Skip to content

Latest commit

 

History

History
2019 lines (1686 loc) · 140 KB

README-ar.md

File metadata and controls

2019 lines (1686 loc) · 140 KB
Raw

الإعداد لمقابلة البرمجة

أنشأتها في المقام الأول كلائحة قصيرة من المواضيع الدراسية لكيف يصبح المرء مهندس برمجيات، ولكن سرعان ما كبرت هذه القائمة إلى ما تراه أمامك اليوم. بعد خوض هذه الخطة الدراسية, تم توظيفي كمهندس تطوير برمجيات لدى أمازون! على الأغلب لن تحتاج إلى ان تدرس بالقدر الذي درسته أنا. لكن على كل حال كل ما تحتاج إليه موجود هنا

درست لمدة ٨-١٢ ساعة في اليوم, لعدة أشهر. هذه هي قصتي: لماذا درست دواما كاملا لمدة ثمانية أشهر من أجل مقابلة لدا قوقل

العناصر المذكورة في هذه اللائحة ستجهزك جيدا لمقابلة تقنية مع تقريبا أي شركة برمجية, حتى الشركات العملاقة: أمازون، فيسبوك، قوقل، وميكروسوفت

بالتوفيق

الترجمات:
ترجمات تحت الإعداد:

Become a sponsor and support Coding Interview University!

Special thanks to:

OSS Capital
Founded in 2018, OSS Capital is the first and only venture capital platform focused
exclusively on supporting early-stage COSS (commercial open source) startup founders.


Gitpod

Dev environments built for the cloud

Natively integrated with GitLab, GitHub, and Bitbucket, Gitpod automatically and continuously prebuilds dev environments for all your branches. As a result team members can instantly start coding with fresh dev environments for each new task - no matter if you are building a new feature, want to fix a bug, or work on a code review.

ما هذا؟

هي خطتي متعددة الأشهر للوصول من مطور ويب (تعليم ذاتي، بدون درجة علمية في علوم الحاسب) لمنصب مهندس برمجيات لشركة عملاقة

Coding at the whiteboard - from HBO's Silicon Valley

تم إعدادها لمهنسي البرمجيات الجدد أو أولئك المنتقلين من تطوير الويب إلى هندسة البرمجيات (حيث المعرفة بعلوم الحاسب ضرورية) إذا كان لديك العديد من سنوات الخبرة في بناء تطبيقات الويب أو البرمجيات، خذ في عين الإعتبار ان المقابلة ستكون اصعب

إذا كانت لديك العديد من سنوات الخبرة في تطوير الويب, خذ في عين الإعتبار أن الشركات االبرمجية الضخمة مثل قوقل, فيسبوك, و ميكروسوفت ينظرون إلى هندسة البرمجيات بشكل مختلف عن تطوير البرمجيات/ويب, و تحتاج إلى معرفة علوم الحاسب

إذا اردت ان تصبح مهندس موثوقية أو مهندس عمليات, ادرس اكثر من القائمة الإختيارية (شبكات, امن)

الفهرس

---------------- Everything below this point is optional ----------------

Additional Resources

لماذا استخدمه؟

أقوم بمتابعة هذه الخطة لتحضير إلى المقابلة الشخصية بجوجل. لقد قمت بناء مواقع ويب، وتقديم خدمات ذات صلة، وبناء شركات ناشئة منذ 1997. لدي درجة علمية في الاقتصاد، وليس في علوم الحاسب. أنا شخص ناجح في مجال عملي، ولكنني أريد أن أعمل بجوجل. أريد أن أعمل على أنظمة كبيرة والحصول على فهم كبير في أنظمة الحاسوب، كفاءة الخوارزميات، كقاءة الهياكل البيانية، اللغات الأقرب إلى الآلة وكيفية عملها. وإذ لم تعرف أين منها لن تعينك جوجل.

عندما بدأت هذا المشروع، لم أكن أعرف الإستاك "stack" من الهيب "heap"، ولم أكن أعرف المعامل الأعلى في قياس كفاءة الخوارزميات "Big-O"، ولا عن التري "tree"، أو عن زيارة الجراف "graph". إذا كان عليا أن أصنع برنامج عن الترتيب، سأخبرك أنه ليس على درجة عالية من الكقاءة.

كل هياكل البيانات التي استخدمتها كانت من الأشياء السابق إعدادها في اللغة البرمجية, ولم أعرف كيفية عملها من الداخل. لم أعرف إطلاقا كيفية تنظيم الذاكرة مالم أحصل على "خارج نطاق الذاكرة" من عملية برمجية، وعندها كان عليا أن أجد طريقة ما لتحايل على الأمر. لقد استخدمت مصفوفة من أكثر من بعد في مرات قليلة, وألاف من المصفوفات المترابطة، لكن لم أنشأ هياكل بيانات من البداية. لكن عند المضي قدما في هذه الدراسة وجدت أني على ثقة عالية من أنه سيتم توظيفي. إنها خطة طويلة، أخدت مني شهور. إذا كانت على دراية من كثير من هذه الأشياء ستأخد وقتا أقل.

كيفية استخدامها

كل عنصر من هذه القائمة مرتب لذلك عليم أن تتبع العناصر من أعلى إلى أسفل. سأستخدم خاصية تعليم ماأنجز من الجيت هب "Github" لمتابعة التقدم.

اصنع مسار جديد يمكن من خلاله أن تضع علامة [x]

احصل على نسخة خاصة "fork" بك واتبع هذه الأوامر

Clone to your local repo

git clone [email protected]:<your_github_username>/coding-interview-university.git

git checkout -b progress

git remote add jwasham https://github.com/jwasham/coding-interview-university

git fetch --all

دون بعلامة X بعد الإنتهاء من دراسة العنصر

git add .

git commit -m "Marked x"

git rebase jwasham/main

git push --set-upstream origin progress

git push --force

More about Github-flavored markdown

هل تشعر أنك لست بالذكاء الكافي

عن مصادر مقاطع الفديو

بعض الفديوهات متاحة فقط عن طريق الاشتراك في كورسيرا "Coursera"، إيدكس "Edx" أو ليندا "Lynda.com". يطلق عليهم موكس"MOOCS". بعض الأحيان الدروس ليست متاحة في كل الأوقات لذلك عليك الانتظار عدة أشهر حتى تكون متاحة للالتحاق بها. دروس ليندا "Lynda" ليست مجانية.

أقدر مساعدتك لإضافة مصارد متاحة دائما مثل اليوتيوب "Youtube" أو مصادر أخرى متاحة.

أفضل استخدام مصادر الجامعات.

مراحل المقابلة الشخصية و الإستعداد العام للمقابلة

اختر لغة برمجية واحدة للمقابلة البرمجية

كتبت مقال قصير عن هذا: أهمية اختبار لغة برمجية واحدة لمقابلة جوجل

يمكن استخدام اللغة التي ترى أنك تشعر بارتياح فيها لإداء جزء البرمحة من المقابلة الشخصية، لكن لجوجل هناك أربع اخبارات فوية:

  • السي بلس بلس "++C"
  • الجافا "Java"
  • البايثون "Python"

يمكن أيضا استخدام هؤلاء لكن اقرأ عنهم أولا. ربما هم من المحاذير

  • الجافا سكربت "JavaScript" -الروبي "Ruby"

هذا مقال كتبته عن اختيار لغة المقابلة: Pick One Language for the Coding Interview.

ستحتاج أن تشعر بارتياح للغة والإلمام بها

اقرأ المزيد عم الاختيارات:

شاهد مصادر اللغات من هنا

You'll see some C, C++, and Python learning included below, because I'm learning. There are a few books involved, see the bottom.

لائحة الكتب

هذه قائمة من العناصر التي استحدمتها. تم اختصارها للمحافظة على الكتب.

التحضير للمقابلة الشخصية

اذا كان لديك الكثير من الوقت

اختر واحدة:

تحديد اللغة

عليك اختيار لغة واحدة للمقابلة الشخصية (انظر للأعلى). هنا بعض التوصيات للغات. لا أملك كل المصادر للغات. ارجب بالإضافة

إذا قرأت واحدا فقط من هذه المصارد، سيكون لديك كل الهياكل البيانية والخوارزميات للبدء في المشاكل البرمجية. يمكن تخطي كل محاضرات الفديو في هذا المشروع، في حالة إذا لا تريد أن تلقي النظر عليهم

Additional language-specific resources here.

C++

I haven't read these two, but they are highly rated and written by Sedgewick. He's awesome.

If you have a better recommendation for C++, please let me know. Looking for a comprehensive resource.

Java

OR:

  • Data Structures and Algorithms in Java
    • by Goodrich, Tamassia, Goldwasser
    • used as optional text for CS intro course at UC Berkeley
    • see my book report on the Python version below. This book covers the same topics.

Python

قبل البدء

هذه القائمة تمتد لأشهر نعم وهذا ما باليد حيلة. هنا بعض الأخطاء التي فعلتها لذا لديك فرصة أفضل.

1. لن تتذكر هذا كله

لقد شاهدت ساعات من الفديوهات وأخذت مدونات لها، وبعد شهور لم أتذكر شيئا. استغرقت 3 أيام لمراجعة مادرسته وعمل فلاش كارد للتذكري.

اقرأ من فضلك لعدم ارتكاب الأخطاء:

Retaining Computer Science Knowledge

2. استخدام الفلاش كار

لحل المشكلة، صنعت مجموعة من الفلاش كارد ضمن فئتين: عام و كود. كل كارد لديه تنسيق خاص.

عملت موقع خاص بي لذا يمكن أن استخدم التابلت للمراجعة.

اصنع واحدا منها لك مجانا:

Keep in mind I went overboard and have cards covering everything from assembly language and Python trivia to machine learning and statistics. It's way too much for what's required.

Note on flashcards: The first time you recognize you know the answer, don't mark it as known. You have to see the same card and answer it several times correctly before you really know it. Repetition will put that knowledge deeper in your brain.

An alternative to using my flashcard site is Anki, which has been recommended to me numerous times. It uses a repetition system to help you remember. It's user-friendly, available on all platforms and has a cloud sync system. It costs $25 on iOS but is free on other platforms.

My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (thanks @xiewenya).

3. ابدأ في إجراء أسئلة المقابلة بينما تتعلم هياكل البيانات والخوارزميات

You need to apply what you're learning to solving problems, or you'll forget. I made this mistake. Once you've learned a topic, and feel comfortable with it, like linked lists, open one of the coding interview books and do a couple of questions regarding linked lists. Then move on to the next learning topic. Then later, go back and do another linked list problem, or recursion problem, or whatever. But keep doing problems while you're learning. You're not being hired for knowledge, but how you apply the knowledge. There are several books and sites I recommend. See here for more: Coding Question Practice.

4. المراجعة ,المراجعة, المراجعة

I keep a set of cheat sheets on ASCII, OSI stack, Big-O notations, and more. I study them when I have some spare time.

Take a break from programming problems for a half hour and go through your flashcards.

5. ركز

There are a lot of distractions that can take up valuable time. Focus and concentration are hard. Turn on some music without lyrics and you'll be able to focus pretty well.

ما لن تجده هنا

These are prevalent technologies but not part of this study plan:

  • SQL
  • Javascript
  • HTML, CSS, and other front-end technologies

الخطة اليومية

Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement.

Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:

  • C - using structs and functions that take a struct * and something else as args
  • C++ - without using built-in types
  • C++ - using built-in types, like STL's std::list for a linked list
  • Python - using built-in types (to keep practicing Python)
  • and write tests to ensure I'm doing it right, sometimes just using simple assert() statements
  • You may do Java or something else, this is just my thing

You don't need all these. You need only one language for the interview.

Why code in all of these?

  • Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember)
  • Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python or Java))
  • Make use of built-in types, so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production)

I may not have time to do all of these for every subject, but I'll try.

You can see my code here:

You don't need to memorize the guts of every algorithm.

Write code on a whiteboard or paper, not a computer. Test with some sample inputs. Then test it out on a computer.

المعرفة المسبقة

Algorithmic complexity / Big-O / Asymptotic analysis

Data Structures

  • Arrays

    • Implement an automatically resizing vector.
    • Description:
    • Implement a vector (mutable array with automatic resizing):
      • Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing.
      • New raw data array with allocated memory
        • can allocate int array under the hood, just not use its features
        • start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128
      • size() - number of items
      • capacity() - number of items it can hold
      • is_empty()
      • at(index) - returns item at given index, blows up if index out of bounds
      • push(item)
      • insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right
      • prepend(item) - can use insert above at index 0
      • pop() - remove from end, return value
      • delete(index) - delete item at index, shifting all trailing elements left
      • remove(item) - looks for value and removes index holding it (even if in multiple places)
      • find(item) - looks for value and returns first index with that value, -1 if not found
      • resize(new_capacity) // private function
        • when you reach capacity, resize to double the size
        • when popping an item, if size is 1/4 of capacity, resize to half
    • Time
      • O(1) to add/remove at end (amortized for allocations for more space), index, or update
      • O(n) to insert/remove elsewhere
    • Space
      • contiguous in memory, so proximity helps performance
      • space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n)

  • Linked Lists

    • Description:
    • C Code (video) - not the whole video, just portions about Node struct and memory allocation
    • Linked List vs Arrays:
    • why you should avoid linked lists (video)
    • Gotcha: you need pointer to pointer knowledge: (for when you pass a pointer to a function that may change the address where that pointer points) This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness.
    • Implement (I did with tail pointer & without):
      • size() - returns number of data elements in list
      • empty() - bool returns true if empty
      • value_at(index) - returns the value of the nth item (starting at 0 for first)
      • push_front(value) - adds an item to the front of the list
      • pop_front() - remove front item and return its value
      • push_back(value) - adds an item at the end
      • pop_back() - removes end item and returns its value
      • front() - get value of front item
      • back() - get value of end item
      • insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
      • erase(index) - removes node at given index
      • value_n_from_end(n) - returns the value of the node at nth position from the end of the list
      • reverse() - reverses the list
      • remove_value(value) - removes the first item in the list with this value
    • Doubly-linked List

  • Stack

    • Stacks (video)
    • Will not implement. Implementing with array is trivial

  • Queue

    • Queue (video)
    • Circular buffer/FIFO
    • Implement using linked-list, with tail pointer:
      • enqueue(value) - adds value at position at tail
      • dequeue() - returns value and removes least recently added element (front)
      • empty()
    • Implement using fixed-sized array:
      • enqueue(value) - adds item at end of available storage
      • dequeue() - returns value and removes least recently added element
      • empty()
      • full()
    • Cost:
      • a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n) because you'd need the next to last element, causing a full traversal each dequeue
      • enqueue: O(1) (amortized, linked list and array [probing])
      • dequeue: O(1) (linked list and array)
      • empty: O(1) (linked list and array)

  • Hash table

More Knowledge

Trees

Sorting

As a summary, here is a visual representation of 15 sorting algorithms. If you need more detail on this subject, see "Sorting" section in Additional Detail on Some Subjects

Graphs

Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were.

Even More Knowledge

System Design, Scalability, Data Handling

You can expect system design questions if you have 4+ years of experience.

Final Review

This section will have shorter videos that you can watch pretty quickly to review most of the important concepts.
It's nice if you want a refresher often.

Coding Question Practice

Now that you know all the computer science topics above, it's time to practice answering coding problems.

Coding question practice is not about memorizing answers to programming problems.

Why you need to practice doing programming problems:

  • Problem recognition, and where the right data structures and algorithms fit in
  • Gathering requirements for the problem
  • Talking your way through the problem like you will in the interview
  • Coding on a whiteboard or paper, not a computer
  • Coming up with time and space complexity for your solutions
  • Testing your solutions

There is a great intro for methodical, communicative problem solving in an interview. You'll get this from the programming interview books, too, but I found this outstanding: Algorithm design canvas

No whiteboard at home? That makes sense. I'm a weirdo and have a big whiteboard. Instead of a whiteboard, pick up a large drawing pad from an art store. You can sit on the couch and practice. This is my "sofa whiteboard". I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick. I use a pencil and eraser.

my sofa whiteboard

Supplemental:

Read and Do Programming Problems (in this order):

See Book List above

Coding exercises/challenges

Once you've learned your brains out, put those brains to work. Take coding challenges every day, as many as you can.

Coding Interview Question Videos:

Challenge sites:

Language-learning sites, with challenges:

Challenge repos:

Mock Interviews:

Once you're closer to the interview

Your Resume

  • See Resume prep items in Cracking The Coding Interview and back of Programming Interviews Exposed
  • Very Important thing to remember while creating your resume, if you applying for big companies is that make it ATS Complaint.
  • How to Create or Check if your Resume is ATS Complaint

Be thinking of for when the interview comes

Think of about 20 interview questions you'll get, along with the lines of the items below. Have 2-3 answers for each. Have a story, not just data, about something you accomplished.

  • Why do you want this job?
  • What's a tough problem you've solved?
  • Biggest challenges faced?
  • Best/worst designs seen?
  • Ideas for improving an existing product
  • How do you work best, as an individual and as part of a team?
  • Which of your skills or experiences would be assets in the role and why?
  • What did you most enjoy at [job x / project y]?
  • What was the biggest challenge you faced at [job x / project y]?
  • What was the hardest bug you faced at [job x / project y]?
  • What did you learn at [job x / project y]?
  • What would you have done better at [job x / project y]?

Have questions for the interviewer

Some of mine (I already may know answer to but want their opinion or team perspective):
  • How large is your team?
  • What does your dev cycle look like? Do you do waterfall/sprints/agile?
  • Are rushes to deadlines common? Or is there flexibility?
  • How are decisions made in your team?
  • How many meetings do you have per week?
  • Do you feel your work environment helps you concentrate?
  • What are you working on?
  • What do you like about it?
  • What is the work life like?
  • How is work/life balance?

Once You've Got The Job

Congratulations!

Keep learning.

You're never really done.

*****************************************************************************************************
*****************************************************************************************************

Everything below this point is optional.
By studying these, you'll get greater exposure to more CS concepts, and will be better prepared for
any software engineering job. You'll be a much more well-rounded software engineer.

*****************************************************************************************************
*****************************************************************************************************

Additional Books

These are here so you can dive into a topic you find interesting.

  • The Unix Programming Environment

    • An oldie but a goodie

  • The Linux Command Line: A Complete Introduction

    • A modern option

  • TCP/IP Illustrated Series

  • Head First Design Patterns

    • A gentle introduction to design patterns

  • Design Patterns: Elements of Reusable Object-Oriente​d Software

    • AKA the "Gang Of Four" book, or GOF
    • The canonical design patterns book

  • UNIX and Linux System Administration Handbook, 5th Edition

  • Algorithm Design Manual (Skiena)

    • As a review and problem recognition
    • The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview
    • This book has 2 parts:
      • Class textbook on data structures and algorithms
        • Pros:
          • Is a good review as any algorithms textbook would be
          • Nice stories from his experiences solving problems in industry and academia
          • Code examples in C
        • Cons:
          • Can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects
          • Chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have
          • Don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material
      • Algorithm catalog:
        • This is the real reason you buy this book
        • About to get to this part. Will update here once I've made my way through it
    • Can rent it on kindle
    • Answers:
    • Errata

  • Write Great Code: Volume 1: Understanding the Machine

    • The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief
    • The author invented HLA, so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like
    • These chapters are worth the read to give you a nice foundation:
      • Chapter 2 - Numeric Representation
      • Chapter 3 - Binary Arithmetic and Bit Operations
      • Chapter 4 - Floating-Point Representation
      • Chapter 5 - Character Representation
      • Chapter 6 - Memory Organization and Access
      • Chapter 7 - Composite Data Types and Memory Objects
      • Chapter 9 - CPU Architecture
      • Chapter 10 - Instruction Set Architecture
      • Chapter 11 - Memory Architecture and Organization

  • Introduction to Algorithms

    • Important: Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently
    • AKA CLR, sometimes CLRS, because Stein was late to the game

  • Computer Architecture, Sixth Edition: A Quantitative Approach

    • For a richer, more up-to-date (2017), but longer treatment

  • Programming Pearls

    • The first couple of chapters present clever solutions to programming problems (some very old using data tape) but that is just an intro. This a guidebook on program design and architecture

Additional Learning

I added them to help you become a well-rounded software engineer, and to be aware of certain
technologies and algorithms, so you'll have a bigger toolbox.

Additional Detail on Some Subjects

I added these to reinforce some ideas already presented above, but didn't want to include them
above because it's just too much. It's easy to overdo it on a subject.
You want to get hired in this century, right?

Video Series

Sit back and enjoy. "Netflix and skill" :P

Computer Science Courses

Algorithms implementation

Papers

LICENSE

CC-BY-SA-4.0