Swift | Open source projects for learning and developers to follow on twitter

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Announced in 2014, the Swift programming language has quickly become one of the fastest growing languages in history. Swift makes it easy to write software that is incredibly fast and safe by design.

Blog for developers to highlight, top 10 trending open source to learn.

  1. MessageViewController A SlackViewController replacement written in Swift, compatible with iPhone X, iOS12. Created by Ryan Nystrom
  2. Swift interpreter for Pascal language (Inspired from Ruslan’s Blog). Created by Igor Kulman
  3. CollectionViewSlantedLayout subclass of the UICollectionViewLayout allowing the display of slanted cells in a UICollectionView.Created by Yassir Barchi
  4. Mint Package manager that installs and runs Swift command line tools, created by Yonas Kolb
  5. CryptoSwift Collection of standard and secure cryptographic algorithms implemented in Swift. Created by Marcin Krzyzanowski
  6. CocoaDebug Debugger tools for iOS supports Swift and Objective C, created by CocoaDebug
  7. iOS-Depth-Sampler Examples of Depth APIs in iOS, created by Shuichi Tsutsumi
  8. Universal Link Testing  It fetches and parses apple-app-site-association file for you to quickly check whether Universal Links are working. created by Ethan Huang
  9. Swift Syntax Set of Swift bindings for the libSyntax library. It allows for Swift tools to parse, inspect, generate, and transform Swift source code. Created by Apple
  10. WhatsNewKit Showcase your awesome new app features, Created by Sven Tiigi


Thanks for reading!

The table of two values, Behaviour and Structure!

The table of two values, Behaviour and Structure!

Is it more important for the software system to work or is it more important to be easy to change? If you ask the business managers they will say work is more important, some developers also go along with this attitude but that’s the wrong attitude.

Why the wrong attitude?

  1. If you give me a program that works perfectly but impossible to change, it means it won’t work when the requirements change.
  2. If you give me a program that does not work but easy to change, it means I can make the change to make it work.

If you’re a programmer with the attitude (1.) then one day your system will reach to the point where the change will be impractical (cost of change will be unaffordably high).

Eisenhower Matrix

Eisenhower said, I have two kinds of problems, the urgent and the important, where the urgent are not important and the important is never urgent.

when it comes to software, The first value of software is behavior, is urgent but not always important. The second value is architecture, is important but never urgent. Of course, some things are not urgent and not important.

  1. Urgent and important
  2. Not urgent and important
  3. Urgent and not important
  4. Not urgent and not important.

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Mistakes that business managers and developer make is to elevate items in position 3 to 1. It means they always fail to separate those features that are urgent but not important from those features that are really urgent and important and this failure leads to ignoring the important architecture of the system in favor of the unimportant features of the system.

So if you are a software developer, you are hired to maintain the quality and structure of the system and only you know the importance of the architecture.

Thanks for reading it, if you want to read in more detail, buy “Clean Architecture by Robert C. Martin”


What are the Design and Architecture?

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What are the Design and Architecture?

The design is more often seems to when it comes to structures and low-level decisions whereas Architecture is often used in the context of something at the high level where we can see how components are connected with each other. But for starters, there is no different at all.

What is the GOAL of good software design?

The goal of software architecture is to minimize the Human Resources required to build and maintain the required system (By Uncle Bob Martin)

Basic fundamentals measure the design?

The measure of design quality is simply the measure of the effort required to meet the needs of the customer if the effort is low and stays same through the lifetime, System design is good else it’s bad.

The Signature of a system design mess?

  • Developer point of view
    The graph says developers started with nearly 100% of productivity but with each release, their productivity going down

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  • Executive point of view?
    Release 1 was delivered with a few hundred thousand payrolls and by the time of 5 release, it’s going to touch $500,000.

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What is going wrong?

The moral of the story says everything in one line: “Slow and steady wins the race”. Yes, it all because of overconfidence. Everyone wants to hit the market first or release the app asap with the statement “We can clean it up later” and they can’t go back for cleaning the things up because now we have the new feature, new release so maybe next time, next time and next time.

The only way to go fast is to go well.

To take the software architecture seriously we have to think and need to know what good software architecture is, compare the different architecture with the requirements.

Thanks for reading it, if you want to read in more detail, buy “Clean Architecture by Robert C. Martin”

Concurrency|Computer Science Core Concepts in Layman’s term


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Let’s say you work as a company secretary and your job is to take the phone calls, manage meetings etc. Every time the phone rings, you have to stop whatever you are doing. A property of a program that allows tasks to run in overlapping time periods.

  1. Parallelism, allows 2 or more tasks to run at the same time (Only if the machine has the multiprocessing capability). You asked your boss and he hired a clerk for taking the call. It looks very simple but concurrency introduces a few problems like the Race condition,
  2. Race Condition, Suppose you have $500 in your bank account, at the same time when you withdraw $200 someone transferred $300 or maybe in simple words same time 2 transaction happened for withdrawing $500.
  3. Mutual Exclusion (Mutex), Solution for the Race condition. Now, whenever some transaction starts it locks the account. if some transaction is going on with your account you cannot withdraw. But next problem is nobody wants to wait every time when there’s is something going on. Semaphore is the modified solution for Mutex.
  4. Semaphore (Improper use of Semaphore will give improper results)
    • Binary Semaphore (Range is from 0 to 1), Idea is to give specific priority to different types of transaction. Withdraw request has a higher priority than bank transfer. So when you withdraw, another transaction for transfer will stop and it will resume once withdraw is completed. (As simple as that, 1 = ongoing transaction, 0 = waiting) Also known as integer semaphore.
    • Counting Semaphore (Range is from -∞ to +∞), Allow more than one process running at the same time. Let’s suppose you’re a key room manager where you have 30 keys if lockers are full users have to wait in the queue. when someone has done they will hand over the key to the first person in the queue.
  5. Deadlock, Another common issue in concurrency modal. Let’s assume user a transferred amount to b and at the same time user b transfer the amount to the user a. both transactions are waiting to complete another one as they can’t access the locked account.


Swift Keynote: Enumeration

  • An enumeration defines a common type for a group of related values and enables you to work with those values in a type-safe way within your code.   
    Or when a property can have its value only out of a defined set, enum is the solution which complimentary provides type-safety and auto-completion at compile time.
  • Enumerations can define initializers to provide an initial case value; can be extended to expand their functionality beyond their original implementation; can have functions and can conform to protocols to provide standard functionality.
  • Enums can have nested enums and associated values. 

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  • Enums can be recursive: A recursive enumeration is an enumeration that has another instance of the enumeration as the associated value for one or more of the enumeration cases. “Indirect” keyword is used to inform the compiler about recursion.

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  • Each enum case’s rawValue depends upon the raw type taken and if no raw type is not taken than rawValue wouldn’t be available. Swift’s enums don’t bound to use only integer type as a raw type, you can use StringsCharacters or even Floats instead.

Happy Coding!!

Swift Keynotes: classes & structs

  • Structs are the value type.

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  • Classes are the reference type.

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  • Properties of a constant instance of the struct are immutable because struct’s instance own the whole object and by declaring it as a constant means the whole object itself will be immutable.

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  • Properties of a constant instance of the class are mutable as class’s instance owns the object’s reference thus by declaring it as a constant only means that the further reference assignment can’t be done.

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  • Structs are blessed with default member-wise initializer but classes are not.

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  • Structs are preferable when they are small and copyable.
  • With Structs, there is much less need to worry about memory leaks or multiple threads racing to access/modify a single instance of a variable.
  • Since struct instances are allocated on the stack, and class instances are allocated on the heap, structs can sometimes be drastically faster (but it still depends on how many values you’re storing and the size/structure.)
  • In a multi-threaded environment, for instance, with a database connection that’s opened in a different thread, structs are safer. They can be copied from one thread to another thread, without running the risk of a race condition or deadlock. Classes do not have this inherent safety unless they’re deliberately made thread-safe.

Thanks a lot for reading it.

Introduction | Data Structure and Algorithms | Quick Notes | Back to Old days

Variable: A variable is nothing but a box with a label(its name) and a predefined type promise that you cannot be broken later. Have a look at mathematical equation below. 

X + 2Y = 45

Here, the names X and Y are placeholders for some data that can justify the equation if put in their places. Similarly, in computer science programming we need something to hold data and variables are nothing but that.

Data Types: In the above example, X and Y can hold any type of value such as an Integer value(5, 10) or real value(2.0, 5.8). But to solve this equation, we have to relate them to a particular kind of value they can take and Data Type is that name used for this purpose in computer science.  Or “A data type is a set of data with predefined values used to declare variables/objects. Example: integer, float, double, character, string etc.”

In computer memory, everything is either 0 or 1. A data type is a thing that tells the compiler about what kind of values a particular set of bytes are of and depending on that the compiler takes further decisions on them.

A data type can be a predefined one or can be customized according to the need. Based on this definition criteria they fall into two categories.

    1. System-defined data types(Primitive data types): As their name specifies, they are defined by the system. The primitive data type provided by many programming languages are int, float, double, char, bool etc. The number of bits allocated for each primitive data type depends on the programming language using, the compiler, and the operating system. For the same primitive type, different programming languages may use different sizes and thus their domain(total available values) will also get change. For example, int may take 2 or 4 bytes. If it is of 2 bytes then it’s domain will be -215 to 215-1 and if 4 bytes then the domain will be -232 to 232-1.
  1. User-defined data types: If primitive data types are not enough, we can define our own data type fulfilling all our requirements. Classes are the best example of user-defined data types that most of the programming languages provide. Swift provides class, struct, enum and protocol, four kinds of user-defined data types.

Data Structure: Data Structure is an arrangement of data in such a way that they can be efficiently stored and retrieved. Or we can say that it is a special kind of format for organizing data. The general data structure includes Stack, Queue, Linked List, Tree, Graphs and so on.

Depending upon the organization of data elements Data Structures are classified into two types

  1. Linear Data Structure: Linked List, Stack, and Queue are linear data structures as elements are arranged in a linear manner in them.
  2. Non-Linear Data Structure: Tree and Graph are non-linear data structure as elements are stored in a non-linear manner in them.

We talk about Data Structures as an Abstract Model and their Concrete Implementation.

An Abstract Data Type is a logical and mathematical model defining some set of rules that have to be followed and some list of operations that have to be implemented by the concrete implementation of that model. We can think of ADT as a black box which hides the inner structure and design of a data type.

For example, an Abstract model of a Car can be… an object having four wheels, a steering, brake, accelerator, motor, some number of seats etc. etc. with on/off, run and some other operations.

A concrete implementation of an abstract model is called Concrete Data Type. For example, Duster is a concrete implementation of abstract model Car.

A list, Stack, Queue, Tree, Graphs etc. are abstract data types having some logical set of rules and operations that have to be defined by their concrete implementation regardlessly of which programming language is getting used. In Java, inside java.util package there is a “List” interface which is nothing but an abstract model of List Data Structure whereas, ArrayList and LinkedList are two concrete implementations of List ADT.

Algorithm: An algorithm is a step by step unambiguous instructions to solve a given problem. There are two main criteria for judging the merits of an algorithm.

  1. Correctness: Is it solving the problem in a finite number of steps. Correction can be measured by comparing the expected and resulted output.
  2. Efficiency: How much resources does it take to solve the complete problem?

Algorithm Analysis: Algorithm analysis is nothing but finding the complexity(time and space usage) of an algorithm in terms of input size, being machine independent and considering just basic computer steps. It is the only way to find out the efficiency of an algorithm so that it can be compared with others to choose the best. Complexity is considered in terms of processing time(Rate of growth), memory usage, developer efforts etc.

The rate of growth is a function which defines at what rate the running time increases as the input size increases. Let’s take an example, Suppose in a party, one guest consumes 2 bottles of water. The number of water bottles needed will be, twice the number of guests will come. Here the rate of growth of water bottle consumption is 2n, where n is the number of guests. Rate of growth function f(n) can be defined as  f(n) = 2n.

Why  Algorithm Analysis: There may so many ways to solve a particular problem. But we need the most efficient solution out of all and to get which solution is most efficient, the analysis is needed.

Types of analysis: From algorithm analysis, we basically want to know that with which input the one algorithm takes the least time and with which it takes the longest time. Based on algorithm’s measurement is divided into following 3 types.

  • Worst case: Defines the input for which the algorithm takes a long time.
  • Best case: Defines the input for which the algorithm takes a least time.
  • Average case: Defines the input for which the algorithm takes less than longer time but more than the last time.

Let’s say there are two packets of goodies.
One packet has between 10 and 20 goodies in it (we’ll call this Packet A).
One packet has between 30 and 40 goodies in it (we’ll call this Packet B).
You can pick only one of them but you don’t know which packet is Packet A or which packet is Packet B.

Here, for you, the worst case will be, if you choose Packet A and the best case will be if you choose Packet B.

Asymptotic Notation: Asymptotic notation is kind of syntax or units that are used to express the best, worst and average cases of an algorithm.

  1. Big-O Notation(Upper Bound Function): This notation represents the upper bound of an algorithm which means in any case running time will not be more than this.

In General, Big-O is used to represent the worst-case efficiency of an algorithm where lower bound is not considered. It is represented as f(n) = O(g(n)) where, g(n) is the function which represents the upper bound of f(n).

   General Rule of Big-O notation:

  • Ignore Constants: Example, the upper bound of 4n is n.
  • Ignore lower order terms: Example, g(n)  of function f(n) = n2 + 2n will be n2 (or any value bigger than this), as n2 will be contributing more than 2n for reaching the worst case.

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In simple words, we have a complex function f(n) and a simple function g(n) and we want to find a constant c such as, when multiplied with g(n), the resultant value will always be greater than f(n) from some point n0 for all n>n0.

Question: Find Big-O of  f(n) = n2 + 5.

Note: n2 is the upper bound(contributing the most in rate of growth) of this equation. Let’s take g(n) = n2, but to prove f(n) = O(n2) we need to have some positive integer c and n0 which can satisfy  f(n) <= c*g(n). we can substitute any value of c that satisfy the condition. So, let’s put c = 2(or more than 2 will also be fine).

n2+5 <= c*n2

n2+5 <= 2n2

5 <= n²

Hence found, g(n) = n2 and Big-O of f(n) with c = 2 and n0 = 3.

Note: there can be any number of combination of c and n0. And if n2 is upper bounding f(n) then any value greater than n2 such as n3, n4  will also upper bound f(n) thus, they can also be big O of f(n) but we should always consider the tighter upper bound.

  1. Omega-𝛀 Notation(Lower Bound Function): This notation represents the lower bound of an algorithm which means, in any case, the running time can never be less than this. Generally, it is represented as f(n) = 𝛀(g(n)) where, g(n) is lower bound of f(n).

Here, we have a complex function f(n) and a simple function g(n) and we want to find a constant c such as, when multiplied with g(n), will lower bound the function f(n) from some point n0 for all n>n0. we can say f(n) ∈ 𝛀(g(n)) if there exists c>0 and n0 >0 such that f(n) = n0.

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Question: Find Big-𝛀 of  f(n) = n + 5.

Let’s assume g(n) = n and prove f(n) = 𝛀(g(n)) by satisfying, f(n) >= c*g(n) for some c > 0, n0>0 and n>=n0 .

n + 5 >= c*n

Here, we can substitute any value of c that satisfy the condition. But looks like 1 is the only value which can satisfy this.

n + 5 >= n

Hence found, g(n) = n and Big- 𝛀 of f(n) with c = 1 and n0 = 1 for all n > 1.

Notice: there can be any combination of c and n0. And if n is lower bounding f(n) then any value less than n such as logn, log(logn)  will also lower bound f(n) thus, they can also be big 𝛀 of f(n).

  1. Big-𝚹 Notation(Average Function): This notation represents the average time that can be taken by an algorithm. Generally, it is represented as f(n) = 𝚹(g(n)) where, O(g(n)) >= f(n) >= 𝛀(g(n)).

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Big-𝚹 notation defined as 𝚹(g(n)) = { f(n): there exist positive numbers c1, c2 and n0 such that  c1*g(n) >= f(n) >= c2*g(n) for all n>= n0}. Or in simple words, we have a complex function f(n) and a simple function g(n) and we want to find a constant c1 and c2 such as, when multiplied with g(n), will middle bound the function f(n) for all value for n >= n0.

Question: Find Big-𝚹 of  f(n) = n2 + 5.

Let’s assume g(n) = n2 and prove f(n) = 𝚹(g(n)) by satisfying, c1*g(n) >= f(n) >= c2*g(n) for some c1,c2 and n0 > 0 for all n>= n0

c1n2 >= n2 + 5 >= c2n2

Here, we can substitute any value of c1 and c2 which satisfies the equation. C1 = 5, c2= 1 and n0= 1 satisfying the equation.

Hence found, g(n) = n2 and Big-𝚹  of f(n) with C1 = 5, c2= 1 and n0 = 1 for all n>1.
In General, worst case is considered to tell the efficiency of an algorithm and Big-O is one used to represent that. Big-𝚹 is considered only when the Big-O and Big-𝛀 of an algorithm are same.


That’s all about the introduction of Data Structure and Algorithm but stay connected for next chapter “Linked List”. Happy Learning!! 🙂 

WWDC 2018 | Keynote |Quick Notes | 2 mins

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“Today is all about Software,” Apple CEO Tim said as he took the stage at WWDC 2018.

It all started with statistics.

  • 20 million iOS developers
  • 500 million weekly app store visits
  • 81% using iOS 11 where only 8% using latest Android
  • Developers earned 100 million through App Store


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  • New iOS 12 will be released as a free update, every model back to the 5S will get a performance boost.
  • ARKit, second generation, which included a lot of cool updates, most interesting is the ability for multiple users to observe and interact with the same environment from different angles.
  • Apple Screen time, now iOS 12 will tell you how much time you’re spending with your iPhone and which are the apps.
  • Do not disturb a lot of improvements, while you are sleeping will hide the notification, one step one time notifications.
  • Photos, with iOS 12 they have revamped it. Allowing more search options driven by AI, share the photos through iMessage.
  • Siri, it’s handling 10 billion requests per month and now Apple is allowing you to interact with it more, create shortcuts to trigger app features.
  • Animojis, more personal now. It’s super accurate, face-tracking and tongue tracking capabilities. Surely it will feel you very familiar.
  • Group FaceTime, now chat with 32 people at once with emoji, sticker, and other effects support.

iOS Apps updates

  • Stocks, new UI with better performance
  • Apple News app.
  • Apple iBooks getting a redesign and a new name.
  • Voice Memos, iPad getting it for the first time and recording will be now synced to iCloud.


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So far biggest functions of the Apple iWatch is fitness, now Apple adding more components which let you challenge your friends.

  • Automatic workout detection using your heart-beats(once you stop working out your heart rate decreases, so it will automatically stop).
  • Walkie-Talkie, Texting/phone are tough using watch screen so Apple added an instant audio messaging app called walkie-talkie (uses the wifi or cellular to interact with other devices).
  • Siri on Watch, allow third-party apps to show you more information. Now just lift your wrist and start talking it means no more “Hey Siri”.
  • Podcasts app is coming on your wrist.


4 Ways to Solve The Problem | Quick-Notes

Problem-solving requires two types of mental skills, analytical and creative. I know this sounds very high level So let’s talk about the basic fundamentals what generally I try to follow in day to day professional and personal activities.

  1. Listen carefully You need to pay very close attention to any information in the problem description. The optimal solution for a sorted vs unsorted array will be totally different so don’t miss anything.
  2. Brute Force Yes correct, Get the brute force solution as soon as possible, don’t think about the optimal solution. I always catch the first thought that comes to my mind. Don’t think about code, the algorithm just rough idea.
  3. Optimize Now it’s time to work on your Brute Force with some BUD (Bottlenecks, Unnecessary work and last Duplicated work) techniques.
    1. Remove the unused information.
    2. Solve it manually on paper with an example.
    3. Reverse engineer your thought process. HOW DID YOU DO?
    4. Make a Time VS Space trade-off.  CAN YOU REDUCE-IT MORE?
  4. Implement Congratulations now you have an optimal solution on paper. The last goal is to write beautiful, modularize code.

If you are trying to solve the problem in interview KEEP TALKING because your interviewer wants to hear how you’re going to approach the problem and it will make the interview more interactive.

Thanks a lot for reading the quick-notes!

Quick Notes | Swift classes into Objective-C Code when you have multiple targets.

How to use Swift classes into Objective Code when you have multiple targets.

For using Swift classes in Objective-C Code when you have one target in your app. We generally need to andimport TargetName-Swift.h next to add support in your Swift file you need to inherit if from NSObject or use @objc flag.

What if you have multiple targets in your codebase? As you cannot import, TargetNameA-Swift.h TargetNameB-Swift.h etc. In that case, you can tell the compiler that not to create Swift module specific to target change it to project name because the project will be same and unique.

For achieving this select your every target, Build Settings and change the build configuration.

Objective-C Generated Interface Header Name —> replace  $(SWIFT_MODULE_NAME)-Swift.h that is specific to the each target, with ​​​​$(PROJECT_NAME)-Swift.h

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Later import PROJECT_NAME-Swift.h in your Objective C code to make use of your Swift code.