This is where Node.js and ASP.NET come into the picture as two remarkable server-side languages for building enterprise applications.

In this post, I will be discussing the ongoing debate of Node.js versus ASP.NET in the developer community. The goal is to find out which comes out on top in a detailed comparison of both languages.

What Is Node.js?

Node.js, developed by Ryan Dahl in 2009, is a single-threaded, cross-platform, open-source, and asynchronous event-driven JavaScript runtime for building fast and scalable network applications.

It runs on Google’s V8 engine (JavaScript engine) and executes JavaScript code. It is suitable for building data-intensive applications, SPA, online chat apps, and video streaming sites.

Node.js is also very apt in handling concurrent requests effectively, as the cluster module of Node.js helps in load balancing all the active CPU cores.

Because Node.js runs on JavaScript, it’s popular among developers, since they don’t have to learn a new language from scratch. This saves considerable time by using the same coding language for both front-end and back-end development.

Companies using Node.js include Uber, Netflix, LinkedIn, Twitter, Trello, PayPal, NASA, eBay, Medium, GoDaddy, and WalMart.

With all this in mind, it’s now time to see some of the key features of Node.js.

Single-Threaded

Node.js operates on Single Threaded Event Loop Model architecture. The event loop mechanism makes the Node.js server more scalable by allowing it to perform all non-blocking operations smoothly. Unlike Apache HTTP servers, Node.js can handle multiple client requests.

Asynchronous

By default, Node.js APIs are non-blocking (asynchronous) in nature. In simple terms, if a client requests a server, then a single thread handles the request. If there is no database interaction with the request, the request is processed, and the client receives the response.

Event-Driven

Node.js has a notification mechanism called “Events” used to receive and track previous API requests from the server. The event-driven mechanism works similarly to the callback mechanism of asynchronous programming. Once the server is started by Node, it declares functions, initiates its variables, and waits for the occurrence of the event. The event module of Node.js has a class called “EventEmitter” that implements event-driven programming.

NPM

Node Package Manager (NPM) is the largest online repository for the JavaScript runtime environment Node.js. With over 1.3 million packages available in the npm registry, developers use npm to discover, develop, install, and publish node programs. At the same time, new organizations can manage private development effectively using npm.

Highly Scalable

The asynchronous nature and single-thread architecture of Node.js make it highly scalable. When a request arrives, the single thread starts processing it, the response is sent back to the client, and the cycle continues. Node.js uses child processes to partition the applications horizontally, which helps the organizations customize the app versions according to client preferences.

Cross-Platform Compatibility

Node.js apps are written in JavaScript and can be used on multiple systems like Mac OS, Windows, Linux, Unix, and mobile devices. A large number of developers write Node.js on OS X and then deploy it into Linux servers. In the Node.js community, Windows gets first-class support.

Performance

Node.js is built on Google Chrome’s V8 JavaScript Runtime motor, which promotes faster code execution. The V8 engines compile JavaScript code into machine code with the help of C++. The V8 engine makes the code implementation smoother and faster.

What Is ASP.NET?

ASP.NET (Active Server Pages Network Enabled Technologies) is a server-side, open-source web app development platform that helps developers build dynamic, data-driven, and interactive apps, websites, and services. It is an eccentric integration of JavaScript, HTML, and CSS.

.NET was built on Common Language Runtime (CLR) and allows developers to use .NET languages like C#, C++, VB.NET, etc. for writing the code. Unlike Python, Java, or PHP, ASP.NET uses compiler-based technology. The compiler gathers all the instances of code and compiles them concurrently. This makes the ASP.NET Core faster and more performant than other frameworks.

So let’s take a look at some of the core features of ASP.NET, used by companies such as SpaceX, Alibaba Travels, ROBLOX, MasterCard, Slack, Cognizant.com, Queue-it, Motorola Solutions, and ViaVarejo.

Supports Cross-Platform

ASP.NET apps can be easily deployed and run immediately on platforms like Linux, Mac OS, and Windows. With .NET, developers have the freedom of choosing their desired OS.

Comprehensive Development Environments

Developers can utilize an IDE (Integrated Development Environment) like Visual Studio for developing aesthetically amazing apps. IDEs provide a rich and dynamic environment for developers to build apps from scratch using drag-and-drop components.

Language Independence

.NET is known as the language-neutral framework. Meaning, developers can use various languages, like C#, for developing apps. They can also create dynamic applications like Starbucks, TrustPilot, Agoda, GoDaddy, etc. using those languages.

High Security and Performance

Developers are likely to agree that, for any software, performance is one of the crucial factors in app development. The ASP.NET Core and Kestrel Web Server have made the .NET framework one of the quickest, most responsive, and most lightweight frameworks available in the market. The new Kestrel Web Server provides asynchronous programming approaches that make the framework fast.

At the same time, Kestrel Web Server provides a unique identification of all the applications that are running on the ASP.NET framework, as .NET verifies the authenticity of apps before allowing them to run.

To learn more, consider reading “Beginning ASP.NET Security.” 

Support HTML5 Form Types

HTML forms allow users to enter the values via various input elements like text boxes, buttons, radio buttons, check boxes, drop-down lists, and more. After providing the values in the various fields, users need to click the submit button to send the data.

ASP.NET supports HTML5 form types. After incorporating the HTML form, additional coding is required to get and display the data on the browser entered by the user.

Unified MVC and Web API Frameworks

Before the development of the ASP.NET Core, developers relied on Model-View-Controller (MVC) frameworks for building web applications—using HTML and Web API to develop RESTful API via XML and JASON. The development of ASP.NET Core has simplified development by combining the MVC and Web API. Now instead of HTML, MVC always returns JASON data.

There is a new element in the ASP.NET Core called Razor pages, which helps in simplifying web UI development. It is a page-based coding module that extends the MVC framework to allow the abridgement of the controller and model features of the page.

Dependency Injection

Before the .NET Core, if the developers had to provide dependency injection in the applications, then they had to rely on third-party frameworks like StructureMap, AutoFactor, etc. However, with the introduction of the ASP.NET Core, this dependency on third-party frameworks died down as the Core has an in-built dependency injection that helps improve the testability and extensibility of the web apps.

Action Filters and Web Sockets

One of the principal features of .NET is Action Filters. These filters help the developers to implement functionalities like caching, authorization, error handling, or any custom logic that can be applied to an action or a controller without modifying the action itself.

ASP.NET supports Web Sockets, which are used to create web-based client-server apps and provide to and fro communications with the browser. Web Sockets are useful in developing real-time communication applications like chatbots, gaming apps, social feeds, etc.

Asynchronous via Async/Await

With the implementation of Async in all the .NET frameworks and third-party libraries, ASP.NET has splendid support for asynchronous patterns. The extensive use of asynchronous programming patterns in the new MVC and Kestrel frameworks has made the .NET Core faster in performance.

Now it’s time to move on to the next round of the Node.js versus ASP.NET battle. Let’s see which server-side language is better performing based on pros and cons.

Pros and Cons of Node.js

Pros:

• Developers don’t have to install external modules when using other apps.
• Developers can interact with other operating systems using a cross-platform library.
• Although it’s single-threaded, it can handle multiple core servers instantly.
• It has the support of a vast active developer community.
• It has fewer abstractions and uses an event looping mechanism.
• There is no buffering when using the platform.
• It serves both client-side and server-side applications.

Cons:

• The asynchronous nature of Node.js makes it challenging for developers to implement it.
• Its limited library support requires developers to integrate third-party libraries into their apps.
• Difficult code readability.
• It is difficult to fix bugs and maintain code.
• The architecture of the apps may get jumbled due to the presence of multiple microservices.
• Unstable APIs and callback issues.

Pros and Cons of ASP.NET

Pros:

• Applications are secured by the built-in per-application arrangement and Windows verification.
• It has a rich toolkit.
• Its just-in-time compilation, caching administrations, local optimizations, and early authoritative provide super execution.
• It is backed by Microsoft and provides better security and safety.
• It is cost-effective, simple to maintain, and easy to update.
• Its drag-and-drop IDE is easy to use.
• It has generic error handling capabilities and uses multiple threads.

Cons:

• Initial compilation is time-consuming.
• Upgradation of the older apps of the .NET framework is a very hectic process.
• It has few third-party libraries and has manual configurations.
• It is less portable compared to Node.js.
• No support for Java.
• The core of the ASP.NET is raw, and its documentation is not detailed.

Node.js Vs ASP.NET: A Detailed Comparison

To better understand this high-intensity Node.js versus ASP.NET battle, let’s compare these two frameworks based on the following parameters:

So, Who Won the Battle?

The discussion of Node.js versus ASP.NET will be going on for years to come, as to which of the two is the best framework for custom software development or to build enterprise applications. From the parameters I have considered, I would say that .NET is best suited for large-sized applications, whereas for small and medium-sized apps and services, Node.js is the best choice.

It’s hard to tell which is better overall between the two as the advantages of both frameworks compensate for their limitations. Even though ASP.NET has high performance compared to Node.js, the light weight of Node.js gives .NET tough competition.

Ultimately, the framework selection should depend on your organization’s requirements, keeping in mind both present and future aspects of the project.

The post Node.js Vs ASP.NET – Battle of Two Server-Side Languages appeared first on Simple Programmer.

As a newbie Java programmer, you might want to know how you can build a large application without using tons of similar code that can exhaust you.

public class User {

    @TestPath(field = TestFieldId.FIRST_NAME, readable = "user first name")
    private String firstName;

    @TestPath(field = TestFieldId.LAST_NAME, readable = "user last name")
    private String lastName;

    @TestPath(field = TestFieldId.DATEOFDATE, readable = "user date of birth")
    private LocalDate birthDate;

}

ValidationRule rule = DOOV.when(userDateOfBirth.ageAt(today()).greaterOrEquals(18)).validate();

// Execute the DSL on the model
DslModel model = new SampleModelWrapper(sampleModel);
Result result = rule.executeOn(model);
if (result.isFalse()) {
  // do stuff on the model that didn't validate
}

MappingRegistry mappings = mappings(
  map(userFirstName, userLastName)
    .using(biConverter((first, last) -> first + " " + last))
    .to(accountFullName),
  map(userDateOfBirth)
    .using(date -> Years.yearsBetween(date, LocalDate.now()))
    .to(accountAge));

DslModel model1 = new SampleModelWrapper(sampleModel1);
DslModel model2 = new SampleModelWrapper(sampleModel2);
Context context = mappings.executeOn(model1, model2);
// do stuff with model2 new values

ValidationRule rule = DOOV.when(userFirstName.isNotNull().or(userLastName.isNull())).validate();

assertThat(rule).validates(model).hasFailedNodeEmpty();

class Destination {

  @JMap
  String id;
  @JMap("SourceField")
  String destinationField;
  String other;
  // getter and setter
 }

 class Source {
   String id;
   String SourceField;
   String other;
   // getter and setter
 }

<jmapper>
  <class name="it.jmapper.bean.Destination">
    <attribute name="id">
      <value name="id"/>
    </attribute>
    <attribute name="destinationField">
      <value name="SourceField">
    </attribute>
  </class>
</jmapper>

JMapperAPI jmapperAPI = new JMapperAPI()
    .add(mappedClass(Destination.class)
             .add(attribute("id")
                     .value("id"))
             .add(attribute("destinationField")
                     .value("SourceField")));

public class Car {

    private String make;
    private int numberOfSeats;
    private CarType type;

    //constructor, getters, setters, etc.
}

public class CarDto {

    private String make;
    private int seatCount;
    private String type;

    //constructor, getters, setters, etc.
}

@Mapper
public interface TestMapper {

    TestMapper INSTANCE = Mappers.getMapper( TestMapper.class );

    @Mapping(target = "seatCount", source = "numberOfSeats")
    TestDto testToTestDto(Test test);
}

@Test
public void shouldMapCarToDto() {
    //given
    Car car = new Car( "Morris", 5, CarType.SEDAN );

    //when
    CarDto carDto = CarMapper.INSTANCE.carToCarDto( car );

    //then
    assertThat( carDto ).isNotNull();
    assertThat( carDto.getMake() ).isEqualTo( "Morris" );
    assertThat( carDto.getSeatCount() ).isEqualTo( 5 );
    assertThat( carDto.getType() ).isEqualTo( "SEDAN" );
}

<dependency>
  <groupId>org.modelmapper</groupId>
  <artifactId>modelmapper</artifactId>
  <version>3.0.0</version>
</dependency>

// Assume getters and setters on each class
class Order {
  Customer customer;
  Address billingAddress;
}

class Customer {
  Name name;
}

class Name {
  String firstName;
  String lastName;
}

class Address {
  String street;
  String city;
}

// Assume getters and setters
class OrderDTO {
  String customerFirstName;
  String customerLastName;
  String billingStreet;
  String billingCity;
}

ModelMapper modelMapper = new ModelMapper();
OrderDTO orderDTO = modelMapper.map(order, OrderDTO.class);

Mapping.from(Customer.class)
    .to(Person.class)
    .omitInSource(Customer::getAddress)
    .omitInDestination(Person::getBodyHeight)
    .reassign(Customer::getTitle)
        .to(Person::getSalutation)
    .replace(Customer::getGender, Person::getGender)
        .withSkipWhenNull(Gender::valueOf)
    .mapper();

class BasicPerson {
  private String name;
  private int age;
  private Date birthDate;
  // getters/setters omitted
}
class BasicPersonDto { 
  private String fullName;
  private int currentAge;
  private Date birthDate;
  // getters/setters omitted
}

  mapperFactory.classMap(BasicPerson.class, BasicPersonDto.class)
   .field("name", "fullName")
   .field("age", "currentAge")
   .register();

Selma

@Mapper
public interface SelmaMapper {

    // Immutable mapping
    OutBean asOutBean(InBean source);

    // Update graph
    OutBean updateOutBean(InBean source, OutBean destination);

  SelmaMapper mapper = Selma.mapper(SelmaMapper.class);

    OutBean res = mapper.asOutBean(in);

    // Or
    OutBean dest = dao.getById(42);

    OutBean res = mapper.updateOutBean(in, dest);
    // res is the value for the bean destination

<dependency>

    <groupId>com.github.dozermapper</groupId>

    <artifactId>dozer-core</artifactId>

    <version>6.5.2</version>

</dependency>

<mapping>
  <class-a>yourpackage.SourceClassName</class-a>
  <class-b>yourpackage.DestinationClassName</class-b>
    <field>
      <a>yourSourceFieldName</a>
      <b>yourDestinationFieldName</b>
    </field>
</mapping>

SourceClassName sourceObject = new SourceClassName();
sourceObject.setYourSourceFieldName("Dozer");

Mapper mapper = DozerBeanMapperBuilder.buildDefault();
DestinationClassName destObject = mapper.map(sourceObject, 
DestinationClassName.class);

assertTrue(destObject.getYourDestinationFieldName().equals(sourceObject.getYourSourceFieldName()));

The post Top 8 Frameworks to Help Java Developers with Bean Mapping appeared first on Simple Programmer.

Perhaps, the answer depends on your purpose of learning, as you are about to choose between the two oldest programming languages still in mainstream use.

However, despite the similarities mentioned above, the truth is that Java and C are worlds apart. In this post, I’ll show you the key differences between them so that you can know what to expect from each.

The 10 Key Differences Between C and Java Programming Languages

C programming language is a general-purpose, procedural programming language that supports structured programming, recursion, and lexical variable scope with a static type system. At present, it’s the most famous and fundamental language. Dennis Ritchie developed it at the Bell Lab in 1970.

On the other hand, Java is an object-oriented, interpreted, high-level language designed by James Gosling. Java is famous for its platform independence behavior and other uses like desktop computing, mobile app development, games, and numerical computing. As a result, it’s one of the most influential programming languages of this time.

With these in mind, let’s now take a closer look at their key differences.

Architecture

C Programming Language is mid-level and combines both machine and high-level language. Since it is compiled, it converts code into machine language. Moreover, C is procedure-oriented and follows a top-down approach.

On the other hand, Java is a high-level, object-oriented programming language that transforms the code into machine language using a compiler or interpreter. In Java, codes transform into bytecode first, and then a virtual machine executes the bytecode. Thus, Java is an interpreted language, and Java follows the bottom-up approach.

Memory Management

C supports user-based memory management, while Java uses a garbage collector.

Java has automatic memory management functionality. When a program executes, it uses the memory in various ways. For example, objects live in the “Heap” part of the memory, which is involved in garbage collection. This assures that the heap has free space; it finds and deletes the object that can’t reach it.

In addition, JVM (Java Virtual Machine) checks the size when it allocates any object. JVM mainly differentiates between large and small sizes, but this differentiation also depends on the JVM version, garbage collector, etc.

On the other hand, C programming has numerous memory allocation and management functions. The function is located in the header file <stdlib.h>. The function void calloc allocates the array of number elements, void free releases the blocks, void malloc allocates the array and leaves them uninitialized, and lastly, void realloc re-allocates memory, extending it up to a new size.

Paradigms

There have been different opinions on designing a programming language since the beginning of software development. As a result, each language has significant rules, concepts, and principles—called programming paradigms.

Both Java and C are multi-paradigms. For example, C is a procedural, structured, and imperative programming language. On the other hand, Java is an object-oriented, generic, imperative, and functional programming language.

If you build an application and want it to be fast, you can choose C. But, you should go with Java if you wish to have portability with a similar amount of speed.

Variable Declaration

C declares variables at the top of a block, but Java can declare anywhere. Again, C uses a free() variable to free up any variable, allowing deallocation of the memory block, and Java uses a garbage collector compiler.

After declaring a variable, Java sets bits in memory for that data type and allocates the name. Therefore, Java needs to declare the data type for further use and representation.

In the C programming language, you should declare a variable before its use. Unlike Java, C doesn’t allocate memory while declaring variables. Notably, the C language has three types of variables: Local, Global, and Static. In addition, Java doesn’t require pointer syntax, while C explicitly handles pointers.

C Variable Declaration:

#include <stdio.h>

void function()
{
int x = 10; // local variable
}

int main()
{
function();
}

Java Variable Declaration: 

String name = “Alena”;
System.out.println(name);

Functions

A group of statements that perform together is a Function. In C programming, it’s called Function, while in Java, Functions are known as Methods.

The Java method is a code called by its name, but it’s associated with any object. You can pass parameters to methods and get some return value from them, but they will always be associated with some objects. Java supports exception handling.

In comparison, a function in C is just a piece of code that you can call anytime by its name and pass parameters to. You can also get the result from any function. The C standard library has various built-in functions like main(), strcat(), memcpy(), etc. C doesn’t support exception handling, for which it often has issues with program flow maintenance. Java supports method overloading, while C doesn’t support it.

Function declaration in C:

return_type function_name( parameter list ) {
body of the function
}

Method declaration in Java:

returnType methodName() {
// method body
}

Speed

The speed efficiency of a language depends on its usage. Primarily, the C language is developed for machine preference, so the code directly goes into the machines.

On the other hand, Java requires a Virtual Machine to transform bite codes into machine language and then deliver it to the machine. It adds an extra process and time. So, in that case, C is faster than Java.

Java is faster than C at runtime in only a few rare use cases because of its memory allocation. Java allocates the heaps separately, providing flexibility on data structure and automated garbage collection, which is above the level compared to C.

Security

In the case of security, memory corruption is the biggest category of high-security factors. Unfortunately, Java doesn’t have any analog rules because of its type system that prevents memory corruption—which becomes harder in C.

Both C and Java have some rules in privilege escalations. However, while Java has an internal privilege system, C doesn’t support it. As a result, you get static data hiding in C and private data hiding in Java.

If you choose between Java and C for a plugin inside a web browser, you should pick Java because Java often releases a vast number of security patches at a time.

Object Management

C offers manual object management while Java has automatic. C operators can manually create and destroy objects. On the other hand, Java largely depends on the garbage collection process for this job, and it takes some time to collect. But you cannot afford the risk of accidentally doing memory management in Java during a critical section.

Compilation

As you already know, C is a compiled programming language, and Java is interpreted. Likewise, C directly converts codes into machine language, while Java transforms codes into bytecode first, then converts this bytecode into machine language. Therefore, compiled languages tend to be faster than interpreted languages, though their platform dependency is questionable.

Learning Curve

The learning curve of a new language depends on the previous programming experience of the learner. If you are starting fresh, C should be the more straightforward language, as it has fewer concepts to learn, so you can catch the idea quite quickly and in a short time.

On the other hand, as an OOP, Java offers numerous features and can require a longer period to get your hands on all functionalities.

C vs. Java: Which One to Choose First?

It’s wise to start learning an early language because the current languages are based on early language syntaxes. Likewise, Java has derived its syntax and several features from C and C++.

As C programming has fewer features, less complexity to learn, and is less prone to errors, it’s wise to get your hands on C programming first. Then, later on, you can move to learning Java and other languages like C++, C#, Objective-C, or Python.

Learning C, you would have to learn more programming as you deal with the lower-level language of computer science and software development. Being object-oriented programming, Java is widely used for developing projects and other programming paradigms. It is also one of the highest-paying programming languages in the current world. Therefore, ultimately, you should choose the one that suits you.

The post C vs. Java: The 10 Key Differences appeared first on Simple Programmer.

Software applications are constantly evolving, and technological innovation further bolsters this development. Standard software practices in use today might no longer be applicable in the next five years.

The post The Top 10 Software Development Trends To Watch In 2022 appeared first on Simple Programmer.

IT architecture is a broad term. It includes enterprise architecture, infrastructure architecture, and solution architecture:

• Enterprise architecture describes a company’s IT system from the business goal perspective and unites people, processes, and technologies.
• Infrastructure architecture represents the entire structure of IT solutions to organize work (data centers, servers, network, custom applications, and so on).
• Solution architecture is applied to develop new software for a particular task.

In this article, I will focus mostly on solution architecture and solution architects. So let’s take a look at what IT architects are responsible for and why you absolutely need one on your project.

IT Architecture in More Detail

For comprehensive IT architecture planning, a crucial aspect is the planning of a foundation—platforms (hardware or cloud providers), external infrastructure (servers, network), and internal infrastructure (delivery of software solutions, their placement, and establishment of communication and interaction).

For example, a company creates a service allowing travelers to book flights, hotels, and taxis. An IT architect’s task is to analyze what tools, programming languages, platforms, and APIs to choose; how long the development will take; and how the audience will use the product, i. e., what devices and platforms they can access it from.

If you’d like to learn more about how the work of IT architects makes products user-friendly and accessible to end-users and allows all technologies to work together accurately and properly, I recommend Software Architecture in Practice by Len Bass, Paul Clements, and Rick Kazman.

Core Processes of Solution Architecture

Well-elaborated solution architecture allows IT specialists to develop a product on time, within the budget, and in line with business requirements. It helps them avoid such difficulties as incompatibility of the technologies used or the impossibility to scale or modify the software. In situations involving poorly elaborated IT architecture, companies have to redevelop programs and systems completely.

Well-designed architecture also makes it possible to more accurately plan the time required to develop and deliver the final product or its parts. It gives sufficient flexibility to development processes and the ability to parallelize these processes, reducing the complexity of understanding individual modules and services.

With this in mind, let’s now take a closer look at the processes an IT architect follows.

Compliance of New Software With the Corporate Environment

When IT architects start their work, they undertake a prior study of the systems within the corporate environment so that the new program syncs with it and the systems don’t come into conflict with each other.

Selection of Technologies for Project Development

Specialists consider the latest software development technologies when creating an IT architecture. They analyze what platforms, programming languages, ​​and tools are suitable for a given project.

To perform such an analysis, an IT architect needs a technical background and programming experience. As a rule, at least five years of development experience is required. Over this time, a programmer manages to work on many various projects and knows different software development technologies.

Meeting Non-Functional Requirements

Every product has non-functional requirements specifying software characteristics: security, performance, user-friendliness, scalability, and so on. The IT architect is supposed to analyze these quality attributes and make sure that the project developed on the basis of the proposed architecture will correspond to them.

Even if it is impossible to predict the need for scaling at the initial stage, the IT architect creates a plan and strategy for the development of a sufficiently flexible infrastructure to automatically manage the expansion process.

Every program is based on the architecture that supports it. As a rule, there is no need to design and document architectural solutions for simple applications because software is often developed according to templates.

However, when it comes to a unique, complex program that needs to be implemented within a large organization’s corporate system, IT architecture must be well-thought-out and accurately documented.

Responsibilities of an IT Architect

If IT architecture is a kind of a frame for an application, it follows that an IT architect is a specialist who builds it. They work out the design of a program, its main parts and interfaces, so that the software is interoperable with external systems. This involves several responsibilities, as listed below.

Analyze the Requirements

Solution architects start their work long before the development process begins, looking for technologies that fit the business.

As I mentioned above, architects take care of the functional and non-functional peculiarities of the system in order to create a successful product. They assess the correctness and feasibility of the requirements and the possibility to meet them within a reasonable time and the allocated budget.

Create a Prototype

IT architects also analyze the technological environment and the сompany’s profile, document the requirements, and create a prototype of an architectural solution.

These specialists share the architectural vision of the project with developers, monitor the process, and support employees at the stage of product development. They fix technical issues, if there are any, and take part in subsequent program updates.

Anticipate Risks

When working on the program design, an IT architect not only creates a solution for the implementation of the initial idea but also anticipates possible risks and restrictions associated with the non-functional product qualities.

For example, if the application isn’t scalable, the money allocated for development is likely to be wasted. If requirements change and this may affect the original design, an architect tries to prevent their negative impact on software performance, security, and other qualities.

To carry out this large-scale job, IT architects need a wealth of experience in programming and business analysis as well as knowledge of modern technologies and Agile methodologies. It can be said that the position of an IT architect is the next step in the career ladder of a tech lead, team lead, or experienced developer.

What Projects You Need an IT Architect For

As a rule, the need for an IT architect arises in large projects with several technical teams (front-end developers, back-end developers, and DevOps engineers). This specialist is also called on when complex non-typical software is being developed. Template development projects—an online store, for example—can do without an architect.

Involving an architect at the start of a small-scale project or startup is mistakenly considered to be unimportant. As a result, after the minimum viable product is completed, the product goes through a full beta testing phase, and new large-scale functional and non-functional requirements appear, it is often too expensive or even impossible to change the system.

This occurs due to the complexity of modification and the presence of hard dependencies, poor testability with no possibility of testing individual parts of the product, poor monitoring, i. e., control of internal and external processes, and other factors.

In global terms, an IT architect is necessary to design an efficient IT solution that meets business goals. Otherwise, the team risks developing a product that won’t be able to work for clients or scale to the full extent and will have to be redone. In fact, these are double costs. An IT architect will help avoid these unforeseen issues in a project.

The IT architect considers rapidly changing technologies and the increasing complexity of systems and can work out strategically important points, find beneficial solutions, and present a general vision of a product to developers and customers. Thus, the customer knows what to expect, and programmers understand how to create the product.

As for large-scale and complex projects, especially with a little-known subject area, an architect has an important additional objective: to define the most atomic parts of the project with a limited area of ​​responsibility. Thus, specialists get a clear understanding of all the processes of development, testing, and further support of the product and its individual modules.

To Build a Solid Product, You Need an Architect

The value of solution architects is that they lay the foundation for the future product. This allows the team to attain coherence between requirements and tech solutions.

As companies strive to keep up with the emerging technologies and build reliable high-quality applications, they need specialists who are aware of how to transform technical know-how into concrete business results. With an IT solution architect, the project has a better chance of a successful launch.

Is it possible to write code without considering the IT architecture? Of course it is, but it’s risky because of the number of things that could go wrong. Without an architect, a project risks delays and unforeseen costs. Figuratively speaking, without IT architecture, the planned skyscraper risks becoming a two-story building.

With a good architect, your project is sure to succeed.

The post Why Is an IT Architect Needed on a Project? appeared first on Simple Programmer.

Cloud computing enables you to access the remote server managed by your cloud service provider, and to use these on-demand remote data centers, you only need an internet connection. Cloud computing enhances your data storage, networking capabilities, and development tools. These resources are available to use on a subscription basis, depending on your usage.

Besides introducing cloud solutions to your company, you should aim to integrate different technologies such as artificial intelligence, Big Data analytics, and machine learning. These tools will improve and automate your business and speed up your business activities and tasks because of their heavy storage space and computational power.

Let’s walk through what cloud computing can do for you and how to visualize the right cloud computing architecture.

What Does Cloud Computing Involve?

There are three types of services that cloud computing offers you:

• Software as a Service (SaaS) – You can also refer to this service as cloud application services. You can directly run this application on your web browser and thus save time you would’ve needed to download and install the software.

• Platform as a Service (PaaS) – Similar to SaaS, this service also offers remote access to the application. The main difference is that it offers a software creation platform and tools.

• Infrastructure as a Service (IaaS) – This service manages application data, runtime environments, and middleware.

Let’s have a look at how these various cloud computing services are implemented in an organization’s cloud infrastructure.

What Is Cloud Infrastructure?

Cloud computing infrastructure allows you to perform cloud computing by offering a huge amount of software and hardware. The infrastructure includes networking, computing power, and storage. Furthermore, it also provides access to the user interface.

The interface works as a platform for the user so that they can access virtualized resources. These resources represent the physical infrastructure containing network switches, servers, storage clusters, and memory as the components.

Physical infrastructure and cloud infrastructure offer the same capabilities. However, with the cloud you receive additional benefits including greater flexibility, ownership at cost, and scalability.

Benefits to Visualizing

Creating a visual representation of your cloud infrastructure is a great way to document complex systems within your organization. These serve as great architectural diagrams to plan, organize, and manage your entire infrastructure.

Security Visualization

When you have a public cloud, managing the traffic becomes necessary. Creating a secure network is a complex task, but having the ability to visualize and map the network will transform the complex console parameters. With thousands of setting options, you can secure your open ports through TCP, IP address, and egress ports. Further, it will enable you to monitor your team members instantly.

Visual Communications

Visual aids can help you improve the internal and external communication of an organization, as visualization helps you to understand complex data with the use of org charts. You can use these charts to streamline organizational and supervisory communication.

Doing so helps employees recognize who they will report to and how the information will flow along the organizational structure. The org chart defines the business structure, responsibilities, roles, and hierarchy.

Troubleshooting

When solving a problem in a business environment, you need instant solutions. For example, if your team added new infrastructure code collapsing the network, restoring it will save you from loss. Having an infrastructure diagram through a list of valuable resources will help you compare the code changed by the team. This way you can troubleshoot the problem and rapidly restore the systems.

You can also integrate a configuration management tool that determines changes and highlight the name of the person who made these changes. Visualization at this point helps you see the big picture about the entire project.

Faster Onboarding of Staff and Contractors

Onboarding new employees can be a difficult task because you have to make them understand the business goal and keep them on the same track as other performing employees. While onboarding, you provide new staff with training resources and information. The better your new staff and contractors understand their responsibilities and roles in the organization, the more effectively they can contribute.

The traditional onboarding process may take up to 12 months, which is a significant amount of time. However, with visualization you can boost the onboarding process and retention rate. The visual representation will transform knowledge and training resources into comprehensive diagrams, allowing you to engage new employees in a way that offers them the bigger picture.

Accuracy

Without accuracy, documents are useless, whether it is a cloud diagram or a traditional flowchart. You may miss recently modified resources without an auto-generating infrastructure. The process grows more complicated if there is a massive team on a cloud because of the difficulty you may face when accommodating every member of the team with appropriate resources.

With visualization, IT teams can generate a visual and interactive overview of the cloud resources. So instead of analyzing all the resources, you can generate a diagram to equip users with valuable data. Furthermore, visualization removes the number of manual errors as well. That means everything you see on the diagram will be running.

Highlight Anomalies

Visualizing your cloud system for the first time includes unexpected problems. New test environments, open ports, and duplicated resources may cause numerous issues after the developing stage. Identifying and solving these problems manually is demanding. However, you can visualize the infrastructure and identify these problems through the automated diagram.

Reporting & Governance

Visualizing the cloud system enables you to document the construction of the platform and provides numerous benefits for storing and extracting accurate documents. The advantages of visualizing diagrams include the generation of the precise governance report. Moreover, with the visual representation, you can explain management reports to the stakeholders.

Types of Cloud Computing Architecture Diagram

A cloud computing architecture diagram helps you in documenting and visualizing the cloud computing architecture. It enables better communication between stakeholders.

The diagram consists of two components; a front-end platform and a back-end platform. The cloud infrastructure is the front end facing the network or internet. The back-end platform includes different devices connected to that cloud server. Both these components work together to describe and streamline the connection. Here are the components of cloud architecture:

• On-Premise Resources – It indicates that a company manages and keeps its IT infrastructure on-site.

• Cloud Resources – This type of architecture offers an organization with a private network to manage its infrastructure.

• Software Components and Services – This type of architecture diagram represents how various software systems employed in a business interact with each other.

• Middleware – A middleware connects the application with other applications, databases, and software.

With these in mind, it’s now a good idea to take a look at some examples of visualizing.

Examples of Visualizing

An appropriate visualization tool offers you an in-depth understanding of the data. When you comprehend the data better, you can recognize the patterns using different types of charts and graphs. For instance, charts can provide information about relationships, KPI, distributions, comparisons, or compositions. Below, you will find some tools for visualizing your data.

AWS

Using AWS cloud, you can store and access your data and create a backup on web applications. The Amazon Simple Storage Service offers an interface for storing and retrieving a high amount of data from any location and time through the internet.

Unlike the traditional hosting model, AWS helps you change the traffic by scaling the web application. With this tool, you ensure more security to your model and lock down the hosts.

Azure Architecture

Microsoft Azure architecture contains numerous servers and network hardware. This facilitates you to host complicated applications and control operations and configurations through virtualized hardware on Azure servers.

Google Cloud Platform

The Google Cloud’s Architecture enables you to design a cloud development system according to your business needs. Google Cloud offers a platform for hosting, serving, and protecting customers. Their aim is to empower their users with complete data control and management. Furthermore, the tools also help you understand methods to efficiently use the platform.

IBM Cloud

IBM Cloud is redefining the term cloud by offering Infrastructure-as-a-service, more than what it was previously. IBM Cloud not only delivers cloud services and data centers, but it also provides a lot more than that, namely solutions for complex problems that aren’t available with the most advanced application.

Learn and Use Cloud Computing To Transform Your Business

Cloud computing is transforming the way in which companies perform their tasks. It offers you a remote platform for data storage and streamlining business tasks.

In order to successfully transform your business to cloud technology and growth, it is essential to identify the type of cloud computing that suits your business. The best part about shifting to cloud services is that they still have a lot to offer with new opportunities. Therefore, staying updated with the technology will drive business results.

The post A Guide To Visualizing Your Cloud Infrastructure appeared first on Simple Programmer.

Solutions architects play a significant role in designing system architecture, with an understanding of technical standards like platforms, technologies, and infrastructure. Their analysis directly helps to successfully define the product, perfect the design, and provide on-time, cost-efficient delivery and lifetime support. Therefore, they have to understand the technology goals of the organization along with the client’s business needs.

To make a software project successful, software architects must follow a set of basic rules, guidelines, and principles. These are the three key principles of software architecture that you should never forget.

1. SOLID Principles

SOLID is an industry-standard framework or a set of principles every developer must follow while working on Object Oriented Programming System (OOPS) projects.

Introduced for the first time in a technical paper—Design Principles and Design Patterns by Robert C. Martin—these five principles are essential for object-oriented design and architecture. SOLID principles focus on enhancing the understandability of software design, boosting scalability, and maintenance.

The underlying SOLID principles are:

• Single Responsibility Principle – This principle states that each module or class should be exclusively responsible for only a single functionality. The original principle states that responsibility is a “reason to change” and each class should have only a single reason to change.
• Open-Closed Principle – The open-closed principle states that each software entity should be open for enhancements and extensions, without having to modify them. This is in line with the polymorphism concept followed by OOPS.
• Liskov Substitution Principle – This principle states that each derived class should be the substitute for its base class. To illustrate, let’s take an example. If A is a subclass of B, then objects of type B may be substituted with objects of type A. Altogether, it means that objects within a software program should be replaceable with examples of subtypes without meddling with the program.
• Interface Segregation Principle – This principle is one of the core things you must follow for enhanced efficiency. It states that existing interfaces should not be topped up with additional functionality by appending new methods into them. What it means is that each interface must be client-specific, and each class should implement multiple interfaces.
• Dependency Inversion Principle – This principle states that a high-level module should never depend on a low-level module. Both modules should depend on abstraction. Also, abstraction should not depend on details, but the details should depend on abstractions. By following this principle, one can remove the dependencies between higher-level and lower-level modules by introducing an interface abstraction.

With continuous use and following the guidelines, SOLID—all five principles together—will give a scalable, modified, tested, and reusable software solution.

2. Principles of Economics

These principles focus on achieving cost-efficiency in a software development project. Essentially, they consist of the following:

Opportunity Cost Principle

This principle is based on the common economic premise that each alternative has the inherent value that we place on that particular alternative. This value can be the cost of the alternative chosen and the benefits thereof. Opportunity costs define what we have to give up in getting that value. For the highest value, we should always opt for the option that offers maximum benefits at the lowest cost.

In the software architecture context, this principle means that one should always weigh down different options against one another. One should only choose a path that adds maximum value to the project.

Last Responsible Moment or Cost of Delay Principle

This principle states that no important action or decision should be delayed until the moment when it is absolutely required. This principle allows developers to get an idea of all crucial alternatives and broaden the perspective to make an informed decision.

Some say that this principle can lead to risks. Still, one can follow this principle by building proof of concepts (PoCs) for demonstrating to the stakeholders the advantages of delaying the decision and the benefits of using an alternative course of action.

#3 Principles of “Least”

These principles focus on least or minimalism philosophy and are essential for managing various aspects of a software development project. Essentially, the “Least” principles include the following:

Principle of Least Astonishment

This principle is also known as the “least surprise” principle and recommends that a solution should not surprise or astonish a subject matter expert when they are introduced to it the first time. This principle focuses on harnessing the existing knowledge of the target audience to eliminate the need for learning when using a particular solution.

Principle of Least Effort

Also known as Zipf’s law, this principle states that every human tends to follow the path that requires the least effort. This means that subsequent developers should introduce no change in the software unless there is an easier way to do the same thing.

In principle, this means that if a solution to perform a task is found, there is no need to improve the existing method.

Simplify Your Software Development Process

Software architectural principles can streamline the entire project and improve the quality of your decision making. By following the above-mentioned core principles, you can be sure of achieving your long-term goals without deviating from your core objectives.

The post Software Architecture Principles That Every Programmer Should Follow appeared first on Simple Programmer.

Architecture describes the building blocks of our software and how they work with each other. If every team member builds the blocks as he or she thinks best, it may work, but it will lead to different styles and concepts used throughout the code base. Chances are that this will quickly lead to unmaintainable code.

If, instead, we have an agreed-upon set of architecture rules, the building blocks will be shaped to fit together and be much easier to extend, test, and maintain.

In my experience as a senior member/architect of a development team, I found it necessary to define a set of architecture rules from the start (yes, even when doing Scrum), but then to get into a mode of continuous decision making together with the team.

This way, there’s no danger of becoming an ivory tower architect who decides everything for the team but who is not respected by the team. You want the team to participate in important decisions, and not feel left behind.

Here’s how I drive architecture decisions in my projects by taking responsibility while working with the team.

Collect Issues and Ideas

First of all, we need a place to collect architecture issues and ideas. This is usually a structured list in form of table with these columns:

• the date the issue was raised
• the name of the person who raised the issue
• a keyword describing the context of the issue in a single word, for ease of indexing
• a short text description of the issue, potentially with links to other material
• the name of the person who will take responsibility for the issue (initially empty)
• a status flag, e.g., “open,” “in progress,” or “done”

This list is the repository of architecture issues, and every person on the project should know it. It’s accessible to all and editable by all. Everyone is invited to add their issues and ideas concerning the architecture to this list.

Usually, not everybody on a team will contribute to this list. Some are content to let others discuss and make decisions, which is totally fine. Often, these are the more junior developers who still lack confidence in their own skills, but they’ll get there.

There are always some developers, however, who will gladly take the chance to contribute ideas about how to do things better and point out the issues they have with the current state of the architecture. Those ideas and issues are what’s going to drive the evolution of our software’s architecture.

Don’t forget to contribute to this list yourself in your role as a senior developer or architect. You want to bring in your experience, after all.

Actually, you should even maintain an architecture issue list if you’re the only person contributing to it or if you’re doing a project on your own. If the list is only in your head, chances are that it will feel like a burden because you’re afraid you’ll forget something. Or you will actually forget something. Your future self will thank you for everything you write down.

Establish a Community of Practice

Collecting issues and ideas alone doesn’t cut it, though. We need to talk about them and make decisions based on them in a structured manner.

In our role as senior developer / architect, we could take the list, withdraw into the penthouse of our ivory tower, and decide on a course of action for each item. However, top-down decisions like that don’t sit well with everyone (and, to be honest, are probably not the best decisions all the time), so we should try to involve the team.

What I’ve successfully done in the past is to establish a community of practice (CoP) for architecture topics. The term “community of practice” is often used in agile projects to describe sub-teams that each drive a certain topic within the project, but it originates from even before agile became a buzzword.

A community of practice in the sense of this article is a group of team members who are interested in software architecture and are actively practicing software development. The “actively practicing” part is important because if they’re not developing software, they won’t know the consequences of any architecture decisions.

Once every two weeks or so, I schedule a meeting for this community of practice. I have a look at the issues and ideas on the list. Usually, a day before the meeting, I talk to everyone who’s contributed issues, so I can gain a better understanding of the issues. Then I decide which topics should be part of the meeting agenda.

It’s important to select the issues to discuss before the meeting. Otherwise, the meeting will likely degrade into an unproductive mob prioritization session.

The meeting is timeboxed, usually not more than an hour or one and a half. Also, each item to discuss is timeboxed so we have a clear-cut agenda.

Each item is then discussed in the group, and if all goes well, a decision is made for the benefit of all. Some items are settled then and there; others may require someone to follow up by evaluating something or talking to some other people. In this case, the item is assigned to a caretaker who follows up. The caretaker and status columns in the issue list are updated accordingly.

One point on the agenda should be to go through all items currently “in progress” to follow up on them.

Having decided on something usually feels rather good. No matter if everyone supports the decision or not, we’re making progress.

Document Your Decisions

This progress must be documented. We must be able to come back in a year and say, “Ah, yes, that’s why we’re doing this the way we’re doing it.”

There are few things as frustrating as discussing something and having to say “I remember we talked about this a couple of months ago, but I don’t remember what we decided back then.”

And let me tell you, this happens a lot to me. I have a chronically bad memory (or perhaps a chronically selective one).

Let’s call the documentation of our decision an “Architecture Decision Record” (ADR). That’s a term that has gained some traction since it was included in ThoughtWorks’ technology radar in 2016.

Essentially, an ADR is a structured document that describes why we have made a decision and what we hope to achieve with it. For example, an ADR may consist of these attributes (adapt this list to your needs as necessary):

• a unique number for easier reference
• a title
• the decision
• the reasons for the decision
• the goals we hope to achieve with it

The ADRs should be kept as close to the code base as possible so that they can be maintained in sync with the code and be part of our code review rituals.

With a well-kept list of ADRs available, we can easily travel back in time when we know we have discussed some topic already and re-evaluate our decision from back then.

Maybe the reasons for a past decision still hold. Sometimes, however, the reasons are not valid anymore because the context has changed or the goals we wanted to achieve with the decision have not been reached. In this case, we can decide on a different way of doing things.

Being able to refer to an ADR also allows us to quickly smother unproductive discussions in our CoP meetings. Just pointing at an ADR and saying “We have talked about this already” works wonders.

And When There Is No Consensus?

There are times when we keep discussing an architecture issue in our CoP meeting and we cannot agree on a course of action for dealing with it.

In this case, we still have a couple of options.

We can postpone the issue to the next meeting. This gives us and the rest of the team some time to think about it. Often, this will be enough to give us or our debating partner some inspiration as to how proceed with the issue. Perhaps we learn something new in the meantime that will help us.

If the matter is urgent and needs to be decided quickly, we can give in to our debating partner’s opinion and do it his or her way. Even if we think this is not the best way to do things, it might be better to do something than to do nothing. Just be sure to document the decision in the ADRs so we can get back to it should it become necessary.

If we really feel that our way is the way to go and disaster will strike if we do it differently, we can overrule the team with our experience. This obviously only works if we are respected enough within the team (or we have a role that gives us the needed authority). And even then, this might offend some people, but sometimes the decision must be made by an architect.

It’s nice if we reach consensus on architecture decisions as a team, but consensus isn’t necessary to successfully work together as a team. If we treat each other with respect while standing strong for some decisions and yielding for others, we can still deliver a well-architected piece of software.

Deliver Great Architecture

Life as an architect or senior developer in a software development team is a lot easier when you involve the team members in the process of making architecture decisions. The team members will feel their opinions are honored, and you spread the architecture knowledge through the team, avoiding architectural messes you would have to clean up later.

The steps of collecting issues, discussing them in a community of practice, and then documenting the decisions take only very little effort, so there’s practically nothing stopping you.

Once this workflow is incorporated into the every-day-life of a project, it will relieve you of the burden of having to decide everything on your own while helping the team to grow and to deliver architecturally sound software.

Start today.

The post Architecture Decisions in a Software Development Team appeared first on Simple Programmer.

However, despite all the emphasis these companies have placed on enhancing their products with machine learning, for most companies, building AI is still difficult and challenging.

Humans can learn almost anything instinctively and autonomously, by watching, reading, and experiencing new things, but setting up a machine learning system to do simple tasks is an incredibly difficult undertaking.

Besides a lot of expertise, you need computing power, data, and time, all of which equals money—money that companies with reduced financial resources simply do not have. The truth of the matter is, there is virtually nothing small about machine learning, AI, or big data, except the number of available experts.

The amount of data, storage capacity, processing power, and experts’ wages required all represent exponentially higher costs than any previous approach. When it comes to AI, you either “go big, or go home.”

The high cost of investment—be that in professionals, hardware, or software—like in any IT-related field, coupled with the scarcity of experienced industry-seniors, always results in a slowdown of advancement in the field and is often coupled with some impact on the consumer side.

Machine learning being a relatively young field, but with high consumer expectations, is certainly not the ideal scenario for its evolution.

Money, however, isn’t the only difficulty businesses face. Let’s take a look at the even deeper challenges and inefficiencies in the AI process and the potential ways to solve them.

Expertise Must Be Ph.D.-Level

While AI research has been going on for several decades, the most promising developments have occurred only in the last few years.

The main reason that machine learning is still in its infancy is due to basic research and development work that must be done.

The ability of a machine to learn anything depends largely, almost solely, on the accuracy of its underlying mathematical model, and developing a good mathematical model requires advanced understanding of arcane topics in linear algebra and calculus, among others.

Most of the available knowledge and intelligence around this topic currently exists only in academic research papers. Bottom line:— You need Ph.D.-level expertise to decipher it all, not to mention pull it off.

As previously hinted at, the number of available scientists in such a young field is extremely low, and often comes with an eye-popping price tag attached. To further aggravate the issue of scarcity, machine learning is also not a field that many newcomers to the IT industry are itching to get into.

It’s an intimidating, hard journey that requires the right personality and a considerable amount of time to work, as well as industry leaders and educators to make it attractive enough for newbies to sink their teeth into.

Data Is Difficult to Obtain

In his book, The Emotion Machine, Marvin Minsky shows how our brains progress from simple, instinctive thoughts, to more complex forms, such as self-awareness. But because we tend to see our thinking as fragmented, instead of as the step-by-step process it is, we fail to build machines—AI.

Yet we often overlook how much data AI involves. To teach humans, even young children, to identify a Chesterfield couch, for example, you need to show them only a few images of Chesterfield couches, and some regular couches for comparison.

These systems, however, don’t just require more information than humans to understand or recognize certain objects; they require hundreds of thousands of times more, according to Neil Lawrence, a professor of machine learning at the University of Sheffield.

It takes thousands of Chesterfield couch images to teach a computer to pick one out of a crowd, not to mention that the “training” material needs to consist of Chesterfield couches of all sizes, colors, and viewing angles.

So how do you teach a computer to identify all the particularities of a Chesterfield couch? You might do a Google or Bing search, but you’ll turn up just a few dozen. In fact, there may not be an existing database of Chesterfield couches large enough, so you’ll end up doing the job yourself, which is an expensive and time-consuming proposition.

Big tech firms like Google, Facebook, and Apple have plentiful data, allowing them to run inefficient machine learning systems, and improve them afterward. Smaller businesses might have good ideas, but without data, they won’t be able to follow through on them.

Smaller businesses ultimately end up generating their own data through time, or rely on publicly available data-sets, something that sometimes large corporations produce, anonymise and make open-source or offer as a service. Without either of these options, machine learning simply doesn’t work, as its own advent as an industry was caused by nothing else than the large amounts of data it needs to be effective.

Without either of these options, machine learning simply doesn’t work, as its own advent as an industry was caused by nothing more than the large amounts of data it needs to be effective.

Computing Takes More Power and Time

Teaching a machine learning system requires dedicated, specially configured servers working in tandem, which means acquiring and setting up the hardware in your own data center. This is possible by using cloud-based computing resources, such as Amazon Web Services or Microsoft Azure.

Not only are these options costly, but the learning process can take days or weeks. In addition, if you’re not getting positive results, the underlying model may need to be tweaked and the learning cycle will go back to square one, because with every change there is a new learning process, and new neural networks are created.

Fortunately, once the system has gone through its learning phase and you are confident in its reliability, operating it on a day-to-day basis to perform its assigned task will require less computing muscle and storage capacity.

Better Days Ahead?

So, unless you’re Google or the U.S. National Security Agency, you probably don’t have the resources to build a machine learning system from scratch. There are commercial machine learning engines you can leverage, such as the Google Photos, Cloud Vision API, but their applications are currently limited. If you want something more specialized, you have two options: Launch a full custom machine learning project, or just wait a few more years for solutions to evolve and tools to become more readily available.

The pace of research shows no signs of slowing down, and we can be certain that commercial software development frameworks that hide much of the complex mathematics will become available. This will allow developers to have easy-to-use tools for building, optimizing, teaching, and testing machine learning models.

All of this, in time, will inevitably contribute to the successful application of AI and machine learning in the case of smaller businesses, as well.

Data will become less expensive to obtain, and products will become smarter and cater to the increasing demand of consumer expectations of intelligent software and hardware, and predictive solutions at a lower price tag.

The post The Main Challenges of Building Machine Learning Tech appeared first on Simple Programmer.

Sharing the Knowledge

\n\nIn this series of articles, I’m going to take my lessons learned from going through all of the design patterns in depth and I am going to do my very best job to assimilate all that information into what I hope will be the most clear and easily understandable explanation of each of the patterns, starting with the Bridge pattern.\n\nIn this article, I will follow this format:\n\n

\n
• Formal definition of the design pattern

\n

• Broken down definition in plain English

\n

• A real world example to let you think outside of the code

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• An existing code-oriented example that would benefit from the design pattern

\n

• A refactoring of the existing example to the pattern

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• An explanation of the official UML diagram of the pattern relating it to the example

\n

• When you should use the pattern

\n

\n\nMy hope is that by the time you read this article you will have in your mind not only a clear picture of what the Bridge pattern is and how it is implemented, but the real problem it is trying to solve and plenty of examples of where and how it can be used.\n\n

The Bridge Pattern

\n\nThe pattern, I’ll be covering in this article will be the bridge pattern. This is a pattern that many developers—experienced and inexperienced alike—struggle with. Most developers I’ve talked to can only site the over-used example of how the pattern solves the problem of multiple operating systems and drawing APIs for those operating systems. I don’t know about you, but I am tired of that rarely useful example. I think we can do better.\n\nLet’s start with the format definition, directly from the GoF book, Design Patterns.\n\n“Decouples an abstraction from its implementation so that the two can vary independently.”\n\nWhat the heck does that even mean? Let’s break it down.\n\n

Breaking it Down

\n\nIn order to break down this definition we need to first make sure we understand what is meant by an abstraction and an implementation—and it’s not what you think.\n\nIn many programming languages such as C# or Java, an abstraction is thought of as an interface or an abstract class. And implementation is usually a structural implementation of that interface or a concrete class that inherits from and abstract base class.\n\nRemember, the GoF definition is not language specific. This mostly affects the word interface—which is the most common point of confusion.\n\nForget about words and what they mean in specific programming languages for a minute and think about what is trying to be conveyed here instead.\n\nWe want to focus on the words themselves, not what they mean in a particular programming language.\n\nLet’s start with abstraction. What is an abstraction?\n\nIt’s a generalized way of looking at something that makes it so you don’t have to know the details of how that thing is implemented.\n\nA car steering wheel is an abstraction on top of a car. The car steering wheel abstracts away what is really going on to make a car change direction.\n\nWe don’t really care how it does it. In fact, the abstraction of the car steering wheel protects us from having to worry about all the details—especially if those details might change in the future.\n\nGood news, in defining an abstraction, we also defined an implementation.\n\nAn implementation is just a realization of that abstraction. It’s what’s going on under the hood. It’s taking an abstraction and making it real.\n\nNow, normally an abstraction and its implementation are coupled.\n\nA car might have a car steering wheel abstraction, but the implementation of that car steering wheel is tied directly to that abstraction.\n\nA car might utilize the car steering wheel abstraction, but it has a specific implementation of that abstraction and that implementation is directly tried to that abstraction.\n\n\n\nBut what if you had multiple kinds of vehicles that you wanted to be able to utilize the car steering wheel abstraction?\n\nWhat if you had boats and airplanes that needed to utilize a steering wheel?\n\nA car has a much different implementation of steering than a boat or an airplane, but all of those vehicles could have a similar looking steering wheel that all operate in a similar fashion.\n\nYou could put a car steering wheel in each of these vehicles, but if the abstraction of the car steering wheel is directly tied to the specific implementation for a car, it’s not going to work out very well. Steering a car might look the same as steering an airplane, but they work very differently.\n\nWhat you need to do is to be able to decouple the abstraction of the steering wheel from its specific implementation for steering a car. You need an abstraction of an abstraction. You need to be able to abstract the already abstract idea of a car steering wheel into a more generalized abstraction of a vehicle steering wheel.\n\nThat is where the pattern comes in.\n\nThe pattern allows us to create a double abstraction—two layers of abstraction.\n\nFirst we have the abstraction of the interface of the steering system for a car, represented by the car steering wheel.\n\nBut, then we take that abstraction one step further. We decouple the specific implementation of steering a car from the abstraction of a car steering wheel and create a higher level abstraction, a vehicle steering wheel.\n\nNow, we can have multiple implementations of this simplified idea, or abstraction, of a vehicle steering wheel.\n\nThe vehicle steering wheel becomes our high level abstraction and the car steering wheel becomes the implementor of that abstraction. We can now create other implementations of the abstraction. We can create boat and airplane steering wheels, each with their own specific implementations.\n\n\n\nNow we can create different steering wheels for each type of vehicle that aren’t coupled to a specific steering system. The pattern makes it so that the abstraction of a steering wheel is decoupled from the implementation of the specific steering systems, like using turning an axle or raising or lowering a wing-flap.\n\n(I also wanted to mention another good book that explains design patterns in a fairly simple way. Check out Head First Design Patterns. It’s one of the books I recommend in my Ultimate List of Programming Books.)\n\n

A Mode Code-Specific Example

\n\nNow, that we understand the pattern at a high level, let’s take what we learned and apply it to a software development domain.\n\nSuppose you are creating a web application framework that will allow you to create different kinds of web applications.\n\nPerhaps you want to be able to use the framework to create blog, news sites, stores and other kinds of web applications.\n\nYou could define a base web application class that could be the parent of all the different kinds of web applications, and everything would be fine until you decided to introduce the concept of themes.\n\n\n\nImagine that you wanted to be able to create a different themes for you blog type of web application.\n\nYou create a few different themes for your blog application. Perhaps you have a light theme and a dark theme.\n\nYou end up further sub-classing the blog type of web application so that you have blog-light and blog-dark, all is fine until you realize that you want to be able to have a light and dark theme for a news site—oh, and also for a store application.\n\nWithout the bridge pattern, you’d have to follow the same pattern of creating a bunch of different classes for each combination of web application type and theme.\n\nSo, you might have store-light and store-dark, and news-site-light and news-site-dark.\n\nThis could get out of hand really fast—especially if you decided to introduce a third theme.\n\n\n\n

Bridge pattern to the rescue.

\n\nAny time you have two inheritance hierarchies in your code, you can simplify that code by utilizing this design pattern.\n\nInstead of having specific classes that are a combination of a web application type plus a theme, you make your base web application type utilize a theme interface that can specific implementations of the different kinds of themes.\n\nSo, the base web application wouldn’t need to know about the differences between a dark or a light theme, but instead it would utilize a generic, abstract theme interface and you could create a light and a dark implementation of that interface.\n\nThen, your specific implementations of web applications, like blog, new sites and stores could be set to use any of the themes you create, because they access the functionality of the theme through a common theme interface.\n\n\n\nNow you can create new kinds of web applications and new kinds of themes and have any combination work together, because you have decoupled the abstraction—the web application—from the implementation—the specific theme.\n\n

Back to the Formal Definition

\n\n\n\nThis is the UML (Unified Modeling Language) that represents the formal definition of the bridge pattern. (If you aren’t familiar with UML, don’t worry. UML is just a way of representing relationships between different entities in a software development that uses a standard language and convention. Most UML diagrams can be understood without being an expert in UML.)\n\nHopefully by this point, it makes a little more sense, but let’s talk about what each part is in our example.\n\nWe start with the abstraction. The abstraction is the “web application.” The abstraction would utilize an implementor to perform some kind of function. In our case the “web application” might have a function to draw an input box.\n\nThe implementor would be the theme base class or interface. Specific themes would be ConcreteImplementors that would implement some specific functionality, like drawing an input box.\n\nFinally, we would have a RefinedAbstraction, which would be any of the web application types. Those web application types, like blog, storefront, and news site, would utilize the Implementor interface without having to know what ConcreteImplementor was actually providing the implementation.\n\n

When to Use the Bridge Pattern

\n\nThe most simple example I’ve ever come up with for defining when you should use the pattern was actually my answer to a StackOverflow Question asking “When do you use the Bridge Pattern?”\n\n\n\nWell, I hope you now have a deep and complete understanding of this pattern, how it works and when to use it.\n\n(Be sure to subscribe here and you’ll get an email update when I release a new article in the design pattern series.)\n\nIf you really want to cement your knowledge, the best thing you can do right now is to come up with a few of your own examples and try implementing one or two with some very basic code.\n\nSometimes learning how to learn is more important than mere learning. Check out my course “10 Steps to Learn Anything Quickly” for a few tips on boosting the rate at which you learn

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