ECONOMIC AND TECHNOLOGICAL EFFICIENCY ISSUES IN THESOFTWARE DEVELOPMENT PROCESS FOR THE OPERATION OFPROGRAMMING DEVICES
The article discusses the key issues related to the economic and technological efficiency of software development involving programmable devices. It highlights the fundamental factors that influence the effectiveness of programming platforms and tools, considering both technological advancements and economic implications. As software development becomes more complex, optimizing resources and minimizing costs while maintaining high performance has become increasingly important. The developed model provides software developers with a structured approach to reducing development time, lowering costs, and improving overall system reliability. One of the critical aspects covered in this study is the use of the Java Native Interface (JNI), which facilitates seamless integration of C++-written code within Java-based applications. This approach allows developers to leverage the advantages of both languages without requiring in-depth knowledge of low-level hardware interactions, simplifying the development process. From an economic standpoint, this methodology significantly reduces initial investment costs and enhances the competitiveness of software solutions in the market. Furthermore, by streamlining development workflows, companies can lower operational expenses while ensuring better system performance. The proposed solution is highly adaptable and can be applied across various industries, including industrial automation, electronic device management, embedded systems, and high-performance computing. It opens new possibilities for software engineers to create scalable, efficient, and cost-effective solutions while maintaining flexibility across different technological platforms.
Authors
- V. Khachatryan (ORCID: https://orcid.org/0000-0003-2567-2930)
- Hayk Gevorgyan
- Margarita YEGHIAZARYAN
Publication Details
- Journal
- ALTERNATIVE
- Published
- 2025-01-01
- DOI
- https://doi.org/10.55528/18292828-2025.1-45
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00