Computer Science and Programming
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Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_science
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Network:📈 Analytical overview of Telegram channel Computer Science and Programming
Channel Computer Science and Programming (@computer_science_and_programming) in the English language segment is an active participant. Currently, the community unites 140 479 subscribers, ranking 804 in the Technologies & Applications category and 88 in the Italy region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 140 479 subscribers.
According to the latest data from 31 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -734 over the last 30 days and by -18 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 7.96%. Within the first 24 hours after publication, content typically collects 1.94% reactions from the total number of subscribers.
- Post reach: On average, each post receives 11 177 views. Within the first day, a publication typically gains 2 728 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 14.
- Thematic interests: Content is focused on key topics such as sellerflash, github, developer, pricing, waybienad.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Channel specialized for advanced topics of:
* Artificial intelligence,
* Machine Learning,
* Deep Learning,
* Computer Vision,
* Data Science
* Python
Admin: @otchebuch
Memes: @memes_programming
Ads: @Source_Ads,
https://telega.io/c/computer_sc...”
Thanks to the high frequency of updates (latest data received on 01 September, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
140 479
Subscribers
-1824 hours
-2617 days
-73430 days
Posts Archive
𝗗𝗼 𝘆𝗼𝘂 𝘀𝘂𝗳𝗳𝗲𝗿 𝗳𝗿𝗼𝗺 𝗜𝗺𝗽𝗼𝘀𝘁𝗲𝗿 𝗦𝘆𝗻𝗱𝗿𝗼𝗺𝗲?
Always believing that you must know everything before doing?
Adjust your viewpoint.
Be a smart learner!
𝗟𝗲𝗮𝗿𝗻 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀, 𝗻𝗼𝘁 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀
Have you ever wondered why some technologies are still with us, and some disappeared? Here is 𝘁𝗵𝗲 𝗟𝗶𝗻𝗱𝘆 𝗘𝗳𝗳𝗲𝗰𝘁 to explain it. This effect tells me that 𝗯𝘆 𝘁𝗵𝗲 𝘁𝗶𝗺𝗲 𝗜 𝗿𝗲𝘁𝗶𝗿𝗲, 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝘄𝗶𝗹𝗹 𝘀𝘁𝗶𝗹𝗹 𝗯𝗲 𝘂𝘀𝗶𝗻𝗴 𝗖# 𝗮𝗻𝗱 𝗦𝗤𝗟. It is a concept in technology and innovation that suggests that the future life expectancy of a non-perishable item is proportional to its current age. In other words, the longer an item has been in use, the longer it is likely to continue to be used.
The concept was named after Lindy's Deli in New York City, where Nassim Nicholas Taleb popularized it in his book "𝗧𝗵𝗲 𝗕𝗹𝗮𝗰𝗸 𝗦𝘄𝗮𝗻." According to Taleb, the Lindy effect applies to many things, including technologies, ideas, and cultures, and evaluates their potential longevity.
In software development, we see that 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 𝗰𝗼𝗺𝗲 𝗮𝗻𝗱 𝗴𝗼, 𝗯𝘂𝘁 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 𝘀𝘂𝗰𝗵 𝗮𝘀 𝗦𝗤𝗟 𝗼𝗿 𝗖# 𝗮𝗻𝗱 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝘀𝘂𝗰𝗵 𝗮𝘀 𝗢𝗯𝗷𝗲𝗰𝘁-𝗼𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗼𝗿 𝗦𝗢𝗟𝗜𝗗 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝘀𝘁𝗮𝘆. All the energy I put into learning those technologies 10-15 years ago continues to support my work today. Some things changed, but the fundamentals stayed and even got better.
So, try to 𝗹𝗲𝗮𝗿𝗻 𝘁𝗵𝗶𝗻𝗴𝘀 𝘁𝗵𝗮𝘁 𝗱𝗼𝗻'𝘁 𝗰𝗵𝗮𝗻𝗴𝗲 (quote from Jeff Bezos). Focus on foundations, not frameworks. I've been doing this for two decades now.
UNTANGLE Spring Security Architecture 🔒
Authentication and Authorization:
- Validates user identity and orchestrates controlled resource access.
- Empowers comprehensive user authentication and nuanced authorization.
Security Filters:
- Intercepts incoming requests, meticulously enforcing security measures.
- Offers a flexible, layered security filter chain for diverse protection strategies.
Custom Authentication Providers:
- N Authentication Provider: Extends authentication capabilities beyond default configurations. Facilitates tailored authentication strategies and seamless integration.
- DaoAuthentication Provider: Adopts a database-backed approach for user authentication. Scrutinizes user credentials against stored records, heightening security.
Authentication Manager:
- Orchestrates the authentication process, coordinating various authentication providers.
- Serves as a pivotal component in managing user identity verification.
Token-based Security (JWT):
- Implements advanced token-based authentication for stateless communication.
- Facilitates secure interaction without the need for server-side storage.
Session Management:
- Efficiently manages user sessions, mitigating session-related risks.
- Provides adaptability for session creation, tracking, and invalidation.
Authentication Tokens:
- Username Password Authentication Token:Represents user credentials for authentication purposes.
- Leverages usernames and passwords for robust user verification.
Add/Remove Authentication Token:
- Dynamically enables the addition and removal of authentication tokens.
- Ensures real-time control over user authentication, promoting flexibility.
DevOps Explained!
Plan:
- Defines project goals, scope, and requirements, identifying stakeholders and resources. 📝
Build:
- Involves coding, compiling, and packaging, emphasizing version control and code management. 🔧
Test:
- Ensures software aligns with quality and functional standards, utilizing automated and security testing. 🧪
Deploy:
- Releases software precisely using deployment automation and monitoring tools. 🚚
Operate:
- Ensures operational stability, promptly addressing issues with management tools. 🛠
Observe:
- Analyzes data from software and production using logging, tracing, and metrics tools. 🔎
Continuous Feedback:
- Gathers ongoing feedback, utilizing loops, surveys, and analytics for improvement. 📊
DevOps:
- Cultivates a culture of collaboration, communication, and continuous improvement for faster, better, and safer software delivery.
How Git Works - From Working Directory to Remote Repository
[1]. Working Directory:
Your project starts here. The working directory is where you actively make changes to your files.
[2]. Staging Area (Index):
After modifying files, use git add to stage changes. This prepares them for the next commit, acting as a checkpoint.
[3]. Local Repository:
Upon staging, execute git commit to record changes in the local repository. Commits create snapshots of your project at specific points.
[4]. Stash (Optional):
If needed, use git stash to temporarily save changes without committing. Useful when switching branches or performing other tasks.
[5]. Remote Repository:
The remote repository, hosted on platforms like GitHub, is a version of your project accessible to others. Use git push to send local commits and git pull to fetch remote changes.
[6]. Remote Branch Tracking:
Local branches can be set to track corresponding branches on the remote. This eases synchronization with git pull or git push.
Computer Memory Explained
Computer memory is like a workspace for your computer. It stores data and instructions that the computer needs to access quickly.
Internal Memory:
1. ROM (Read-Only Memory):
- PROM (Programmable ROM): Programmable once by the user post-manufacturing. 🖊
- EPROM (Erasable Programmable ROM): Can be erased with ultraviolet light and reprogrammed. ☀️🔁
- EEPROM (Electrically Erasable Programmable ROM): Can be erased and reprogrammed electrically, multiple times. ⚡️
2. RAM (Random Access Memory):
- SRAM (Static RAM): Retains data as long as power is supplied, no need to refresh, faster than DRAM. ⚡️💨
- DRAM (Dynamic RAM): Stores data in capacitors that must be refreshed periodically, widely used. 🔄
- SDRAM (Synchronous DRAM): Syncs with CPU clock speed for improved performance. ⏱
- RDRAM (Rambus DRAM): High bandwidth memory with Rambus technology. 🚀
- DDR SDRAM (Double Data Rate SDRAM): Transfers data on both rising and falling clock edges.
- DDR1: First generation, higher speed and bandwidth than SDRAM. 🆕
- DDR2: Improved version of DDR1 with lower power consumption and higher speeds. 🔋💨
- DDR3: Higher speeds and reduced power consumption over DDR2. 🔋➕💨
- DDR4: Higher module density and increased performance with reduced voltage. 🔋🆙🎛
External Memory:
1. HDD (Hard Disk Drive): Uses spinning disks to read/write data, traditional storage device. 🔄💾
2. SSD (Solid State Drive): Non-volatile flash memory for faster speed than HDDs. 🚀💾
3. CD (Compact Disc): Optical disc for storing digital data, used for music and software
DevOps is a set of practices that combines software development and IT operations. It aims to shorten the software development life cycle and provide continuous delivery with high software quality. 🚀
DevOps has several phases
Plan: This phase involves defining the goals, scope, and requirements of the software project. It also includes identifying the stakeholders, risks, and resources needed. 📝
Build: This phase involves writing, compiling, and packaging the code into executable units. It also includes using version control, code review, and configuration management tools. 🔧
Test: This phase involves verifying that the software meets the quality standards and functional specifications. It also includes using automated testing, performance testing, and security testing tools. 🧪
Deploy: This phase involves releasing the software to the production environment or to the end-users. It also includes using deployment automation, orchestration, and monitoring tools. 🚚
Operate: This phase involves running and maintaining the software in the production environment. It also includes using incident management, problem management, and change management tools. 🛠
Observe: This phase involves collecting and analyzing data from the software and the production environment. It also includes using logging, tracing, and metrics tools. 🔎
Continuous Feedback and Discovery: This phase involves gathering feedback from the stakeholders, users, and customers. It also includes using feedback loops, surveys, and analytics tools. It also involves discovering new opportunities, challenges, and trends. 📊
DevOps is a culture that promotes collaboration, communication, and continuous improvement. It helps to deliver software faster, better, and safer. 😊
18 Most common used Java List methods
1. add(E element) - Adds the specified element to the end of the list.
2. addAll(Collection c) - Adds all elements of the specified collection to the end of the list.
3. remove(Object o) - Removes the first occurrence of the specified element from the list.
4. remove(int index) - Removes the element at the specified position in the list.
5. get(int index) - Returns the element at the specified position in the list.
6. set(int index, E element) - Replaces the element at the specified position in the list with the specified element.
7. indexOf(Object o) - Returns the index of the first occurrence of the specified element in the list.
8. contains(Object o) - Returns true if the list contains the specified element.
9. size() - Returns the number of elements in the list.
10. isEmpty() - Returns true if the list contains no elements.
11. clear() - Removes all elements from the list.
12. toArray() - Returns an array containing all the elements in the list.
13. subList(int fromIndex, int toIndex) - Returns a view of the portion of the list between the specified fromIndex, inclusive, and toIndex, exclusive.
14. addAll(int index, Collection c) - Inserts all elements of the specified collection into the list, starting at the specified position.
15. iterator() - Returns an iterator over the elements in the list.
16. sort(Comparator c) - Sorts the elements of the list according to the specified comparator.
17. replaceAll(UnaryOperator operator) - Replaces each element of the list with the result of applying the given operator.
18. forEach(Consumer action) - Performs the given action for each element of the list until all elements have been processed or the action throws an exception.
Ever wondered how Docker 🐳 works?
1. Docker Build 🏗
2. Docker Push ☁️
3. Docker Run 🏃
4. Docker Pull 🚚
5. Docker Images 🖼
If you design complex systems, you'll love sequence diagrams
Complex system architectures can quickly become tangled and hard to follow. Enter sequence diagrams! They keep your design neat and easily understandable.
For example, check out the diagram below. It depicts a client/server interaction, clearly differentiating between a cache hit and a cache miss. This is a prime example of how visual aids simplify complex interactions.
Sequence diagrams are a must when you aim to:
- 🚀 Map out end-to-end system workflows.
- 🔍 Clarify interactions between components.
- 📚 Produce clear and concise documentation.
- 🔧 Identify design flaws.
I have two favorites for creating sequence diagrams. WebSequenceDiagrams and Mermaid (links in comment). You can make sequence diagrams easily with just text.
Do you have a go-to tool for crafting good-looking sequence diagrams? Drop your suggestions below! 👇
Improving API Performance with Database Connection Pooling
The diagram below shows 5 common API optimization techniques. Today, I’ll focus on number 5, connection pooling. It is not as trivial to implement as it sounds for some languages.
When fulfilling API requests, we often need to query the database. Opening a new connection for every API call adds overhead. Connection pooling helps avoid this penalty by reusing connections.
How Connection Pooling Works
1. For each API server, establish a pool of database connections at startup.
2. Workers share these connections, requesting one when needed and returning it after.
Challenges for Some Languages
However, setting up connection pooling can be more complex for languages like PHP, Python and Node.js. These languages handle scale by having multiple processes, each serving a subset of requests.
- In these languages, database connections get tied to each process.
- Connections can't be efficiently shared across processes. Each process needs its own pool, wasting resources.
In contrast, languages like Java and Go use threads within a single process to handle requests. Connections are bound at the application level, allowing easy sharing of a centralized pool.
Connection Pooling Solution
Tools like PgBouncer work around these challenges by proxying connections at the application level.
PgBouncer creates a centralized pool that all processes can access. No matter which process makes the request, PgBouncer efficiently handles the pooling.
At high scale, all languages can benefit from running PgBouncer on a dedicated server. Now the connection pool is shared over the network for all API servers. This conserves finite database connections.
Connection pooling improves efficiency, but its implementation complexity varies across languages.
Leveraging SAM for Single-Source Domain Generalization in Medical Image Segmentation
📄 https://arxiv.org/pdf/2401.02076.pdf
💻 https://github.com/SARIHUST/SAMMed
@computer_science_and_programming
