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2 days ago

INSTEAD OF WATCHING AN HOUR OF NETFLIX TONIGHT. This 60-minute Cambridge lecture by Demis Hassabis will teach you more about the future of AI than most people will learn in the next 5 years. Bookmark it and give it an hour, no matter what.

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Dr Milan Milanović

@milan_milanovic

about 1 year ago

𝗧𝗼𝗽 𝟭𝟬 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 is the process of designing the structure and behavior of a software system, which includes making decisions about components, modules, interfaces, and the system's organization. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 are essential because they provide reusable solutions to common problems in software design. They capture best practices and proven solutions for designing reliable, scalable, maintainable, and extensible software systems. There are many software architecture design patterns to know, but some of the most important ones are: 𝟭. 𝗟𝗮𝘆𝗲𝗿𝗲𝗱 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern is based on dividing the application into logical layers, where each layer has a specific responsibility and interacts with the layers above and below it. 𝟮. 𝗠𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern is based on decomposing the application into small, independent services that communicate through well-defined APIs. 𝟯. 𝗘𝘃𝗲𝗻𝘁-𝗗𝗿𝗶𝘃𝗲𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern uses events to communicate between different components or services, where events trigger actions or reactions in the system. 𝟰. 𝗦𝗽𝗮𝗰𝗲-𝗯𝗮𝘀𝗲𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (𝗦𝗕𝗔): is a software design method that centers the system's structure around the idea of "spaces," which are independent and autonomous units. 𝟱. 𝗠𝗶𝗰𝗿𝗼𝗸𝗲𝗿𝗻𝗲𝗹 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: this is an approach where the kernel provides minimal functionality and services are implemented as separate modules outside the kernel. 𝟲. 𝗣𝗲𝗲𝗿 𝘁𝗼 𝗣𝗲𝗲𝗿 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗽𝗮𝘁𝘁𝗲𝗿𝗻: this is a decentralized model where nodes in a network can act as both clients and servers, allowing for distributed sharing of resources and information without a central authority. 𝟳. 𝗖𝗹𝗼𝘂𝗱 𝗻𝗮𝘁𝗶𝘃𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: this is a pattern where applications are developed and deployed to run on cloud platforms, leveraging cloud services and infrastructure for scalability, reliability, and agility. 𝟴. 𝗖𝗤𝗥𝗦 (𝗖𝗼𝗺𝗺𝗮𝗻𝗱 𝗤𝘂𝗲𝗿𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗲𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻): This pattern separates the command and query responsibilities of an application's model, making it easier to scale and optimize the application. 𝟵. 𝗛𝗲𝘅𝗮𝗴𝗼𝗻𝗮𝗹 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern separates the application into an inner and outer layer, where the inner layer contains the business logic and the outer layer includes the interfaces with the outside world. 𝟭𝟬. 𝗖𝗹𝗲𝗮𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern emphasizes separating concerns and decoupling components, making it easier to maintain and change an application over time. #softwarearchitecture #programming #developers

milan_milanovic's tweet photo. 𝗧𝗼𝗽 𝟭𝟬 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻𝘀

𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 is the process of designing the structure and behavior of a software system, which includes making decisions about components, modules, interfaces, and the system's organization.

𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 are essential because they provide reusable solutions to common problems in software design. They capture best practices and proven solutions for designing reliable, scalable, maintainable, and extensible software systems.

There are many software architecture design patterns to know, but some of the most important ones are:

𝟭. 𝗟𝗮𝘆𝗲𝗿𝗲𝗱 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern is based on dividing the application into logical layers, where each layer has a specific responsibility and interacts with the layers above and below it.

𝟮. 𝗠𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern is based on decomposing the application into small, independent services that communicate through well-defined APIs.

𝟯. 𝗘𝘃𝗲𝗻𝘁-𝗗𝗿𝗶𝘃𝗲𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern uses events to communicate between different components or services, where events trigger actions or reactions in the system.

𝟰. 𝗦𝗽𝗮𝗰𝗲-𝗯𝗮𝘀𝗲𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (𝗦𝗕𝗔): is a software design method that centers the system's structure around the idea of "spaces," which are independent and autonomous units.

𝟱. 𝗠𝗶𝗰𝗿𝗼𝗸𝗲𝗿𝗻𝗲𝗹 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: this is an approach where the kernel provides minimal functionality and services are implemented as separate modules outside the kernel.

𝟲. 𝗣𝗲𝗲𝗿 𝘁𝗼 𝗣𝗲𝗲𝗿 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗽𝗮𝘁𝘁𝗲𝗿𝗻: this is a decentralized model where nodes in a network can act as both clients and servers, allowing for distributed sharing of resources and information without a central authority.

𝟳. 𝗖𝗹𝗼𝘂𝗱 𝗻𝗮𝘁𝗶𝘃𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: this is a pattern where applications are developed and deployed to run on cloud platforms, leveraging cloud services and infrastructure for scalability, reliability, and agility.

𝟴. 𝗖𝗤𝗥𝗦 (𝗖𝗼𝗺𝗺𝗮𝗻𝗱 𝗤𝘂𝗲𝗿𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗲𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻): This pattern separates the command and query responsibilities of an application's model, making it easier to scale and optimize the application.

𝟵. 𝗛𝗲𝘅𝗮𝗴𝗼𝗻𝗮𝗹 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern separates the application into an inner and outer layer, where the inner layer contains the business logic and the outer layer includes the interfaces with the outside world.

𝟭𝟬. 𝗖𝗹𝗲𝗮𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: This pattern emphasizes separating concerns and decoupling components, making it easier to maintain and change an application over time.

#softwarearchitecture #programming #developers

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mukulcodes retweeted

Dr Milan Milanović

@milan_milanovic

over 1 year ago

𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗣𝗮𝗽𝗲𝗿𝘀 𝗘𝘃𝗲𝗿𝘆 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗦𝗵𝗼𝘂𝗹𝗱 𝗥𝗲𝗮𝗱 We as developers need to learn new stuff, which is one of the most essential things in our professional life. This helps us build and develop new skills for the job. Yet, I found that people are not reading so many research papers on computer science. You could ask why would you do this. Well, in those papers, you will understand different computer science and software engineering concepts (depth and breadth). Most of the features you use today in your programming languages came from some of those papers, and with new papers, you can predict what will come. Here is the list of the most critical computer science papers: 𝟭. 𝗢𝗻 𝘁𝗵𝗲 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮 𝗧𝗼 𝗕𝗲 𝗨𝘀𝗲𝗱 𝗶𝗻 𝗗𝗲𝗰𝗼𝗺𝗽𝗼𝘀𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗶𝗻𝘁𝗼 𝗠𝗼𝗱𝘂𝗹𝗲𝘀 (𝟭𝟵𝟳𝟮.), 𝗗.𝗟.𝗣𝗮𝗿𝗻𝗮𝘀 In this paper, Parnas discussed modularization as a mechanism for improving a system's flexibility and comprehensibility while reducing its development time. He also discussed the criteria for decomposing systems into modules. Link: https://t.co/6VIcOaxAKJ 𝟮. 𝗔𝗻 𝗔𝘅𝗶𝗼𝗺𝗮𝘁𝗶𝗰 𝗕𝗮𝘀𝗶𝘀 𝗳𝗼𝗿 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 (𝟭𝟵𝟲𝟵.), 𝗖.𝗔.𝗥. 𝗛𝗼𝗮𝗿𝗲 In this paper, C. A. R. Hoare explores the mathematical logic underlying computer programming. Deductive reasoning should inform every program's state and output. Axioms make up deductive reasoning, and inference rules are based on this collection of axioms. Link: https://t.co/PO7rC1I5pk 𝟯. 𝗧𝗶𝗺𝗲, 𝗖𝗹𝗼𝗰𝗸𝘀, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗢𝗿𝗱𝗲𝗿𝗶𝗻𝗴 𝗼𝗳 𝗘𝘃𝗲𝗻𝘁𝘀 𝗶𝗻 𝗮 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺 (𝟭𝟵𝟳𝟴.), 𝗟. 𝗟𝗮𝗺𝗽𝗼𝗿𝘁 In the essay, Lamport discusses how humans perceive time, the necessity for a paradigm change regarding distributed systems, and the notion of incomplete ordering. Link: https://t.co/JhYFSrl6yg 𝟰. 𝗢𝘂𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗧𝗮𝗿 𝗣𝗶𝘁 (𝟮𝟬𝟬𝟲.), 𝗕. 𝗠𝗼𝘀𝗲𝗹𝗲𝘆, 𝗣. 𝗠𝗮𝗿𝗸𝘀 This paper discusses the causes and effects of complexity in software systems and approaches to understanding it. Link: https://t.co/lMI5IiKKtX 𝟱. 𝗗𝘆𝗻𝗮𝗺𝗼: 𝗔𝗺𝗮𝘇𝗼𝗻’𝘀 𝗛𝗶𝗴𝗵𝗹𝘆 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗞𝗲𝘆-𝘃𝗮𝗹𝘂𝗲 𝗦𝘁𝗼𝗿𝗲 (𝟮𝟬𝟬𝟳.), 𝗚.𝗗𝗲𝗖𝗮𝗻𝗱𝗶𝗮 𝗲𝘁 𝗮𝗹. This paper explains the design and architecture of AmazonDB, a fast NoSQL key-value database. You can learn that Dynamo is designed as a write-intensive data store, but it has limitations and scaling possibilities. Link: https://t.co/uakqVwHyTO. 𝟲. 𝗠𝗮𝗽𝗥𝗲𝗱𝘂𝗰𝗲: 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗼𝗻 𝗟𝗮𝗿𝗴𝗲 𝗖𝗹𝘂𝘀𝘁𝗲𝗿𝘀 (𝟮𝟬𝟬𝟰.), 𝗝. 𝗗𝗲𝗮𝗻, 𝗦. 𝗚𝗵𝗲𝗺𝗮𝘄𝗮𝘁 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲 The paper explains the MapReduce programming model and its implementation for processing and generating large data sets. Link: https://t.co/EvmQnDmATF 𝟳. 𝗔 𝗡𝗼𝘁𝗲 𝗢𝗻 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 (𝟭𝟵𝟵𝟰.), 𝗝. 𝗪𝗮𝗹𝗱𝗼, 𝗚. 𝗪𝘆𝗮𝗻𝘁, 𝗔. 𝗪𝗼𝗹𝗹𝗿𝗮𝘁𝗵, 𝗦. 𝗞𝗲𝗻𝗱𝗮𝗹𝗹 The authors of this study debunk an old myth that building a distributed system makes distribution visible. Link: https://t.co/lrONESHt2s 𝟴. 𝗔 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 𝘀𝘂𝗶𝘁𝗲 𝗳𝗼𝗿 𝗼𝗯𝗷𝗲𝗰𝘁-𝗼𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗱𝗲𝘀𝗶𝗴𝗻 (𝟭𝟵𝟵𝟰.), 𝗦.𝗥. 𝗖𝗵𝗶𝗱𝗮𝗺𝗯𝗲𝗿 This paper presents a new set of software metrics for OO design. Link: https://t.co/t8XNvv4ARZ. 𝟵. 𝗔 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗼𝗱𝗲𝗹 𝗼𝗳 𝗱𝗮𝘁𝗮 𝗳𝗼𝗿 𝗹𝗮𝗿𝗴𝗲 𝘀𝗵𝗮𝗿𝗲𝗱 𝗱𝗮𝘁𝗮 𝗯𝗮𝗻𝗸𝘀 (𝟭𝟵𝟲𝟵.), 𝗘. 𝗙. 𝗖𝗼𝗱𝗱 The paper addresses some of the problems with database systems at the time of its publication that the relational model solved. SQL Databases are based on this paper. https://t.co/hqTrzqxfWQ 𝟭𝟬. 𝗪𝗵𝘆 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 (𝟭𝟵𝟵𝟬.), 𝗝. 𝗛𝘂𝗴𝗵𝗲𝘀 In this paper, the authors describe the importance of functional programming where modularisation is key. Link: https://t.co/d4luxwTZQl. Bonus: "𝗛𝗼𝘄 𝘁𝗼 𝗥𝗲𝗮𝗱 𝗮 𝗣𝗮𝗽𝗲𝗿", 𝗦. 𝗞𝗲𝘀𝗵𝗮𝘃 This paper outlines a practical and efficient three-pass method for reading research papers. Link: https://t.co/3lfjvx3Dlj

milan_milanovic's tweet photo. 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗣𝗮𝗽𝗲𝗿𝘀 𝗘𝘃𝗲𝗿𝘆 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗦𝗵𝗼𝘂𝗹𝗱 𝗥𝗲𝗮𝗱

We as developers need to learn new stuff, which is one of the most essential things in our professional life. This helps us build and develop new skills for the job. Yet, I found that people are not reading so many research papers on computer science. You could ask why would you do this. Well, in those papers, you will understand different computer science and software engineering concepts (depth and breadth). Most of the features you use today in your programming languages came from some of those papers, and with new papers, you can predict what will come.

Here is the list of the most critical computer science papers:

𝟭. 𝗢𝗻 𝘁𝗵𝗲 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮 𝗧𝗼 𝗕𝗲 𝗨𝘀𝗲𝗱 𝗶𝗻 𝗗𝗲𝗰𝗼𝗺𝗽𝗼𝘀𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗶𝗻𝘁𝗼 𝗠𝗼𝗱𝘂𝗹𝗲𝘀 (𝟭𝟵𝟳𝟮.), 𝗗.𝗟.𝗣𝗮𝗿𝗻𝗮𝘀

In this paper, Parnas discussed modularization as a mechanism for improving a system's flexibility and comprehensibility while reducing its development time. He also discussed the criteria for decomposing systems into modules.

Link: https://t.co/6VIcOaxAKJ

𝟮. 𝗔𝗻 𝗔𝘅𝗶𝗼𝗺𝗮𝘁𝗶𝗰 𝗕𝗮𝘀𝗶𝘀 𝗳𝗼𝗿 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 (𝟭𝟵𝟲𝟵.), 𝗖.𝗔.𝗥. 𝗛𝗼𝗮𝗿𝗲

In this paper, C. A. R. Hoare explores the mathematical logic underlying computer programming. Deductive reasoning should inform every program's state and output. Axioms make up deductive reasoning, and inference rules are based on this collection of axioms.

Link: https://t.co/PO7rC1I5pk

𝟯. 𝗧𝗶𝗺𝗲, 𝗖𝗹𝗼𝗰𝗸𝘀, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗢𝗿𝗱𝗲𝗿𝗶𝗻𝗴 𝗼𝗳 𝗘𝘃𝗲𝗻𝘁𝘀 𝗶𝗻 𝗮 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺 (𝟭𝟵𝟳𝟴.), 𝗟. 𝗟𝗮𝗺𝗽𝗼𝗿𝘁

In the essay, Lamport discusses how humans perceive time, the necessity for a paradigm change regarding distributed systems, and the notion of incomplete ordering.

Link: https://t.co/JhYFSrl6yg

𝟰. 𝗢𝘂𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗧𝗮𝗿 𝗣𝗶𝘁 (𝟮𝟬𝟬𝟲.), 𝗕. 𝗠𝗼𝘀𝗲𝗹𝗲𝘆, 𝗣. 𝗠𝗮𝗿𝗸𝘀

This paper discusses the causes and effects of complexity in software systems and approaches to understanding it.

Link: https://t.co/lMI5IiKKtX

𝟱. 𝗗𝘆𝗻𝗮𝗺𝗼: 𝗔𝗺𝗮𝘇𝗼𝗻’𝘀 𝗛𝗶𝗴𝗵𝗹𝘆 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗞𝗲𝘆-𝘃𝗮𝗹𝘂𝗲 𝗦𝘁𝗼𝗿𝗲 (𝟮𝟬𝟬𝟳.), 𝗚.𝗗𝗲𝗖𝗮𝗻𝗱𝗶𝗮 𝗲𝘁 𝗮𝗹.

This paper explains the design and architecture of AmazonDB, a fast NoSQL key-value database. You can learn that Dynamo is designed as a write-intensive data store, but it has limitations and scaling possibilities.

Link: https://t.co/uakqVwHyTO.

𝟲. 𝗠𝗮𝗽𝗥𝗲𝗱𝘂𝗰𝗲: 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗼𝗻 𝗟𝗮𝗿𝗴𝗲 𝗖𝗹𝘂𝘀𝘁𝗲𝗿𝘀 (𝟮𝟬𝟬𝟰.), 𝗝. 𝗗𝗲𝗮𝗻, 𝗦. 𝗚𝗵𝗲𝗺𝗮𝘄𝗮𝘁 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲

The paper explains the MapReduce programming model and its implementation for processing and generating large data sets.

Link: https://t.co/EvmQnDmATF

𝟳. 𝗔 𝗡𝗼𝘁𝗲 𝗢𝗻 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 (𝟭𝟵𝟵𝟰.), 𝗝. 𝗪𝗮𝗹𝗱𝗼, 𝗚. 𝗪𝘆𝗮𝗻𝘁, 𝗔. 𝗪𝗼𝗹𝗹𝗿𝗮𝘁𝗵, 𝗦. 𝗞𝗲𝗻𝗱𝗮𝗹𝗹

The authors of this study debunk an old myth that building a distributed system makes distribution visible.

Link: https://t.co/lrONESHt2s

𝟴. 𝗔 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 𝘀𝘂𝗶𝘁𝗲 𝗳𝗼𝗿 𝗼𝗯𝗷𝗲𝗰𝘁-𝗼𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗱𝗲𝘀𝗶𝗴𝗻 (𝟭𝟵𝟵𝟰.), 𝗦.𝗥. 𝗖𝗵𝗶𝗱𝗮𝗺𝗯𝗲𝗿

This paper presents a new set of software metrics for OO design.

Link: https://t.co/t8XNvv4ARZ.

𝟵. 𝗔 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗼𝗱𝗲𝗹 𝗼𝗳 𝗱𝗮𝘁𝗮 𝗳𝗼𝗿 𝗹𝗮𝗿𝗴𝗲 𝘀𝗵𝗮𝗿𝗲𝗱 𝗱𝗮𝘁𝗮 𝗯𝗮𝗻𝗸𝘀 (𝟭𝟵𝟲𝟵.), 𝗘. 𝗙. 𝗖𝗼𝗱𝗱

The paper addresses some of the problems with database systems at the time of its publication that the relational model solved. SQL Databases are based on this paper.

https://t.co/hqTrzqxfWQ

𝟭𝟬. 𝗪𝗵𝘆 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 (𝟭𝟵𝟵𝟬.), 𝗝. 𝗛𝘂𝗴𝗵𝗲𝘀

In this paper, the authors describe the importance of functional programming where modularisation is key.

Link: https://t.co/d4luxwTZQl.

Bonus: "𝗛𝗼𝘄 𝘁𝗼 𝗥𝗲𝗮𝗱 𝗮 𝗣𝗮𝗽𝗲𝗿", 𝗦. 𝗞𝗲𝘀𝗵𝗮𝘃

This paper outlines a practical and efficient three-pass method for reading research papers.

Link: https://t.co/3lfjvx3Dlj

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mukulcodes retweeted

Manning Publications

@ManningBooks

3 days ago

If you're making technical decisions that shape a system, you're already doing software architecture. The difference is whether you're doing it intentionally. In Grokking Software Architecture, @codeliftsleep gives developers the vocabulary, frameworks, and thinking process needed to make better long-term technical decisions. Watch the First Chapter Summary: https://t.co/z8tejnhusJ

ManningBooks's tweet photo. If you're making technical decisions that shape a system, you're already doing software architecture.

The difference is whether you're doing it intentionally.

In Grokking Software Architecture, @codeliftsleep gives developers the vocabulary, frameworks, and thinking process needed to make better long-term technical decisions.

Watch the First Chapter Summary: https://t.co/z8tejnhusJ

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Muhammad Sufyan

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FullStack Developer #programmer #freelancer

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Alive and Kicking || Computer Engineer || Data Engineer

BILAL

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Human curiosity is infinite. Let's remember Why?What? How? as a child. The enemies of curiosity are prejudice and common sense

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4 days ago

LOVE YOU VENKY BRO ❤️😭

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Sam

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🔴 RAJAT IS JUST A CAPTAIN, THE REAL MENTOR IS VIRAT KOHLI 🤯 Ravi Ashwin🎙️: Rajat Patidar deserves huge credit for his captaincy. He selflessly gave Virat Kohli the space to lead and mentor the team, focusing on what was best for RCB rather than seeking the spotlight himself.