All posts by Mindfire Solutions

React vs Angular to develop Single Page Application

November 1, 2021Angular JS, ReactMindfire Solutions

Introduction:

Single page application (SPA) is a website or web application that interacts with users by rewriting the current web page dynamically with updated data from the web server, rather than loading complete new pages as is the default approach. The objective is to make the website seem more like a native app with quicker transitions. The page does not reload or transfer control to another page at any time during the process.

Huge companies around the globe are using Angular and React. Companies like Whatsapp, Instagram, Facebook, Netflix, Uber, Airbnb, Dropbox etc use React. Whereas, companies like Google, Nike, Forbes, Sony, HBO use Angular etc.

The market for front-end development frameworks and tools has grown highly competitive. Angular and React are the most popular JavaScript frameworks and libraries among developers which are new. These are well-supported technologies for developing front-end apps. Despite the differences between them, developers use these frameworks to create single page application (SPA).

React:

Facebook and a network of individual developers and communities manage React and it is one of the most popular frameworks. React is a strong, adaptable, and extremely flexible framework that allows its components to be used across various applications.The framework is used by most React development services due to its “learn once, write anywhere” approach and code reusability to create rapid and scalable programmes for all platforms. Its component-based and declarative characteristics make it simple for developers to design interactive and sophisticated user interfaces.

Angular:

Angular is one of the most flexible JavaScript frameworks for web app development, with a wide range of capabilities. It has a lot of features, is quite strong, and gives you greater control over your web application. Angular is a typescript-based programming framework. It’s a component-based framework for building highly scalable web applications. It comes with a number of well-integrated libraries and features, including client-server communication, routing, and more.

Comparision between the two technologies to develop single page application:

Angular and React are inherently different in several ways, therefore we must establish a common ground for comparison

● Document Object Model (DOM):

Angular employs real DOM, which means that if a single section of the tree data structure is changed or modified, the entire tree data structure is updated. In React app development, however Virtual DOM is used, allowing app development companies to track and update changes without affecting other sections of the tree. In the react versus angular race, React wins because Virtual DOM is more fast.

● Data Binding:

Data-binding refers to the connection between the component’s logic and the data it displays. Angular which is bidirectional supports two-way data binding by connecting the Document Object Model (DOM) values to Model data via the Controller. Whereas, React being unidirectional uses one-way data binding, which allows you to direct the flow of data in only one direction. Although two-way data-binding can be implemented with React, by default, a component’s and view’s connection is always one-way. We can add logic to a component to make the connection two-way.

● Performance:

The rivalry between the two frameworks intensifies, with none falling behind in terms of performance. But,the performance of Angular is comparatively slower due to the two-way data binding. The two-way flow of data often causes performance concerns. Server-side rendering becomes faster thanks to React’s virtual Document Object Model. React apps perform better as a result of this.

● Componentization:

Angular has a very fixed and complex structure as it is constructed on three layers: Model, View, and Controller. Developers use Angular to break the app’s code into different files. This enables the reuse of templates or components in various parts of the application. React, on the other hand, opts for a distinct architecture. It provides a straightforward method for creating component trees. The library includes functional programming, including declarative component definitions. React code is easy to read and rationally structured. JavaScript developers can more readily transition to React thanks to reusable components and clear coding.

● Directives:

Angular Directives allow us to organise our code and operate around the DOM. These directives give us access to the DOM when working with Angular. Apart from the directives that come with it, developers can also write their own.The templates are returned with attributes in Angular, and the syntax of Angular’s directives is sophisticated and complex. This makes it confusing to new developers. This distinction between templates and directives does not exist in React. The template logic, or directives, must be written directly in the template. At the end of each component, the logic and templates in React are discussed. It allows readers to comprehend the meaning of the code without having to know the syntax.

● Learning curve:

When compared to React, Angular has a steep learning curve. The Angular framework allows you to tackle a problem in a variety of ways, has a complicated component management system, and necessitates knowledge of various concepts and languages. Furthermore, the framework is constantly evolving, necessitating the need for developers to keep up with what’s new in the Angular ecosystem and to upgrade their skills accordingly. However, React allows you to quickly learn and create an app in the React ecosystem. If you are familiar with JavaScript, React becomes much more easier to learn. It has several valuable tools for newbies to grasp the framework and construct a single page application.

When to use React?

Both Angular and React are excellent choices for developing single page application. The choice between the two is mostly dependent on the project at hand.

● React is a better choice as it has a lower learning curve because existing JavaScript and HTML code may suffice, which allows for faster development. However, as time goes on, developers will need to learn more advanced technologies

● React outperforms Angular, because of its virtual DOM implementation and rendering optimizations. It’s also simple to switch between React versions; unlike Angular, where you have to install updates one by one.

● React has the advantage of allowing segregated debugging, which aids developers in achieving app stability. Furthermore, React’s component-driven architecture allows us to reuse components, reducing development time and expenses.

● Using React, developers have access to a wide range of pre-built solutions. This reduces the number of errors while also speeding up the development process. React’s library can be incorporated into any project (even if it is made with Angular).

So, when to use Angular?

● The team is familiar with Typescript.

● The app’s complexity ranges from low to medium.

● You prefer ready-to-use solutions and want to increase your productivity.

● You wish to use the CLI option Bundle Budgets, which alerts developers when the application bundle size exceeds a predetermined limit. In other words, if you want to control the size of your app, Angular is the way to go.

● You need a feature-rich, large-scale application.

Like other businesses, if you too are looking to develop Single Page Application, Mindfire Solutions can be your partner of choice. We have deep expertise in both React and Angular. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

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Sentiment Analysis in Healthcare

October 18, 2021Healthcare Application Development, Healthcare ITMindfire Solutions

Introduction:

Sentiment Analysis refers to analyzing text data and assigning some kind of sentiment to it. For e.g., we see a movie review on the IMDB website such as – “It was a good movie”. We can understand that the viewer liked the movie and we can go on to say that this review can be assigned a positive sentiment. Similarly, If the review was “It was a bad movie”, we can consider this as negative feedback for the movie and say that it generates a negative sentiment. So how do we go about creating a model that takes in a review/ statement as input and gives out the corresponding sentiment ?

One way to go about it is to create a dictionary of all words that correspond to positive feedback, and another of all words that provide negative feedback. Run a search through the statement and see which words are present. This is a very very simple example of how Sentiment analysis can be done. More on this later, but why would we need a Sentiment Analysis model?

Most companies provide their customers a platform, which could be social media or a company website, to express their feelings about a product or service so that the company can then use this data to improve the quality of their product / services. Since people can post feedback at ease with just their mobile phones, this generates a huge amount of data. Going through all data manually is a labor-intensive process. Hence, sentiment analysis has become an important tool for companies to track and monitor their online feedback and brand value. This is just one example; there are other areas as well where one can use a tool such as sentiment analysis. Let’s look at how it can help to solve some challenges in the Healthcare Industry.

Defining our Input to the model:

Before we discuss the details of the model, we need to find a way to represent sentences for a model to understand. The first approach is bag of words. The way this approach works is we first create a vocabulary of all words we have in our training data. This vocabulary then forms our feature space, or our X’s for the training. Given the number of words in the English language, we could have 10000 words in our vocabulary. We will get to reduce our feature space later.

So now that we have our X’s, we define a way to represent a sentence. We can do so by assigning the count of each word to our feature space. Coming back to our previous example, “It was a good movie”, we will have the following counts or word frequencies- It:1 , was: 1, a: 1, good:1, movie:1. The values for all other words will be 0. Each word will have a fixed position on our feature space, so for all other words, if we substitute zero then we have 0, 0,0,…,1,0,,…1,0…0. Note we have counts only at the position of the words in our current example. This type of encoding is also called one hot encoding.

We can limit the number of words our vocabulary has by using a few tricks, for instance removing words like a, the, this, is, etc. These words do not generally add any meaning to our sentences. These are stop words. Next, to further limit our vocabulary, we can keep only those words that have a frequency above a certain threshold. Doing this, we can reduce our vocabulary to 1/10th of our initial size. Now coming to encoding our target variable. Since this is a good review, we have 1 as our target variable. Note that we are only trying to classify good or bad reviews and having a 1 for good and 0 for bad is sufficient for training our model. All of these can be achieved by a few lines of code using python’s NLTK (Natural Language ToolKit) library and python’s Scikit-learn library.

Defining our model:

Machine learning can broadly be categorized into two parts, supervised and unsupervised learning. Supervised learning is one where we give both input and targets as training data. This is generally used for classification or regression tasks. Unsupervised learning contains just input data, no output is associated with it, and this is used for clustering problems, where the algorithm tries to group the input data into clusters. Since this is a classification problem, we will be classifying the review into one of the good or bad classes, we will rely on either Logistic regression or Random Forest classifier.

We will go into the details of logistic regression or Random Forest in a different article. But for the purpose of this venture, we will pass a python list (arrays) to the model. This is the input list that we get using one hot encoding as defined above, and get a one or zero as an output. Let’s assume the model we build has around 80% chance for classifying a given review accurately. This may not necessarily be difficult to achieve for a task such as this. All of these can be achieved fairly easily using python’s Scikit Learn library.

Problems faced by the service Industry and Solution with Sentiment Analysis:

An insurance company wants to find out whether imparting behavioral training to their service staff has an impact on the overall feedback they receive as reviews.

We start by defining a metric for valuation. Let our performance indicator be the number of positive reviews/ total number of reviews. Assuming there are at least 30 reviews for each staff under consideration. We get the reviews for all staff before and after behavioral training has been imparted. Put them through our model and generate positive and negative outcomes for these reviews. Then do a comparison of percentage positive and negative reviews before and after the training. This will establish a correlation between training and change in reviews. To establish causation, we also need to create treatment and control groups. The treatment group will have the staff that receives the training and control will be the staff that doesn’t. Comparing the change between treatment and control groups will tell us whether the training has an impact.

Like other businesses, if you too are looking for solutions in Sentiment Analysis, Mindfire Solutions can be your partner of choice. We have deep expertise in AI and ML Capabilities. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

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The Future of Application Development for Enterprises: React

October 4, 2021Enterprise Application Development, Mobile App Development, ReactMindfire Solutions

Introduction

Mobile applications play an essential role in generating revenue for businesses with an online presence. An application has all the functionality of the company website, but it is more compatible with the mobile device’s hardware and interface. Mobile Application development has helped multiple industries to expand their global footprints.

According to a latest industry report, mobile applications were responsible for generating 365 billion U.S. dollars in revenue worldwide, and it is not hard to predict that these numbers will only increase. It is projected that by 2023, mobile applications will rake in business well worth over 935 billion U.S. dollars for companies globally.

As the future of mobile applications is looking very bright, more companies are focusing on developing applications that offer a seamless user interface and meet all their customer’s requirements. However, it is not an easy task to create a successful application.

There are many methods and approaches you can adopt to develop an app. You can choose to build a native application, or you can go for cross-platform app development. You also have the option to choose from different programming languages and frameworks.

Most companies prefer a cross-platform app development framework because it saves a lot of time and resources. One such framework that has grabbed the attention of developers is React or React Native, to be specific. A latest industry report showed that as of 2020, React Native was the 2nd most popular choice among developers for cross-platform app development.

Before we get into why React or React Native is the future of enterprise application development, let us understand a bit about it.

The Key Features Of React Native

React Native is a cross-platform application development framework created by Facebook. It was made an open-source platform in 2015 and has been used by many enterprises ever since. Popular companies like Instagram, Netflix, Flipkart, Tesla, and others have used React Native for cross-platform development.

An application that is used for Android and iOS is called a cross-platform application. React Native makes it very easy to build a cross-platform app. The developer will only have to write the code once, and the app can cater to multiple mobile operating systems.

Even though React Native is a cross-platform app development framework, one of the benefits of developing an app on React Native is that it delivers a user experience akin to a native application. Hence, you can expect a React Native app to run smoothly without any glitches.

Many computer engineers and developers claim that, with time, more and more enterprises will choose React Native for cross-platform application development. Let us dissect why that is the case.

Why Is React Native Future Of Enterprise Application Development?

Here is why React Native will be the future of mobile app development for enterprises:

● Reduces Development Time

One of the things that most companies love is reducing the time to market so that their product can be available as soon as possible. By using React Native, businesses can achieve lower time to market. It enables the developers to build the app in a much faster and efficient way.

The developer using React Native can create an application in 30% less time than the other platforms. As the development time reduces, the production cost also goes down. It is the reason why companies prefer React. It is also the reason many startups are choosing to develop their app on React Native.

Startups always aim to achieve high returns with minimum investments. Another advantage of React Native is its code reusability. 90 % of code written for Android can be used for iOS and vice versa. It again saves much time.

● Cross-Platform Ability

As discussed earlier, React Native is an excellent framework for cross-platform app development. However, at the inception of React, you could have only developed applications for iOS. Later, when Facebook realized the full potential of React, they re-developed the framework that was compatible with Android as well.

React Native allows your team developers to build an application on a single platform. This process eliminates any miscommunication among the team. There are different design specifications for different operating systems. React Native also came up with a solution to this problem by providing file extensions that can be used when needed.

● Native Nature

The name “React Native” was given to the framework because the application developed on it can operate as a native application. A native application can only work on one operating system; It can work for iOS or Android, but not both. Native applications have better integration with the device’s hardware and therefore deliver outstanding performance.

This native app-like performance is because of the native widgets of React Native, which also helps in UI development. In fact, React Native surpasses native applications in terms of performance.

Another reason for the excellent performance of React Native is JavaScript, which is the scripting language in React. It allows the framework to create complex applications.

● Real-Time Updates

Real-time updates are another feature that attracts businesses towards React. You can push new updates into the application without user intervention through the app stores. Due to this, users get to enjoy the updated version of your app seamlessly.

React Native makes the up-gradation cycle of your app short and direct.

● Unparalleled User Experience

Most business owners are looking to provide a top-notch user experience to each individual using their application. Its compatibility and native app-like nature ultimately add up to create a rich user experience that your target audience will enjoy and will not mind revisiting your application when needed.

● Large & Growing Community

React Native has a large community of experts backed by Facebook. The React Native community is very active. If the developer faces issues at something while using React, they can share their problem with the community, and the community helps overcome it. There are already more than 2 lakh questions and answer on React Native, so the answers to their questions may be available.

Overall, this makes things easy for the development team if they face any issues while using React framework.

The Way Forward for Application Development

The value that React Native adds to the enterprise application makes it a clear choice among the business owners and developers for cross-platform application development. With less effort and money, React Native offers a high Return of Investment, which most companies want.

From the above points, it will not be a stretch to say, “React Native is the future of enterprise mobile application development”.

Like other businesses, if you too are looking for SaaS Based System, Mindfire Solutions can be your partner of choice. We have deep expertise in React Capabilities. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years

Here are a few interesting projects we have done with the help of React. Click here to know more:

Case study for a social network platform for travellers.

Case study for a video consulting platform.

Rental and Property management case study.

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Suitability Of Ruby on Rails To Develop SaaS-based System

September 27, 2021Ruby on RailsMindfire Solutions

Introduction

Ever since the onset of the pandemic, most companies are letting their employees work from home. It has become the New Normal now. Nevertheless, working from home can lead to many complications, especially for those who work as software developers, requiring specialized systems and hardware infrastructure to operate.

Pain points like outdated native applications on the laptop and lack of local storage for updates can impact daily productivity. Here, using a SaaS platform is exceptionally convenient. It eliminates the need for local resources and brings cost-efficiency through a pay-per-use model.

Thanks to their myriad business benefits, more and more organization are adopting SaaS tools. According to an industry report, in 2019, Software as a Service generated a grand revenue of 148.5 billion USD. These figures account for two-thirds of the revenue generated from the entire public cloud services market. By the end of this year, the SaaS revenue is projected to skyrocket and reach around 190 billion USD. It is slated to reach 305 Billion USD by as early as 2025.

Application and web development on SaaS platforms permit various languages and frameworks, including React.JS, Django, Ruby on Rails (RoR). The following article will discuss why Ruby on Rails has the most suitability with SaaS-based systems.

However, before we get into RoR, let us first understand a bit about SaaS-based systems.

Overview Of SaaS-Based Systems

SaaS is a cloud-based solution in which the SaaS service provider hosts all the applications and relevant data via the internet. The customers do not have to spend their time and resources developing on-premise management software; instead, they can rent these services from the SaaS service provider and pay per their requirements. SaaS-based systems run exclusively on the server of the service provider, who handles the maintenance workloads.

Benefits Of Using SaaS

• It allows the high availability of the application across multiple devices such as laptops, desktops, and mobile phones, permitting seamless remote working

• The pay-per-use model allows customers to drive cost-leadership

• With SaaS, much of the delivery workload for an application to run it seamlessly across environments reduces. The SaaS service provider gives access to enterprise applications such as cloud ERP, CRM, and many more

• The SaaS model lowers the time-to-market for the application and also its development and maintenance costs.

What Is Ruby On Rails?

Ruby is a general-purpose programming language for web development. The syntax of the language is straightforward, and its simplicity is often compared to Python, another programming language known for its lucidity. However, despite such perks, building a SaaS-based application on Ruby is a tiresome job. That is why separate tools and frameworks were developed to resolve the issue. It is where Rail comes into the picture.

Rails is a framework which helps create web applications, using Ruby as its core programming language. Ruby On Rails (RoR) is a software platform that makes web development much more manageable. It is an open-source platform created by David Heinemeier Hansson.

Ruby on Rails combines Ruby with other programming languages like JavaScript, HTML, and CSS for creating web applications that can operate on a web server. Most of the time, Ruby on Rails is classified as a server-side web application development platform.

The developers opt for Ruby on Rails because of its compact nature and easy to code programming interface. Many global businesses such as Shopify, Airbnb, SoundCloud, GitHub, Hulu have been using Ruby on Rails ever since its launch.

Why Ruby On Rails Is The Most Suitable For A SaaS-Based System?

Developing SaaS-based systems using Ruby on Rails have proven and undeniable advantages for the developer and the businesses, that can be summed as under:

Easy Up-scaling

Startups and mid-market entities into development do not have to worry about switching to a new platform or software with the expansion of their customer base. Ruby on Rails is agile enough for the web application to efficiently handle a sudden surge of users at any given instance. Further, to achieve high scalability, Ruby on Rails features modular code.

Great Performance & Efficiency

Ruby on Rails is based on industry-acclaimed philosophies like “do not repeat yourself.” and convention over configuration. It makes RoR very developer-friendly and hence has been a clear choice for SaaS-based product development.

With RoR, developers can plug new functions and features into SaaS-based applications efficiently. Some open-source libraries are also available that can shorten the development cycle, effectively curtailing the development cost.

High Security

One of the most important benefits of using Ruby on Rails for SaaS-based product development is its secured nature. RoR helps protect the system against various threats like SQL injection and XSS attacks. Further, the Ruby on Rails framework intuitively protects against all the standard security issues and takes appropriate action in case of a breach.

Versatile Nature

Ruby on Rails is a highly versatile framework with the ability to integrate other frameworks and technologies. It allows developers the opportunity to alter the SaaS-based application depending upon the customer’s needs. They can also make live updates and changes to the application.

Final Notes

These were some of the most important reasons why Ruby on Rails is suitable for Saas-based product development. However, besides the capabilities of Ruby on Rails, it does take the proven skillsets and business understanding of the development team to build a winning SaaS-based application.

Like other businesses, if you too are looking for SaaS Based System, Mindfire Solutions can be your partner of choice. We have deep expertise in Ruby on Rail Capabilities. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done to develop SaaS Systems with Ruby on Rails. Click here to know more:

Case study for a buisness tech solution.

Case study for an influencer marketing solution.

Product line content management case study.

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AI in Healthcare Insurance

September 20, 2021Healthcare Application Development, Healthcare IT, Machine LearningMindfire Solutions

AI has transformed industries and has immense potential to reshape the healthcare landscape. Medical data like patient visits, prescriptions contain valuable information which can be extracted to create a more structured data format. This has become possible with Artificial Intelligence and Machine Learning. This in turn offers insights into the trends and facilitates collaboration between different healthcare units. Applications for AI in healthcare range from early detection of symptoms to potential diagnosis at a fraction of the cost and increased accuracy.

What is Optical Character Recognition?

Artificial intelligence refers to the use of Machine Learning algorithms to mimic human behavior. Say we want to create a program that takes an input and gives an output. The program uses some decision-making mechanism to arrive at an output. This is primitively done by something called IF-ELSE statements. The limitation of these statements is that one needs to know the exact condition that will produce the desired output. For example, we know the marks of a student and we want to assign a grade, we can hardcode the same using if-else statements – IF marks > 90 then grade = ‘A’. In this case, we have a clearly defined boundary that helps us arrive at our output. But what happens when we don’t have a clearly defined boundary?

Let me explain this with an example. Suppose we have an image of a letter. And we want our program to tell us which letter it is. What kind of code shall we write? This is an example of a problem that doesn’t have a clearly defined boundary. One way to solve this problem is to build a model, which does not use if-else statements but works quite differently. The idea is to feed the program an input image (say an image of ‘A’) and tell the program that it’s an ‘A’. We do this repetitively and try to get the program to learn what ‘A’ looks like. Hence, the term “Machine Learning”. We do the same for every letter or number. This falls under the computer vision category, namely Optical Character Recognition.

Overview of Natural Language Processing :

Natural language Processing is an area of AI and Linguistics and it deals with the application of computational techniques and models to the analysis of human languages. NLP deals with processing written text including but not limited to extracting useful information such as named entities, etc. This requires an understanding of what a word means, which is not something computers generally have. This too is done by learning, where a huge amount of text is fed to the model, and it will try to learn patterns and dependencies between words. In the next section, we will define a problem statement and see how an application of these two concepts can help us make better decisions faster, way faster.

Problems faced by the Healthcare Industry :

Insurance companies have certain parameters to account for when finalizing the premiums they charge for their insurance. One of the most important parameters is the medical history of the member/ insurance holder. The idea is that if a member has more cases of medical history then that member is more likely to raise a claim in the future, thereby costing more.

So the insurance companies need to know relevant details of the medical history and assign risk scores (this could be a topic for another article) corresponding to the medical history. But medical histories are generally stored in paper form. Suppose you had a doctor’s visit, everything there is generally stored in paper format. One might have had any number of tests, and these are in most cases available in paper form. Thus, going through all the paperwork of a member’s medical history is an engaging task. This might take a person anywhere between 30mins – 1 hour. So, is there a way to automate the task?

How can AI help to resolve the issue?

The first step in the process is to get the images of all our documents. The idea is to use OCR to extract the text information from images and subsequently use NLP to extract relevant information, such as diagnosis, procedure or operation, medications that the member is on, etc. There are many open-source OCR engines, one such engine is Tesseract OCR.

Tesseract is used for text detection within large documents or used in concurrence with an external text detector. It can be used directly or through an API to extract text from images. It supports Unicode and has the ability to discern more than 100 languages and can also be trained to recognize multiple languages. The current model, Tesseract 4 focuses on line recognition. It also supports the legacy Tesseract 3 in recognizing character patterns. It is compatible with many programming languages and frameworks. CNN (Convolutional Neural network) is typically used for single character whereas RNN is used for multi-characters.

The next step is to feed the image to the tesseract engine. It will give a file output that contains text extracted from the image. There are various Open source NLP engines. We then feed lines from the text file to our NLP engine which will read each line and use dependencies between words to figure out what our diagnosis, procedure or medications will be. Most NLP engines offer phrase matching capabilities, so we can look for particular phrases as well. We can narrow our search to a specific diagnosis (or any other information of relevance) as well.

Final Steps :

Once we have extracted output from the NLP engine, we can create a database that will have fields such as member name, document type, extracted information, etc. We can use the above pipeline and feed it numerous files at once. After every output, we can append the same to our database.

This process takes a mere few seconds to go through all the files of a member. Using this, we will be able to read through the medical history of thousands of members in a matter of hours.

Like other businesses, if you too are looking to develop applications for AI in healthcare, Mindfire Solutions can be your partner of choice. We have deep expertise in AI and ML Capabilities. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

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Why Should Enterprises Consider Migrating Applications From .Net To Python?

September 13, 2021Application MigrationMindfire Solutions

Market Landscape

Technology is evolving, and keeping up with the latest trends in programming languages and computer coding provides a competitive advantage to institutions. Coding skills form a core part of the successful functioning of banks, automobiles, hospitals, and every aspect of our tech requirements. However, choosing the correct programming language in IT, data analytics, application migration, research, web designing, and engineering segments is vital.

Software development involves continual learning about programming tactics and new languages. The accelerated demand for ‘online’ has fueled the need for programming languages. It becomes vital to optimize software development capabilities to be at par with the latest trends to help better efficiency, customization, and customization and its smart implementation.

Technology Overview

What drives the success of programming languages can be determined by their implementation in the corporate and academic segments. Today, in academics, advanced-level programming holds a dominant share. Businesses can take advantage of the latest technology for their in-house training and initiate activities for employees both online and offline.

Gaining insights on the latest market trends, Python is a dynamic, free open source, and interpreted programming language that most software developers favorably consider. It supports object-oriented programming as well as procedural-oriented programming.

Python has bagged second place as the most common programming language in 2019. It has also secured third place in 2021, as per a report published by Statista. Also, Github and Google Trends reported Python as one of the most popular programming languages in the world in 2020.

On the other hand, .Net is a free and open-source, managed computer software framework for Windows, Linux, and macOS operating systems developed by Microsoft in the 90s. In 2020, The One Technologies reported .Net as one of the top frameworks for web development.

Let’s identify a much-developed technology that can enhance an enterprise’ capabilities.

.Net Features

.Net is a free-of-cost open-source platform and helps to develop: applications, websites, games, and IoT (Internet of Things). It is a cross-platform software framework that helps to create websites on Windows, Linux, and macOS. Similarly, Xamarin/Mono is a type of .Net implementation which is in use only for running apps.

.Net also has a built-in automated monitoring system named ASP.Net. The ASP.Net constantly monitors web pages and caters to issues such as memory leaks or infinite loops. The developers are notified immediately, which ensures stability in all .Net applications.

Python Components

Python is an object-oriented programming language recognized for its simplicity and readability of syntax. Global industries use this programming language to automate their tasks and analyze data. They also use it for other purposes like website building, machine learning, and software testing. Today, Python is among the most versatile programming languages used.

Apart from programming or data sciences, Python can also perform various tasks such as keeping track of stock prices and managing inventory.

Application migration from .Net to Python

The latest trends in the market today show that industries are vastly adopting Python for their tasks. This has become possible with application migration from existing languages to Python. Let’s learn its importance with its key components in comparison with .Net.

● .Net is a framework that supports multiple programming languages (C# (C-sharp), F# (F-sharp), and Visual Basic) for web development. On the other hand, Python is an enhanced programming language that has also developed several frameworks for web development like Django and Flask.

● To use C#, one needs to have complete knowledge of Java. In contrast, Python doesn’t have many prerequisites. Another highlighted feature of Python is that it was built on the Don’t Repeat Yourself (DRY) principle. It means writing quality code needs minimum effort.

● Syntax of Python is also much more straightforward than C#. In Python, one does not have to end every line with a semicolon. It’s very easy to read and has lots of whitespaces. If a program takes ten lines of code in C#, the same program in Python will take around 4 or 5 lines of code.

● With the help of Python, the work and duration of the project reduces to almost half.

Now let us compare Python frameworks Django and Flask with the .Net framework.

● Python has excellent compatibility with machine learning. .Net Framework offers ML.Net and libraries like Accord.NET to develop ML models. However, these models have limited applications as comapared to Python. It is one of the significant reasons why application migration to Python has become prevalent.

● All the .Net implementations have been given one standard API called .Net Standard. Along with this also a massive collection of libraries is built on .Net Standard. All of the libraries, runtime, and compiler of .Net are present on Github for free.

● The massive libraries of Python are available in source and binary form. It is also freely available for all platforms. By using Python, one of the added benefits is its large community. Unlike the .Net community, the Python community is very active and consistently adds new functionalities to its already vast collection of libraries. It means the developers can do more work on Python by doing less.

● Also, as compared to .Net Framework, Django has a much better ORM. At times, enterprises prefer Flask framework over .Net because of its lightweight and minimal nature.

Choosing the right Python framework is crucial for a successful project. Explore our insightful article: Detailed comparison of the best Python frameworks to find the best fit for your development needs. Make an informed decision and embark on a seamless and efficient development journey

If your business is seeking application migration services, consider partnering with Mindfire Solutions. Specializing in .Net to Python migration, we offer comprehensive Python software development services to facilitate seamless transitions. With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years.

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Is React Native The Clear Choice For Cross-Platform Application Development?

September 2, 2021Mobile App DevelopmentMindfire Solutions

Mobile Applications Overview

As of 2020, there are around 218 billion app downloads reported globally. Companies generated revenue of US $462 billion through mobile application development. According to an industry report, it is anticipated that by the end of 2023, mobile apps are expected to generate more than US $935 in revenue.

More and more enterprises are now focusing on developing their mobile applications.
Selecting the right app development platform or framework is essential, as the application would contribute to the business’s profit. Therefore, creating a user-friendly app that has a top-notch user interface is vital for them. However, making such an app is not an easy task.

The two most used mobile operating systems globally are Android and iOS. Therefore, everyone develops mobile apps for these two systems only. Android and iOS, each of them has provided its platforms and tools to create applications. The only problem here is that apps developed on Android cannot function on the iOS platform and vice versa. “Isn’t there a way to build an app for both operating systems?’ – This is one question that people are grappling with.

It is here that cross-platform apps come into the picture. Before we know why React Native is the best choice for application development, let us understand the concept of cross-platform applications.

What Is Cross-Platform Application Development

The applications that work only on iOS or Android (works on one or the other) are called native apps. Native apps are built for a specific OS; they seamlessly integrate with the smartphone’s hardware and delivers the best UI experience possible.

Furthermore, to develop native applications on iOS and Android, an enterprise would have to hire two different teams. This means that React native applications require more workforce and money to create it. Cross-platform applications are those which are used on multiple operating systems or platforms at once. By creating a cross-platform application, developers don’t have to write different code for different OSs.

More importantly, cross-platform development saves enterprises a lot of time, and they don’t have to hire two different teams of developers. Therefore, creating cross-platform applications has become a popular choice among companies, and it has become a common practice to use this approach for app development.

There are many mobile application frameworks available for cross-platform development. React Native is one of them.

Overview Of React Native

React Native is a mobile application framework created by Facebook and made available in 2015. It’s an open-source platform. React Native uses JavaScript as its programming language.

React Native transforms the code to the native APIs that help it integrate with the device hardware.The stability that React Native provides is far better than other frameworks. A single code can create applications for different platforms. This code can also be edited in case there are any updates in the future. With the help of many pre-existing codes available on React Native, the developers can finish the assigned project faster.

The number of users for react Native have risen exponentially, since it’s release. Github in 2018 recorded it as the second-highest choice for any repositories. In current times React Native is the second most popular cross-platform application development framework.

Many world-renowned companies such as Instagram, Facebook, Flipkart, Tesla, Shopify, and others have used React Native to develop their applications.

Let us learn why React Native is the best choice for cross-platform app development.

React Native Enables Efficiency

Some reasons why React Native is a clear choice:

● One aspect that is most unique about React Native is its ability to provide code reusability. Project managers and engineers are the ones who appreciate this capability the most. It is also found that 90 % of the code written for iOS can be used on Android and vice versa.

● Another benefit of React Native is that web application code can be used for mobile application development if both are on React Native. It saves a lot of time for the companies. The price of production comes down when project duration reduces.

● The developers much appreciate the UI (User Interface) offered by React Native. As the reactive Native framework uses JavaScipt; it is responsive and has less buffering time. Hence React Native enhances the user experience.

● If developers face any problem while coding, the large community of React Native can help them resolve the issues. The community members often share their experiences. Therefore it is also possible that solutions to their problems are already available on the platform.

Now, let’s compare React Native with one of its major competitors, Flutter

Like React Native, cross platform appplications also use Flutter for application developement. But unlike React Native, Flutter uses Google’s Dart as its programming language. Dart is a new programming language as compared to JavaScript. There are instances when enterprises prefer Flutter over React Native.

Does that mean Flutter is a better choice? The answer to this question is not very straightforward. Both the frameworks have something different to offer, and one is better at some things than the other.

Here are some areas where React Native has the upper hand over Flutter.

● The advantage of choosing React Native is that developers find JavaScript a much easier language than Dart. This is the reason why finding a proficient software developer for React Native is less complicated.

● As React Native has been around longer, it is backed up by more than thousands of packages. This number is nearly five times higher than the Flutter.

● Whenever there will be a discussion on the user interface, React Native will always be a winner. The UI experience of React Native is more dynamic than Flutter’s.

● The installation and configuration process of React Native is simple. Where else, in the case of Flutter, things are a little bit complicated.

Final Thoughts

From the above pointers, we can conclude that React Native is one of the top choices for developing a cross-platform application. If you are confused about choosing between Flutter and React Native, select the platform depending on your requirements.

Lastly, you should know that the future of React Native is looking bright due to its simplicity and capability of solving development problems. That is the reason why most businesses prefer React Native for cross-platform development.

Like other businesses, if you too are looking for cross platform Application development, Mindfire Solutions can be your partner of choice. We have deep expertise in React Native . With a team of highly skilled and certified software professionals, that have developed many custom solutions for our global clients over the years. Click here to know more:

Here are a few interesting projects we have done to develop cross platform applications with React Native.

Case study for an e-Commerce web and mobile Application development for Android and iOS

Case study for an application on B2B Merchandising

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Leveraging Kubernetes for End-to-End Quality Assurance

June 22, 2020Quality Assurance, Software QA TestingKubernetesMindfire Solutions

Kubernetes is an all-in-one container orchestration tool that helps in the management, deployment, monitoring, and scaling of systems for containerized applications which are all packaged in one open-source system. If your organization works with containerized applications using Docker, then you would already know that things become tedious, and it becomes difficult to manage them when they scale up.

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Classic QA Process:

Here, the end-user only interacts with the front-end user interface in both monolithic and containerized applications. Similarly, the traditional QA process can be used for containerized applications but should be seen as a subset of the QA process in the Kubernetes world. UI or API testing using tools like selenium or Rest- assured can be used for automation testing for applications running on Kubernetes, but this is a costly process that requires high investment in terms of time, money & resources. To overcome this, it requires us to look outside the box to find better solutions that can be paired up with these and provide better coverage right from the beginning. This would result in the scope of the QA process getting increased when applied to Kubernetes applications.

Enhanced QA Process (hybrid) for Kubernetes Applications:

Kubernetes applications are generally deployed using continuous integration and continuous delivery. To assist the developers in the release cycle, the traditional approach of creating end-to-end tests is not adequate and now requires QA to work very closely with developers on the tests so that it can be written quickly and executed swiftly.

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The following are the new technologies that help in accomplishing the full potential of the QA process in the Kubernetes world.

AB Testing
Chaos Engineering
Consumer-Driven Contract Testing
Helm Tests

AB Testing:

The complexity of applications has increased vastly, and business requires constant UI updates and feedback based on the frontend changes. The business stakeholders hire marketing and research teams to attract more customers and convert more leads from different marketing campaigns.

Here Kubernetes gives us the power to leverage continuous feedback by using the customers as testers and present real-time statistics for businesses to make decisions in real-time

Chaos Engineering:

Chaos engineering tests the resilience and weakness of a system in production by creating expected chaos in the system to verify that none of the activities has affected the performance and stability of the system. This builds confidence that the system can handle unexpected situations and that any failures that exist can be addressed before the customers face the brunt. Since they get known to the QA team in advance, it gives them the opportunity to fix those unexpected outages before they actually affect large groups of users. Some examples can include scenarios like increasing load on a Microservice, introducing DNS failures, Mimicking hard drive failure, etc.

This can be achieved by using Free and open-source tools available depending upon the cloud provider on which the system is hosted. For example, one of the better-known tools is Chaos Monkey used by Netflix for cloud-hosted Kubernetes clusters.

Consumer-Driven Contract Testing:

Often times while working with microservices, creating full end-to-end integration tests are expensive and requires high execution time. Even if you hit failures, it is hard to figure out which service is causing the failure if the complexity of the system is high. We can create Consumer-Driven Contract Testing using Pact which is available in almost all languages. It makes it easy to write the integration tests and helps us to test consumer-provider rules using JSON files.

So, what is a pact? PACT is a binding contract between the consumer and the provider, which has to be always followed. In the world of microservices, the pact is based on the API call (consumer) and response (provider). It can be done using either a single isolated microservice (while mocking the other microservices) or on a real system with all microservices running.

Why use PACT when we can write end-to-end integration tests? Well, it helps us create tests before we move to write expensive integration tests and can provide us with the general sanity of all the microservices running in our system.

Helm Tests:

Most organizations use Helm charts to deploy Kubernetes resources on Kubernetes clusters. These charts are really powerful and often contain tests written in the chart which can be used to test if all the resources got deployed successfully to our Kubernetes cluster.

Since Helm tests use a scripting language to perform basic sanity checks on the deployed resource, we should leverage the tests provided by popular charts over the internet. In case, you are making in-house helm charts, then you might want to skip this for some better integration test since tests written in scripting language can be difficult to write and maintain.

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With the fast evolution of the application architecture and introduction of DevOps culture, the traditional QA process is not able to provide the same value for money and is often seen as one of the bottlenecks when it comes to the release cycle. Hence, QA must design and plan their framework to provide a blend of fast test results and improved end-to-end integration tests. The role of QA is now changing from Quality Assurance to Quality Assistance. Since the QA process has to be optimized as per the AUT, this article hopefully has helped you in identifying the process of a robust end-to-end QA framework for applications running on the Kubernetes cluster.

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The views and opinions expressed in this article are those of the author. To know more about our company, please click on Mindfire Solutions. For over 20+ years now, we have been the preferred Software Development Partner of over 1000+ Small and Medium-sized enterprises across the globe.

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CallKit integration for VoIP Apps

June 2, 2020iOS App Development, Mobile App DevelopmentCallKit IntegrationMindfire Solutions

Most of us by now are accustomed to using the services of a third-party provider to make VoIP calls over desktops, laptops, and smartphones. But making VoIP over Native iOS apps was never a convenient task. In fact, Apple has completely restricted the use of VoIP push for any kind of background processing from iOS-13. Earlier developers were using VoIP push for making call (audio/video) notifications or some other processing in the background. Apple took this decision to avoid the overbearing process that was happening in the background. It was not only leading to disproportionately high consumption of resources but also a significant drain of battery capacity.

A typical VoIP call usually comes as a notification on one’s screen, and in order to receive it, the user needs to slide the notification and also type a passcode to receive, if locked. Burdensome! Isn’t it? Especially if compared to how a native app eases the same experience.

The solution to this comes with CallKit, which is a framework that is capable of elevating your third-party VoIP app experience to a very intuitive one. You get the same rich, full-screen native call UI to accept and attend the calls. Once a call is accepted you also get a “Callback “option to initiate the same function (WebRTC) which you have used earlier. You can also set custom ringtones for your app that would be different from native call ringtones.

Besides, if you are on a call in your app and you start getting native calls, you will be able to hold and swap the calls. It could be an audio call, facetime call, or even another VoIP call. Even your call history will be stored in the call directory (missed, received, dialed calls, and add-in favorites). You can also make the call from Siri, Bluetooth, and access the “Do not disturb” functionality.

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The Impact of DevOps Adoption on Teams

January 22, 2020ThoughtsSMB and IT Outsourcing, Software DevelopmentMindfire Solutions

Companies operating in the field of software development have ushered into an era of stiff challenges and expectations, unprecedented till now. Possessing the qualities of agility, accuracy and speed simultaneously are becoming imperative for survival rather than a means of maintaining a competitive edge. Under the circumstances, a DevOps culture provides a flexible, efficient approach of standing up to the demands. It does so by following a model that delivers results leveraging the dependencies that exist between the software development and operations aspects of software delivery. It balances responsibilities more evenly than in a traditional waterfall model, where developers simply turn completed code over to those in charge of operations. DevOps also establishes procedures to ensure that all team members have insights into application performance, which provides benefits such as greater collaboration and engagement between team members.

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Improved Collaboration

Traditional software development happens in phases. There are teams mapped to each phase and each team is entrusted with the responsibility of playing its part in the successful completion of the phase it is involved in or responsible for. The result of this approach is that the ownership of a team gets too confined only to the successful execution of the part it deals with. Thus, each team tends to be most concerned with achieving its own objectives instead of meeting the organization’s ultimate business goals. As long as projects get executed successfully, the fissures that exist beneath do not come to the forefront. It is only in the moments of crisis that the lack of synergy becomes apparent and sometimes takes gigantic proportions resulting in the partial or complete derailment of projects.

DevOps neutralizes this possibility completely. The approach requires all team members to be equally dedicated in meeting the broad goals while also focussing on their individual ones. This leads to improving collaboration between people across the development and operations teams. This model eliminates the possibility of working in silos. Members across teams remain fully committed to the software throughout its development life cycle to ensure that their project’s overall goals are met. Accountability for successful delivery lies with all. This compels employees to get more involved in working together.

More Engagement

One of the primary goals of DevOps is to shorten the development life cycle while still delivering software that meets business objectives. The shorter development cycle essentially means a higher frequency of code releases followed by exposing these releases to scrutiny for the detection of bugs within the code, infrastructure and configuration. The pace at which things get done is brisk. There are no slack periods for teams anymore waiting for their phases to begin. All this brings about a high degree of engagement for all the members involved in a project. And it can be intense at times. The results are equally impressive. Industry reports have indicated that the failure rate of organizations with a DevOps culture is 60 times lower than those that don’t.

Higher Efficiency

DevOps uses a workflow that emphasizes on continuous delivery (CD) and continuous integration (CI). The efficiency that gets infused results in software getting delivered faster and with a higher frequency. Automated testing and integration tools are also key elements in DevOps practices. It makes the IT staff more efficient by eliminating the need for them to perform repetitive tasks. Developers no longer need to wait for code integration processes to complete, which can otherwise get quite time-consuming.

DevOps platforms offer opportunities for improving efficiency and increasing the predictability of cloud-based solutions like Azure and Amazon Web Services (AWS). These platforms use a scalable infrastructure to reduce testing and deployment times by increasing available hardware resources during this period. They also provide DevOps as a service, such as Azure DevOps. AWS also provides a set of services specifically intended to help organizations implement DevOps practices.

Exposure & Learning

Employees are generally happier and more productive under the DevOps model, largely because it focuses more on performance than anything else. There are fewer administrative obstacles and greater sharing of risk, which allows individuals to blossom. Members in both development and operations teams prefer DevOps because they get exposed to multiple roles, resulting in their getting a better understanding of project execution and the business as a whole. This experience is more rounded, fulfilling and increases job satisfaction considerably.

Better Results

The improved collaboration between teams and the ensuing efficiency has a direct impact on reducing the time needed to build software. Collaboration encourages a proactive approach amongst team members in putting their act together. All this eventually reduces the time needed to bring a product to market. This benefit is particularly important in competitive markets where the ability to deliver software on time has a direct impact on the revenue and market share. With the DevOps approach not only is the speed looked after but also the quality of the outcome. It also increases customer satisfaction when they receive a comprehensive product sooner than expected, with all the promised benefits delivered quality-wise. To achieve this end goal can be a highly fulfilling experience for all the members involved in giving shape to the software.

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A DevOps culture improves the collaboration between groups with historically distinct roles, especially people in software development and operations. This practice provides many other benefits that generally result in the faster delivery of software. DevOps practices also improve the engagement of team members by making them responsible for projects throughout their entire life cycle, rather than a specific phase of the project. The increasing availability of tools is making it easier for organizations to implement DevOps practices, allowing team members to automate many of the tasks needed to develop, test and maintain code.

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If you have any queries in this field, talk to Mindfire Solutions. For over 20+ years now, we have been the preferred Software Development Partner of over 1000+ Small and Medium-sized enterprises across the globe.

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