DEV Community: Hima Pujara

Codeless Test Automation: A Detailed Guide

Hima Pujara — Fri, 26 May 2023 08:55:05 +0000

From preventing bugs to reducing development costs and improving performance, software testing has enabled tech brands to identify technology's true potential. Since manual testing practices appeared to be a consuming task, the need to deliver products rapidly to the market changed the entire scenario.

However, the demand for user-centric and performance-driven products enabled developers to regain control of quality assurance with advanced test techniques like automation.

As a part of transformative development tactics, Codeless test automation has emerged as a trend that has improved the accuracy and reliability of test results. Since automated tests are less prone to human error and can be executed with a high degree of consistency, codeless automation can help to identify defects or issues in the software more effectively, leading to better overall software quality.

In this blog, we have underlined all the aspects of codeless test automation, highlighting all the challenges, limitations, best practices, and the potential it brings to the Quality Assurance aspect of futuristic development.

The Codeless Test Automation: The Definition

Codeless test automation refers to a type of software testing where test cases are created and executed without the need for writing or coding any scripts. It involves using visual interfaces or drag-and-drop tools to create automated tests that can simulate user actions and interactions with software applications.

According to a study by Testim.io, teams using codeless test automation reported a 90% reduction in test creation time and a 40% increase in test coverage. Besides, Gartner has predicted, “low-code application development will be responsible for more than 65% of application development activity by 2024."

Test automation enabled businesses to save time and effort by automating repetitive and time-consuming test cases. Besides, automated tests can be run overnight or during off-hours, freeing up manual testers to focus on other tasks and leading to faster turnaround times for software releases.

Codeless test automation tools provide a simple and intuitive way to create automated tests, even for testers with little or no coding experience. With codeless test automation, testers can focus on creating test scenarios and defining test data without worrying about the technical details of scripting and coding.

Benefits Of Codeless Test Automation

Faster test creation: Codeless test automation tools allow testers to create test cases easily without the need for coding or scripting.

Improved test coverage: Codeless test automation tools identify more bugs and issues, improving the overall quality of the software application.

Reduced risk of errors: Codeless test automation tools mostly minimize human errors and ensure that test cases are executed consistently and accurately with simplified regression.

Faster feedback: Codeless test automation tools provide quick feedback on the quality of the application, allowing developers to identify and address issues more quickly.

Cost-effective: Codeless test automation tools can be more cost-effective as they require less technical expertise and can be implemented more quickly.

Easier maintenance: Codeless test automation tools can be easier to maintain as they often have a visual interface that allows testers to update and easily modify test cases as needed.

Codeless test automation tools use a combination of AI and ML algorithms to both generate test scripts and execute tests automatically. These tools can capture user actions and interactions with software applications and use this information to create automated tests.

Moreover, Codeless test automation can speed up the testing process, reduce the risk of errors, and improve the accuracy and efficiency of testing. Using codeless techniques and artificial intelligence for quality assurance can also help increase test coverage by enabling testers to create numerous test cases in a short time.

The Challenges Of Codeless Test Automation

Let's understand some of the key challenges of codeless test automation:

Limited Flexibility

Codeless test automation tools often have limited flexibility. Hence, they cannot handle complex testing scenarios or custom requirements. This can result in testers having to create manual test cases to cover gaps in test coverage, which can negate the benefits of codeless automation.

Tool Limitations

The features and functionality of the tool can limit codeless test automation tools. If a tool does not have the necessary features to support a specific testing scenario, testers may need to switch to a different tool or use a manual testing approach.

Steep Learning Curve

While codeless test automation tools are designed for ease of use, there can still be a learning curve for new testers. Testers may need to undergo training or experiment with the tool before using it effectively.

Maintenance Requirements

Codeless test automation tools still require maintenance to ensure that they continue to work effectively. This can include updating test cases to reflect changes in the software application or fixing issues with the tool itself.

Risk Of False Positives

Codeless test automation tools can sometimes produce false positives, which can lead to a loss of time and effort in tracking down non-existent bugs or issues.

Therefore, testers must carefully evaluate the capabilities and limitations of codeless test automation tools to determine whether they suit their testing needs. Besides, they also need to be prepared to invest time in learning and maintaining these tools to ensure that they provide maximum value.

Codeless Test Automation Best Practices

Many codeless test automation tools are available, each with its own strengths and weaknesses. It is important to identify the tool that best suits your testing needs, taking into consideration the type of application being tested, the testing environment, and the skill set of the testing team. Besides, testers must keep certain rules or best practices in mind when aiming for codeless test automation.

Define clear testing objectives

It is important to clearly define the testing objectives and goals before beginning the codeless test automation process. This can help to ensure that the test cases are aligned with the business and user requirements

Create modular and reusable test cases

Codeless test automation tools allow testers to create modular and reusable test cases that can be easily updated and modified as needed. This saves time and ensures that the testing efforts are more efficient.

Collaborate with developers

Collaboration between testers and developers is crucial in codeless test automation. Testers must work closely with developers to ensure that the testing efforts align with the development process and that any issues or bugs are resolved quickly.

Continuously update and maintain test cases

Codeless test automation tools require continuous maintenance. Testers must regularly review and update the test cases to reflect changes in the software application and ensure that the testing efforts remain relevant and effective.

Monitor and analyze test results

Testers must continuously monitor and analyze the test results to identify any issues or trends that may indicate problems in the software application. This can help ensure that the testing efforts are effective and that the software application is high quality.

Top Tools For Codeless Test Automation

When selecting a codeless test automation tool, it's important to consider specific software testing needs, the type of application being tested, and the skillset of your testing team.

TestCraft: TestCraft is a cloud-based, codeless test automation tool that enables testers to create, manage, and execute test cases without the need for coding. It supports multiple platforms and languages and offers advanced features such as visual testing and AI-powered test analysis.

Katalon Studio: Katalon Studio is an all-in-one test automation tool that supports both codeless and scripted testing. It offers a user-friendly interface, supports multiple testing frameworks, and allows for easy integration with other tools and systems.

Leapwork: Leapwork is a cloud-based, codeless test automation tool that enables testers to automate tests using a visual language. It offers a large library of pre-built building blocks and supports multiple platforms and applications.

Testim: Testim is a codeless test automation tool that uses AI and ML to help testers create and execute test cases.

mabl: mabl is a cloud-based, codeless test automation tool that uses AI to help testers create and execute test cases. It offers advanced features such as self-healing tests and visual testing and supports multiple platforms and languages.

Codeless Test Automation & The Future Of QA

The future of codeless test automation in QA is promising. With advancements in technology, codeless test automation tools are becoming easier to use, making it possible for non-technical testers to create and execute complex test cases.

With the use of AI and ML to automate testing, AI-powered codeless test automation tools can analyze the behaviour of an application and suggest test cases, making the testing process more efficient and effective.

Moreover, integration of codeless test automation with DevOps and Agile methodologies can be used to create automated tests that are run continuously, providing fast feedback on the quality of the application under test.

Conclusion

Overall, codeless test automation has the potential to revolutionize the way software testing is done. As technology constantly changes and evolves, we expect to see tech organizations adopting codeless test automation contributing to the digital transformation goals planned around QA.

10 Best Bitcoin Wallet Apps: A Quick Go Through

Hima Pujara — Wed, 16 Mar 2022 15:23:35 +0000

We can't overlook the fact that cryptocurrency is growing tremendously and many people around the globe are getting involved in it. Especially, the Bitcoin.

Created in 2009, Bitcoin is one of the most popular cryptocurrencies that uses peer-to-peer technology to facilitate instant payments. As per CNBC, “Bitcoin has risen nearly 70 percent since the start of 2021, driving the entire crypto market to a combined $2 trillion in value.”

However, anyone who needs to store and trade Bitcoin or Altcoins must have access to a crypto wallet. As crypto wallets these days are loaded with features that enhance the process of trading cryptocurrency, almost all the industries have started accepting payments and transactions in Bitcoin. Also, there are wallet apps for crypto investors which makes owning Bitcoin or any other virtual currency easy for effective transactions at any place and time.

Today, we are going to talk about the top 10 bitcoin wallets that offer advanced security features like two-factor authentication and other interesting features you expect to have seamless bitcoin trading while initiating with the most significant benefits for which one should use a Bitcoin wallet.

Let’s begin!

The Advantages Of Using Bitcoin Wallet

You can send and receive money to anyone in the world without using a bank.
Bitcoins can’t be stolen. No one can steal bitcoins unless they have a physical access to a user's computer and send the bitcoins to their account.
It is difficult to track transactions. Unless users publicize their wallet address publicly, no one can no one can trace transactions back to them.
It is easy to transfer across borders.
One can have multiple cryptocurrency wallets, so in case if one gets lost or hacked, you don’t lose all your money.

Top 10 Bitcoin Wallet Apps

With all such benefits to offer to the cryptocurrency enthusiasts, let us quickly go through the top 10 Bitcoin wallet apps that crypto investors may like to use:

ZenGo: Being one of the most popular bitcoin wallet apps, Zengo provides utmost freedom and control for crypto investors. There are no minimum, maximum, or extra fees for crypto investors to buy and earn bitcoin. It facilitates bulletproof security and customer support with the help of facial biometrics. In this way, it helps to control funds in digital wallets. This is the first-ever keyless bitcoin and cryptocurrency wallet app for crypto investors.

Coinsmart: This app helps in the easy buying of cryptocurrencies and bitcoin through bitcoin wallets. It helps with quick and convenient ways to pay for transactions and features in a secure way. This app enables crypto investors to access the funds on the same day as the deposit.

Coinmama: It is known as one of the leading cryptocurrency exchange platform to exchange bitcoins with credit cards, bank transfers, or debit cards. It offers its users multiple payment options and high spending limits along with fast-track verifications with instant delivery. This Bitcoin wallet app also provides a crypto calculator and Bitcoin calculator to ease the transaction in the cryptocurrency market.

Ledger Nano X: Ledger gives you full power over your crypto investment: a hardware wallet, combined with one single app which offers the best security along with the ease of use and ownership of your crypto assets. The wallet is a Bluetooth enabled secure device to manage cryptocurrencies and digital assets. It also helps to keep private keys offline while the ledger live app provides access to key services.

Mycelium: The mycelium Bitcoin wallet app is one of the oldest and most popular Bitcoin wallets. There is no cross-border control and fees- no payment limits as well as no maximum limits. It offers:

Advanced cold storage
Savings account
Spending account
100% security

Coinbase: Undoubtedly Coinbase is one of the top Bitcoin wallet apps for crypto investors. It is focused on securely managing the rights to private keys of Bitcoin wallets. This app supports more than 4,000 tokens with the whole world of DApps. This wallet app can provide access to vaults and transaction details, a storage place for all cryptocurrencies and NFTs, Protection to digital assets, as well as acts as a self-custody wallet.

Binance Chain: At first, the Binance chain wallet looks similar to other extension-based wallets. However, it's quite different as it helps to transfer cryptocurrencies between the Binance.com account and the wallet app. If any of the investors doesn't have a bitcoin wallet, he/she can install an extension et for transactions.

Kraken: The Kraken app is suitable for beginners and aspiring crypto investors to deal with popular cryptocurrencies such as Bitcoin. With the help of the bitcoin wallet app, one can keep a tab on favorite projects and can also instantly invest in bitcoin while checking out the top gainers of the day. This app is also available in the pro version.

Exodus: Exodus is an easy-to-use multi-currency software wallet that is available for desktop and mobile. The wallet excels in its simple design and superb online support. It is suitable for both beginners and professional crypto investors for sending and exchanging bitcoin efficiently. This app can give more control over the wealth with the help of live charts, built in exchange, and cryptocurrency assets.

Electrum: This app is securing bitcoin payments since 2011 through its bitcoin wallet app. It’s is faster and enhances the bitcoin experience with two-factor Authentication verification. It provides multiple user interfaces and supports hardware wallets.

Conclusion

As per CBS news,’ The first week of 2022 hasn't been kind to bitcoin, as the cryptocurrency lost 11% of its value in mere days and finished this week at about $42,000 - down almost 40% from its all-time high last fall’.

However, we can’t overlook that in a sign of crypto’s growing importance, the investors need to keep themselves aware of current and upcoming trends pertinent to cryptocurrency. Also, it is extremely necessary for Bitcoin App developers to look for cybersecurity requirements and foster solutions like Blockchain technology.

Since blockchain has emerged as a technology that works a decentralized ledger, Crypto App Developers could foster it to secure the storage of Bitcoin and other cryptocurrencies.

As we expect to see even more crypto companies going public in 2022 than we saw in 2021, wallet apps adhering to the ongoing security trends in the market can help crypto investors take business-effective and profitable decisions.

Why Python is Good for Machine Learning?

Hima Pujara — Wed, 08 Jul 2020 14:04:41 +0000

Websites, applications, databases and several other real-world applications are based on programming languages. These languages are logic based and help in bringing smart technology and the real-world scenarios together. Numerous programming languages handle different type of problems and situations. The primary motive of these programming languages is to make the functioning of applications in the real world easier and to solve problems accordingly. Some renowned programming languages include Python, C++, C#, MATLAB, FORTRAN, Java, and much more.

Python is one such programming language which is extremely popular around the world. It was developed by renowned developer Guido van Rossum. It is a high-level programming language which has numerous perks over others. It makes use of object-oriented paradigms, classes, and objects, with a pre-included standard library to make it easier for developers to design robust and versatile solutions for their customers.

The need for programming languages

A world without programming languages is hard to imagine. It is these languages that are the reason behind all excellent software, smoother functioning apps, and rapidly evolving technology. Programming languages have widely required in the modern era. They come with a multitude of features that help in designing and solving problems.

They assist in developing real-world algorithms which are incorporated in business companies and other sectors. They also have essential elements which are necessary for the functioning of a smart device. Programming languages also help in easily defining complex structures. They help in storing data, handling information, arranging and viewing multiple works too.

Features of Python

Numerous features are associated with Python which makes it a truly versatile programming language. Some of the key features are as follows.

• Python is a multi-programming language
• It supports all kinds of platforms
• The language also supports functional programming, aspect-oriented programming, metaprogramming, and object-oriented programing.
• It is widely extensible, unlike other languages which are very limited.
• Its extensions also support logic programming and design by contract.
• It free and open source software that is available anywhere.
• The language is very expressive hence it focuses even on the presentation aspects too.
• The language has a vast standard library.

Advantages of Python

A wide range of benefits of Python makes the language better than others. Some key perks of the languages are as follows.

• Python has a package of third-party modules-These modules help the language become compatible with other languages as well. So, Python can collaborate with other languages to offer a wide range of solutions. These modules are also the reason behind the language for being compatible with other languages.

• Extensive support libraries are also another perk of the programming language.It has several header files, string operations, and mathematical files incorporate in its libraries which makes programming tasks speedy, comfortable, and short.

• Other languages may require training and expert guidance- However, Python eliminates this requirement. The language is straightforward to learn and code. The code is also relatively shorter compared to other languages. The syntax and semantics of the languages are simple as well. So, it is an ideal beginner’s language too.

• Python has an object-oriented design which makes it suitable for real-world scenarios which focus on logical situations.The language is capable of developing codes that have data abstraction, data encapsulation, polymorphism, data binding, security and much. The approach of the language is also different from other languages which makes it renowned for building complex applications.

• The language also has spectacular features which make it interactive, dynamic, modular, portable, and extensible in C++.

All these features make Python extremely popular. According to GitHub Octoverse, it is ranked the second most popular language after JavaScript.

Applications of Python

Since Python has various characteristic features, it is famous around the world in multiple sectors. The primary applications of Python in the real-world scenario are as follows.

• The language comes handy in developing frameworks which could be micro or advanced. Hence, it is hugely popular in web development.

• It is also applicable in scientific computing which includes data analysis, handling libraries, visualizations, and much more.

• Python is also used in numeric computing too. In digital computing, the language handles parallel computing, boot camps, and other materials.

• In various schools, high school children are taught Python before teaching other languages as it is easier to learn. The language can also be pursued in higher studies as well in the future.

• Most of the graphic user interfaces are built or designed based on Python. Development of other software’s is also possible through this language.

• The languages also have a significant application in developing ERP systems, project management, and general-purpose applications too.

Key companies that use Python

Numerous companies use Python in real life on a full scale. Some giants include Google, Facebook, Instagram, Spotify, Quora, Netflix, Dropbox, Reddit, and much more.

The founded of Python worked in Google during the years 2005 to 2012. So, it is clear that the company uses Python. By 2016, Facebook and Instagram started using Python extensively. While Spotify incorporates more than 6000 processes whose implementation is through Python in their company.

Netflix and Dropbox considered the programming language around 2012. By 2015, Reddit also started using the language widely.

What is machine learning?

Machine learning is a method in which systems are capable of understanding scenarios without being programmed beforehand. It is an application of artificial intelligence which requires experience, instruction, patterns, and observation to conclude. There are various types of machine learning methods namely supervised algorithm, unsupervised algorithm, semi-supervised algorithm, and reinforcement algorithm.

Advantages of machine learning

Soon it is believed that artificial intelligence will rule over all the smart devices. One such application of artificial intelligence i.e. machine learning also has its advantages which it is famed for. Some of the perks of the method are as follows.

• Machine learning can adapt patterns and behaviors. The systems identify repeated trends and accordingly take decisions.

• This method of learning is known to improve efficacy. It also provides precise and accurate information over time. So, in future machine learning can be highly reliable with appropriate advancements.

• Machine learning methods do not require human guidance. Hence, they are very instantaneous, fast, and durable. They are reliable with decisions in the future.
The machine learning method along eliminates time lag or delays and can also check for viruses, bots, and other threats.

Python and machine learning

Machine learning is instrumental in the modern era. Python is a widely used language in the real world is known to be the base for machine learning.

The reasons why Python is suitable for machine learning are as follows

• Most of the artificial intelligence frameworks are supported by Python as it can handle various platforms.

• The language is very flexible compared to other languages which make it accessible for machine learning as it requires understanding scenarios based on specific patterns.

• Python is suitable for machine learning because it has special libraries incorporated within it. These libraries contain mathematical and logical operations which is an essential methodology for machine learning.

• The language has a more natural syntax and semantics to follow. So, it reduces the complexity of the code or the algorithms necessary for machine learning.

• It is the best language for beginners. Hence, it is a simple language that can reduce complications that arise during the machine learning method. The language is often described as a readable pseudo code.

• Python is excellent for machine learning because it is also a widely supported language. Hence, during the development of machine learning a large number of developers will support the development.

Programming languages are essential in today’s world. They help in making human thoughts turn into reality. The programming languages assist in defining structures, classes, and objects that deal with the real world. They also help to solve problems more efficiently and in an ordered fashion. Data can also be stored in these languages in such a way that they give better a view, analysis, and reports.

Programming languages are also great for designing anything ranging from essential to complex systems. Without these languages, the world would be an unbelievable place. Some renowned programming languages include Python, XML, HTML, JavaScript, and much more.

Python is a renowned high-level language with applications in various sectors. Major companies such as Google, Facebook, and Amazon use this programming language. The language has many key features and advantages which include compatibility with multiple platforms, standard libraries, object-orientated design, and simple interface. It is also an excellent language for machine learning.

Machine learning is a process where systems understand real-life scenarios without being programmed beforehand. These systems understand problems through repeated behavioral patterns just like humans and arrive at an efficient decision. As Python is an extremely flexible language with different platforms and other languages, it is ideal for machine learning.

Python also has special libraries and is widely supported by large developers. It is also simple language without any complex syntax and semantics, so it is ideal for developing machine learning.

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