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Автоматический анализ связанности в программной системе

выпускная квалификационная работа магистра

Автоматический анализ связанности в программной системе

Abstract

В данной работе изложена сущность подхода к созданию программы для автоматического определения связанности компонентов в приложениях. Определено понятие связанности, описаны её типы, метрики для её оценки, а также паттерны проектирования для её снижения. Проведен анализ существующих систем для автоматического анализа связанности. Изучена технология статического анализа исходного кода приложений. Разработана конкретная программная реализация приложения для автоматического определения связанности, основанная на статическом анализе исходного кода приложений, с применением алгоритма HITS для расчета связанности. Проведен анализ связанности приложений с открытым исходным кодом.

This work aims to consider the basis of creation of a program for the automatic coupling analysis of applications. It was described the term of coupling itself, its types, metrics and design patterns used in order to reduce coupling. The work investigates current software for the automatic coupling analysis and describes the approach of static analysis of source code of applications as one of the main methods used in this software. As a result of this work the application for the automatic coupling analysis was created. The application is based on the static analysis and uses HITS algorithm for the coupling evaluation. The program was used to assess coupling of open-source software.

Keywords

Программирования языки, static analysis, Кодирование, связанность, Алгоритмы, статический анализ, coupling, Вычислительные машины электронные персональные

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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