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Website Development for Advertisements for Rental and Sale of Real Estate

The purpose of the work is to develop a website for real estate agents and potential buyers, with the ability to publish advertisements for rental and sale of various properties. The objective of the work is to show the knowledge and skills that were acquired through the studies in the TTI (Transport and Telecommunication Institute).In this work were used the following methods:1. Analyzation of the subject area Real Estate;2. Analyzation of existing analogs;3. Design and development of data base, data access, business service, client, and server parts of the web application;4. Quality control.As the result of the work were made the web application for real estate agents and potential buyers was made, where the users can read the description, upload, modify and delete the advertisements. Was created the authentication on the website. Was created the data base of the website to store all of the information about advertisements and users.As the conclusion of the work all of the functional requirements for the website were made, full development cycle of the project was utilized and all of the errors that were raised during the work were fixed.

Author: Aleks Eglītis

Supervisor: Karina Kostjkina

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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COMPARATIVE ANALYSIS OF LLM-BASED APPROACHES FOR SQL GENERATION

The rapid development of Large Language Models has unlocked opportunities for restructuring software development processes in general as well as in such cases as converting natural language into SQL queries. This study seeks to experimentally evaluate the effects of four LLM-based methods on the efficiency and quality of SQL generation. Evaluation is being held based on following metrics: Correctness, Completeness and Consistency. Studied LLM-based SQL generation methods include Specific LLMs tailored for SQL code generation like SQL Coder frameworks for generating SQL code (Vanna.ai, 2023; Llamaindex, 2023) and Multi agent collaborative networks for transforming language into SQL.The research utilizes a mix of literature review case studies and simulations. It offers a comprehensive review of the advancements in LLM-driven SQL generation encompassing concepts, technologies, methodologies, strengths, limitations, and ethical considerations.This research successfully bridges the gap between theoretical foundations and practical application of AI-augmented approaches while promoting the integration of LLM-based SQL generation, into automated software development processes.

Author: Maksim Ilin

Supervisor: Dmitry Pavlyuk

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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