emacsway-log: Software Design, Clean Architecture, DDD, Microservice Architecture, Distributed Systems, XP, Agile, etc. @emacsway_log Telegram 频道

emacsway-log: Software Design, Clean Architecture, DDD, Microservice Architecture, Distributed Systems, XP, Agile, etc.

emacsway-log: Software Design, Clean Architecture, DDD, Microservice Architecture, Distributed Systems, XP, Agile, etc.
Software Design, Clean Architecture, DDD, Microservice Architecture, Distributed Systems, Extreme Programming, SDLC, Agile, etc.

Chat: https://t.me/emacsway_chat

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Persistence: https://dckms.github.io/system-architecture/
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最后更新于 23.03.2025 17:45

Exploring Modern Software Design Principles

In today’s ever-evolving technological landscape, software design principles play a crucial role in ensuring that applications are robust, scalable, and maintainable. The advent of complex systems has necessitated a fresh approach to software engineering, leading to the emergence of paradigms such as Clean Architecture, Domain-Driven Design (DDD), and Microservice Architecture. These methodologies are not mere trends; they signify a shift towards creating software that not only meets the functional requirements but is also adaptable to change, which is vital in a fast-paced digital world. Software development practices such as Agile and Extreme Programming (XP) further complement these design philosophies, fostering collaboration and iterative progress. With intricate distributed systems becoming commonplace, understanding these concepts is essential for modern developers and organizations aiming to deliver high-quality software solutions that stand the test of time.

What is Clean Architecture and why is it important?

Clean Architecture is a software design philosophy that emphasizes separation of concerns, making it easier to manage complexity. It suggests that each layer of the application should be independent of the others, allowing developers to modify or replace layers without impacting the entire system. This modularity is essential for ensuring the longevity and adaptability of the software as requirements evolve.

Moreover, Clean Architecture promotes testability, as each component can be tested in isolation. This reduces the risk of introducing bugs when making changes to the codebase. Additionally, by enforcing boundaries between different layers of the application, developers can better adhere to software engineering best practices, resulting in cleaner, more maintainable code.

What is Domain-Driven Design (DDD) and how does it differ from traditional approaches?

Domain-Driven Design (DDD) is an approach to software development that prioritizes the domain or business logic in the design of the application. It encourages collaboration between technical and non-technical stakeholders to create a model that accurately reflects business processes. Unlike traditional approaches that may focus on technical aspects, DDD emphasizes understanding the domain and building software that aligns closely with business needs.

DDD also introduces concepts such as bounded contexts and aggregates, which help manage complexity in large systems. By defining clear boundaries within which specific models apply, teams can work more effectively without stepping on each other's toes, thus reducing conflicts and enhancing productivity.

How does Microservice Architecture benefit software development?

Microservice Architecture is an architectural style that structures an application as a collection of small, autonomous services. Each service runs independently and can be developed, deployed, and scaled individually, allowing for greater flexibility in the development process. This approach is especially beneficial for large applications where teams can work concurrently on different services without interference, leading to faster delivery of features.

Furthermore, microservices facilitate technological diversity as different services can be built using different programming languages or frameworks based on their specific needs. This adaptability not only enhances performance but also allows teams to leverage the latest technologies without overhauling the entire system.

What role do Agile methodologies play in modern software development?

Agile methodologies advocate for an iterative and incremental approach to software development, emphasizing collaboration, customer feedback, and flexibility. Agile allows development teams to respond to changes quickly, which is crucial in today’s fast-paced environments where requirements can shift unexpectedly. Teams work in short cycles, known as sprints, to deliver small increments of functionality, thereby creating opportunities for regular feedback and adjustment.

Additionally, Agile promotes a culture of transparency and communication, encouraging team members to collaborate closely. This engagement helps identify potential issues early in the development process, leading to improved quality and customer satisfaction as the end product is continuously refined based on stakeholder input.

What is Extreme Programming (XP) and how does it enhance software quality?

Extreme Programming (XP) is a software development methodology that aims to produce higher-quality software and higher quality of life for the development team. It encompasses practices such as pair programming, test-driven development (TDD), and continuous integration. By having two programmers work together at one workstation, teams can produce better code through real-time review and knowledge sharing.

XP also focuses on frequent releases in short development cycles, which helps ensure that the software meets user needs and can adapt quickly to changes. The emphasis on TDD ensures that testing is integrated into the development process, leading to fewer bugs and ensuring that the software remains reliable as it evolves over time.

emacsway-log: Software Design, Clean Architecture, DDD, Microservice Architecture, Distributed Systems, XP, Agile, etc. Telegram 频道

Are you a software enthusiast looking to delve deeper into the world of software design, clean architecture, domain-driven design (DDD), microservice architecture, distributed systems, extreme programming (XP), and agile methodologies? Look no further than Emacsway-log! This Telegram channel is a treasure trove of valuable information and discussions on various aspects of software development.

Emacsway-log covers a wide range of topics, including software design principles, best practices in clean architecture, strategies for implementing DDD, the ins and outs of microservice architecture, building and managing distributed systems, the benefits of XP, and the latest trends in agile development. Whether you are a seasoned software developer or just starting your journey in the tech industry, this channel offers valuable insights and resources to help you stay ahead in the ever-evolving world of software engineering.

Join the Emacsway-log community today and engage in stimulating conversations with like-minded professionals who share your passion for software craftsmanship. Explore the chat group for real-time discussions, seek expert advice through the consulting service provided by @born_of_granite_bot, and dive into the world of software architecture and system design through the informative resources available at https://dckms.github.io/system-architecture/. Embrace the Emacsway and elevate your software development skills to new heights!

emacsway-log: Software Design, Clean Architecture, DDD, Microservice Architecture, Distributed Systems, XP, Agile, etc. 最新帖子

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https://research.google/pubs/what-improves-developer-productivity-at-google-code-quality/

22 Mar, 06:50
647
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Как я делаю fitness-functions для микросервисов. Продолжение. Начало здесь.

По хуку before_scenario() (или before_tag()) создается дамп изначального состояния БД (если он не был создан ранее) утилитой pg_dump в многопоточном режиме, с использованием аргументов:
--jobs=n, где n - количество ядер процессора, len(os.sched_getaffinity(0));
--format=directory (требуется для параллельного дампа);
--clean;

Composition Pattern отлично подошел для создания дампов баз данных нескольких микросервисов.

При необходимости, созданная директория с дампом архивируется и сохраняется в хранилище (тут есть разные варианты сохранения дампов между запусками тестов, от монтирования удаленной директории до отправки архива в S3).

По хуку after_scenario() (или after_tag()) дамп изначального состояния БД восстанавливается утилитой pg_restore так же в многопоточном режиме, с использованием аргументов:
--jobs=n
--clean

Некоторые коллеги из других компаний восстанавливают БД на уровне файлов PGDATA тестируемого сервиса. Работает быстрее, но менее универсально.

При исполенении шага "Given SUT with 10000000 objects" проверяется наличие актуального предзаполненного дампа БД для указанного объема данных и производится или его восстановление, или его создание путем генерации фэйковых данных. С целью сокращения времени генерации, я генерирую данные непосредственно в БД, хотя можно и через Public API сервиса. Для генерации используется собственный performance framework, позволяющий воспроизвести селективность индексов целевой системы. Коробочные решения мне неизвестны, но за основу можно взять:
- https://hypothesis.readthedocs.io/en/latest/strategies.html
- https://github.com/litestar-org/polyfactory

На следующем шаге создаем нагрузку. Я использую тот же собственный performance framework, который автоматически определяет создавать ли зависимый объект или реиспользовать ранее созданный в соответствии с заданной вероятностной распределенностью. Коробочные решения мне опять же неизвестны, но за основу можно взять:
- https://schemathesis.readthedocs.io/

Если используется JS (например, при использовании K6), то имеет смысл обратить внимание на:
- https://dredd.org/

Для изоляции сервиса можно использовать Mountebank, WireMock или Mockintosh (на Python), pytest-httpserver. На PyPi достаточно много реализаций mock-серверов. Вплоть до стандартного http.server. Некоторые из них позволяют генерировать данные на основе OpenAPI спецификации. На JS имеет смысл посмотреть в сторону Prism. См. так же OpenAPI Generator (docs), Swagger Codegen (HOWTO).

Для относительно небольших систем нагрузочный движок можно не использовать вообще, ограничившись простой многопоточностью multiprocessing.Pool.map().

В некоторых случаях подойдет минималистичный нагрузочный движок molotov.

Для крупных систем потребуется распределенный нагрузочный движок. Locust можно запускать как библиотеку (пример). О том, как подружить Locust и asyncio, см. здесь. K6, Gatling, JMeter можно запускать через субпроцессинг.

Результат каждого запроса записывается в Graphite или в Prometheus для детализированного анализа.

Используя Gherkin, удалось совместить хранение спецификаций как функциональных, так и нефункциональных требований. При этом функциональные требования в Gherkin формате очень хорошо ложатся на EventStorming диаграмму.

[UPDATE]: см. также:
- https://allurereport.org/docs/behave/
- https://allurereport.org/docs/pytestbdd/

13 Mar, 16:12
1,617
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🔹https://dialog.guide/ - Как подготовить и принять
бизнес-решение в команде
. Библиотека алгоритмов.

Thanks to @vec650

01 Mar, 11:59
2,001
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ℹ️ В прошлом году неожиданно обновилось до 4 версии руководство по программной инженерии SWEBOK (The Guide to the Software Engineering Body of Knowledge) Предыдущая версия руководства была выпушена в 2014, а первая версия появилась в 2004.

🆕 Еще более неожиданным является то, что к 15 областям знаний, описанным в SWEBOK ранее, добавились три новых: Software Engineering Operations, Software Security и (сюрприз-сюрприз) Software Architecture. При этом область знаний Software Design, существовавшая в предыдущей версии, тоже сохранилась.

⬇️ Загрузить руководство можно по ссылке выше. Русскоязычный обзор новой версии SWEBOK можно почитать в журнале Открытые системы. СУБД

26 Feb, 11:01
2,063