectiveness of the proposed approach: reducing the memory size by up to 45% for individual arrays without data loss. The results indicate the feasibility of implementing such solutions to improve system performance and reduce infrastructure costs. The scientific contribution is the development of a new metric for evaluating compression efficiency and a recommendation system for detecting excessive memory consumption in managed runtime environments.