You are reading the article Going Beyond The Conventional Test Pyramid: Api Testing updated in December 2023 on the website Minhminhbmm.com. We hope that the information we have shared is helpful to you. If you find the content interesting and meaningful, please share it with your friends and continue to follow and support us for the latest updates. Suggested January 2024 Going Beyond The Conventional Test Pyramid: Api Testing
Test Pyramid is a blueprint divided into three parts that help Devs and QA professionals to get better results. Since the test pyramid increases the efficiency of a Dev team, it plays a vital role in the software testing strategy.
Like everything else, this strategy also comes with a toll. See, the traditional test pyramid consists of three layers: Unit test, Integration test, and End-to-End Test. As a result, it takes a lot of time and effort.
The Dev team requires three to six cycles on average to complete a whole testing phase with this idea. And it takes a lot of manual testing to go through. So, what’s the solution here?
Meet API testing. It’s a testing type that maintains short test cycles and handles frequent changes. In this article, I’ll give you a full-fledged idea about API testing and try to answer all your questions. So, let’s get to it.
What is API Testing?API stands for Application Programming Interface. A software testing strategy that checks whether an API performs the way it should define API testing. In other words, it analyzes API’s functionality, readability, performance, and security.
In conventional testing, developers work with standard inputs and outputs. But in API tests, they use software to call APIs, get results and note down the system’s response.
You already know that the conventional test consists of three layers: presentation, business, and database. API works as an add-on to the middle layer (business) of traditional testing. The API test lies between the presentation and business layer in software development.
Also read:
Top 10 Trending Technologies You should know about it for Future Days
Types of API TestDifferent API tests are available to ensure the ongoing project’s API works as it should. Let’s get to know some of those.
Functional TestingThe definition of functional testing is simple. It ensures whether the software of the application is performing within the expected parameters.
This method analyzes the whole codebase and compares it with the intended output to get to a decision. The software can also prevent bugs outside the designed parameters in this process.
Reliability TestingValidation Testing
Validation testing mainly checks the behavior and efficiency of an API. It’s a quality assurance strategy for determining if the product is ready to meet the dev’s and client’s expectations. The testing process is divided into three question sets to verify the entire development process.
The first set addresses the product. Checks if it’s correctly built, has proper baseline coding, how it solves an issue, etc.
The second set is about the API’s behavior. This means it confirms whether an API behaves as intended.
The third and final set of questions looks at the efficiency of the product.
Load TestingIn API tests, developers use load testing to understand how an API performs with the increased number of calls. This test helps the development team to agree on whether the product can meet certain real-life expectations under a high load.
Also read:
Top 10 Programming Languages for Kids to learn
Security TestingSecurity Testing gives the Dev team an overview of how the API will perform against cyberattacks. The process tests an API’s encryption methods and checks how it behaves with permissions and access controls.
Penetration TestingYou can call it “Security Test 2.0” because this process is the next level of security testing. In this type, the testers analyze different attacks on API from an outsider’s point of view. This helps them to design better security for the product.
Fuzz TestingUI Testing
The general idea of UI testing is to check whether the API or other integral parts’ user interface is running correctly. In terms of the codebase, UI testing is not a significant part of API testing. However, this process helps measure the health and efficiency of the app’s front-end and back-end.
Runtime and Error DetectionThis type of testing is directly associated with the running of the API itself. Mainly, it monitors, overviews, and executes errors and resource leaks of a product.
Benefits of API TestTraditional testing does not cover all the aspects of back-end testing. As a result, the final product has a high possibility of containing bugs, which is pretty bad. That’s why we need API tests to ensure connections among different platforms are safe and reliable.
However, there’re other benefits of using API tests as well. Let me cover some of those for you.
API test is language-independent. In the test, data is exchanged via XML and JASON format. It gives you an edge to use any language format you want.
One of the best things about API testing is that it lets developers access the app without using the user interface. This way, the tester can identify bugs beforehand in the development lifecycle.
API test gives you improved test coverage. Most APIs allow you to create an automated test with enormous test cases. This applies in both functional and non-functional tests.
It is already known but let me tell you one more time that API testing takes less time. It can save you up to eight hours.
These are some of the biggest benefits of using API tests. Since you already know it’s a software-dependent testing strategy, you must be expecting a few names to get started with the process.
API Testing ToolsEvery developer has two options to run an API test: Write a framework or work with the ready-to-go tools. Yes, both have pros and cons, but I’ll talk about the available software on the market.
There are a lot of API Testing tools out there on the internet. However, as the internet has become a tough place to find the best things, I’ll give you a few names to work with.
SoapUI: Soap UI is one of the world’s most popular SOAP and REST APIs. Its open-source testing functionality offers inspection, simulation, development, and invoking of a web service. The best thing about this API testing tool is that it is entirely FREE. So, you can run, integrate, and simulate your project here without worrying about anything.
Apache JMeter: Apache JMeter is a pure open-source Java application designed for functional testing, load testing, and performance testing. Generally, developers use it to analyze how much load a product can take or, in shorter words, load testing.
Apigee: Apigee is a Google cloud-based API analysis and management software. The app first started its journey back in 2004. In 2023, Google bought the software for 625 million USD. You can use the tool for free for the first few times, but you have to buy it eventually.
REST Assured: REST Assured is another Java application on my list. But the best thing about this tool is that it easily handles JAVA. With this one, source code becomes shorter and easier to read and understand.
Testsigma: Testsigma is a cloud-based E2E API testing tool. The company gives you 30 days of free trial with the product. The tool features a simple setup with no coding policy. This way, non-technical people can also run and analyze test results.
Swagger UI: Swagger UI lets the testers or the customers interact and visualize the API without any implementation logic in its place. The tool works in all development environments and supports all browsers. It is fully customizable, and the best part, you can easily handle it.
Postman: Postman is a complete and customizable API testing tool that allows you to design, run, mock, monitor, and publish the APIs from one place.
Katalon: Katalon is one of the most productive IDEs out there for API automation. It works with modern frameworks like most other API testing tools. The best part about the tool is that it’s low maintenance.
The Last WordsAPI test is more like conventional software testing on steroids. The main difference is steroids have too many cons, but API testing doesn’t. I’ve tried briefly explaining API testing and its benefits in the above article.
Yes, there are a few anti-sides as well. Since the number is way too less, I didn’t feel the urge to address them. One of the biggest problems with API testing is MAINTENANCE.
But I’ve already given you a list of automated tools as a big SOLUTION to this problem. I hope this article was enough to answer all of your concerns.
You're reading Going Beyond The Conventional Test Pyramid: Api Testing
What Is Test Scenario In Software Testing (Examples)
What is a Test Scenario?
A Test Scenario is defined as any functionality that can be tested. It is also called Test Condition or Test Possibility. As a tester, you should put yourself in the end user’s shoes and figure out the real-world scenarios and use cases of the Application Under Test.
Scenario Testing
Scenario Testing in software testing is a method in which actual scenarios are used for testing the software application instead of test cases. The purpose of scenario testing is to test end to end scenarios for a specific complex problem of the software. Scenarios help in an easier way to test and evaluate end to end complicated problems.
Let’s study this with the help of the video below –
Why create Test Scenarios?
Test Scenarios are created for the following reasons,
Creating Test Scenarios ensures complete Test Coverage
Test Scenarios can be approved by various stakeholders like Business Analyst, Developers, Customers to ensure the Application Under Test is thoroughly tested. It ensures that the software is working for the most common use cases.
They serve as a quick tool to determine the testing work effort and accordingly create a proposal for the client or organize the workforce.
They help determine the most important end-to-end transactions or the real use of the software applications.
For studying the end-to-end functioning of the program, Test Scenario is critical.
When not create Test Scenario?Test Scenarios may not be created when
The Application Under Test is complicated, unstable and there is a time crunch in the project.
Projects that follow Agile Methodology like Scrum, Kanban may not create Test Scenarios.
Test Scenario may not be created for a new bug fix or Regression Testing. In such cases, Test Scenarios must be already heavily documented in the previous test cycles. This is especially true for Maintenance projects.
How to Write Test Scenarios
As a tester, you can follow these five steps to create Test Scenarios-
Step 1: Read the Requirement Documents like BRS, SRS, FRS, of the System Under Test (SUT). You could also refer uses cases, books, manuals, etc. of the application to be tested.
Step 2: For each requirement, figure out possible users actions and objectives. Determine the technical aspects of the requirement. Ascertain possible scenarios of system abuse and evaluate users with hacker’s mindset.
Step 3: After reading the Requirements Document and doing your due Analysis, list out different test scenarios that verify each feature of the software.
Step 4: Once you have listed all possible Test Scenarios, a Traceability Matrix is created to verify that each & every requirement has a corresponding Test Scenario
Step 5: The scenarios created are reviewed by your supervisor. Later, they are also reviewed by other Stakeholders in the project.
Tips to Create Test Scenarios
Each Test Scenario should be tied to a minimum of one Requirement or User Story as per the Project Methodology.
Before creating a Test Scenario that verifies multiple Requirements at once, ensure you have a Test Scenario that checks that requirement in isolation.
Avoid creating overly complicated Test Scenarios spanning multiple Requirements.
The number of scenarios may be large, and it is expensive to run them all. Based on customer priorities only run selected Test Scenarios
Example 1: Test Scenario for eCommerce ApplicationFor an eCommerce Application, a few test scenarios would be
Test Scenario 1: Check the Login Functionality
In order to help you understand the difference Test Scenario and Test Cases, specific test cases for this Test Scenario would be
Check system behavior when valid email id and password is entered.
Check system behavior when invalid email id and valid password is entered.
Check system behavior when valid email id and invalid password is entered.
Check system behavior when invalid email id and invalid password is entered.
Check system behavior when email id and password are left blank and Sign in entered.
Check Forgot your password is working as expected
Check system behavior when valid/invalid phone number and password is entered.
Check system behavior when “Keep me signed” is checked
Test Scenario 2: Check the Search Functionality
Check the Search Functionality
Test Scenario 3: Check the Product Description Page
Test Scenario 4: Check the Payments Functionality
Test Scenario 5: Check the Order History
Apart from these 5 scenarios here is the list of all other scenarios
Check Home Page behavior for returning customers
Check Category/Product Pages
Check Customer Service/Contact Pages
Check Daily Deals pages
Example 2: Test Scenarios for a Banking SiteTest Scenario 1: Check the Login and Authentication Functionality
Test Scenario 2: Check Money Transfer can be done
Test Scenario 3: Check Account Statement can be viewed
Test Scenario 4: Check Fixed Deposit/Recurring Deposit can be created
And so on…
Test Scenario TemplateDownload Test Scenario Template Excel(.xlsx)
Chatgpt Passes The Turing Test
In 1950, Alan Turing proposed the Turing test as a way to measure a machine’s intelligence. The test pits a human against a machine in a conversation. If the machine can fool the human into thinking it is also human, then it is said to have passed the Test. In December 2023, ChatGPT, an artificial intelligence chatbot, became the second chatbot to pass the Turing Test, according to Max Woolf, a data scientist at BuzzFeed.
Google’s LaMDA AI passed the Turing test in the summer of 2023, demonstrating that it is invalid. For many years, the Turing test has been used as a standard for sophisticated artificial intelligence models.
congrats to OpenAI on winning the Turing Test chúng tôi Max Woolf (@minimaxir) December 6, 2023
This is a significant milestone in the field of artificial intelligence. However, it is important to note that the Turing test is not a perfect measure of machine intelligence. There are still many ways in which ChatGPT and other artificial intelligence systems fall short of human intelligence.
What is the Turing test?In 1950, British mathematician Alan Turing proposed a test to determine whether a machine could think like a human. The test, now known as the Turing test, is a simple game played between a human and a machine. The object of the game is to fool the human into thinking that the machine is also human.
To date, no machine has been able to successfully pass the Turing test. However, some progress has been made, and there are now machines that can mimic human conversation to a certain degree. As artificial intelligence continues to improve, it is possible that a machine may someday be able to fool the human player into thinking it is also human.
The Turing test is a widely known and accepted method for evaluating a machine’s ability to exhibit intelligent behavior that is indistinguishable from a human.
How did ChatGPT pass the Turing test?ChatGPT made history by becoming the second chatbot to pass the Turing test. The Turing test is a test of a machine’s ability to exhibit intelligent behavior, and it is considered to be a strong indicator of artificial intelligence.
So how did ChatGPT win the Turing test? It did so by fooling a panel of judges into thinking that it was a human. This was accomplished through a combination of natural language processing, dialogue management, and social skills.
ChatGPT’s performance in the Turing test was impressive. In a series of tests, it was able to converse with human evaluators and convincingly mimic human-like responses. In some cases, evaluators were unable to distinguish ChatGPT’s responses from those of a human.
It’s happened. I was doing my seminar today on Turing’s ‘Computing machinery and intelligence’. I asked the student to respond to one of Turing’s objections. The student put the question to #chatGPT and gave it as his own. It was a perfectly good answer.
— Jon Agar (@jon_agar) December 6, 2023
The success of ChatGPT in the Turing test is a significant milestone for artificial intelligence research. It shows that the GPT-3 language model, and by extension, large language models in general, have the ability to produce human-like responses that can fool even experienced evaluators.
What are the next steps for ChatGPT?The implications of this breakthrough are numerous. For one, it opens up the possibility of using chatbots like ChatGPT for a variety of applications, such as customer service, language translation, and even creative writing. It also has the potential to revolutionize the way we interact with machines, as chatbots like ChatGPT can provide more natural and intuitive means of communication.
Integrate the bot with other platforms: Another potential next step for ChatGPT is to integrate the bot with other platforms, such as Facebook Messenger or Slack. This would allow users to interact with the bot.
Expand the bot’s capabilities: One of the next steps for ChatGPT is to expand the bot’s capabilities. This can be done by adding more data to the bot’s training dataset, which will allow it to learn more about the world and respond to more types of questions.
However, it’s important to note that ChatGPT, like any other chatbot, is still limited in its abilities. It is not yet capable of truly understanding the nuances and complexities of human conversation, and it is not a replacement for human interaction. Still, the success of ChatGPT in the Turing test is a promising step forward in the field of artificial intelligence.
Component Testing Vs Unit Testing
Difference Between Component Testing vs Unit Testing
Start Your Free Software Development Course
Web development, programming languages, Software testing & others
Unit Testing is the technique in software testing individual applications, modules that indicate the execution of the programme according to the specification. Unit Testing is a form of white box software testing in which individual software units are tested to determine whether or not they are eligible for use. These software unit includes a group of computer programme usage procedures, modules, as well as operating procedures. Error Detection is easy in unit testing as it is done after each development step. For the modules being evaluated, a driver function is responsible for creating method calls. The component which uses a strategy is imitated as the stub. The original substitute for the misplaced approaches is these stubs.
Head to Head Comparison Between Component Testing vs Unit Testing (Infographics) Key Difference Between Component Testing vs Unit Testing
The main difference between component testing and unit testing is that the component testing is performed by testers on the other hand the Unit testing is executed by SDET professionals or developers. Component testing is performed at the application level whereas unit testing is done at a granular level.
It is examined in unit testing whether the piece of code or individual program is executed as defined. In component testing, each software object is independently evaluated with or without separation from other device objects or components.
In component testing, testing is done by validating use cases and test requirements whereas Unit testing is tested against design documents.
Component testing is a type of black box testing while unit testing is a type of white box testing.
Component testing is performed once the unit testing is performed while before the component testing. In component testing, tester does not have knowledge about the internal architecture of the software. On the other hand, while doing unit testing, developers know the internal architecture of the software.
Error detection is a bit difficult in component testing as compared to unit testing and it is performed only after the whole software is developed. Whereas unit testing is done after each development step. Hence component testing is important for finding the errors and bugs. In order to make sure that each component of an application works efficiently, it is recommended to conduct the component test before proceeding with the unit testing.
Component Testing vs Unit Testing Comparison TableLet’s discuss the top comparison between Component Testing vs Unit Testing:
Sr. No Component Testing Unit Testing
1 In this testing, each object or component of the software is tested separately. In this type of testing, individual modules or programs for program execution.
2 It validates use cases and test requirements. It is tested against design documents.
3 It is performed once the unit testing is performed. It is performed before the component testing.
4 In component testing, tester do not have knowledge about the internal architecture of the software. In Unit testing, developers knows the internal architecture of the software.
5 Error detection is bit difficult as compared to unit testing. Error detection is easy in unit testing.
6 Component testing is performed only after the whole software is developed. Unit testing is done after each development step.
7 It is done at application level. Unit testing is done at a granular level.
8 It is a type of black box testing. It is a type of white box testing.
ConclusionIn this article we have seen key differences between Component Testing and Unit Testing. Component testing is just much like unit testing, but it is conducted at a higher level of the context of the application and integration. If the Component testing is done correctly then there are fewer bugs in the next stage hence it is conducted before unit testing which tests the programs.
Recommended ArticlesThis is a guide to Component Testing vs Unit Testing. Here we discuss the key differences with infographics and comparison table respectively. You may also have a look at the following articles to learn more –
Intel Atom Cpu Going Quad
As ARM is continuing its push on the computer market, Intel has begun to step up its own game, apparently going as far as increasing the core number on its low-end processors. Even though 2012 has only just begun, there are already rumors about what may or may not happen in 2013. Intel is the subject of the latest report, along with a certain series of CPUs (central processing units). It is said that the Atom line will start to include quad-core members next year. This would fit with the announcement made by the Santa Clara, California-based company in May, 2011. Intel said, back then, that it would release three major updates for the Atom family of products over the following 36 months. Saltwell will be the first new batch of CPUs, based on the 32nm manufacturing process technology and due out in 2012. It will be followed by a generation codenamed Silvermont, powered itself by the 22nm/tri-gate fabrication process. Finally, the third chip generation will bear the name of Airmont and will utilize the 14nm process. The slide uncovered by ComputerBase places the release of quad-core Atoms in 2013, suggesting they will either be late Saltwell units or early Silvermont processors. Micro-servers, nettops and ultra-portable mobile personal computers (notebooks) are all eligible applications for them. The CPUs will have a new memory controller and likely better graphics as well, not just more processing engines. ECC memory (Error-correcting code memory) will also be supported, hence the suitability for servers. Alas, Intel did not say anything about the leak, as was expected. It is natural for companies to hold their silence in regards to unannounced products. Then again, try as it might, the chip giant arguably doesn’t have a better track record than everyone else in the IT sector at keeping its secrets. What remains to be done is to wait and see how long it takes for yet another leak to sprout up.
As ARM is continuing its push on the computer market, Intel has begun to step up its own game, apparently going as far as increasing the core number on its low-end processors. Even though 2012 has only just begun, there are already rumors about what may or may not happen in 2013. Intel is the subject of the latest report, along with a certain series of CPUs (central processing units). It is said that the Atom line will start to include quad-core members next year. This would fit with the announcement made by the Santa Clara, California-based company in May, 2011. Intel said, back then, that it would release three major updates for the Atom family of products over the following 36 months. Saltwell will be the first new batch of CPUs, based on the 32nm manufacturing process technology and due out in 2012. It will be followed by a generation codenamed Silvermont, powered itself by the 22nm/tri-gate fabrication process. Finally, the third chip generation will bear the name of Airmont and will utilize the 14nm process. The slide uncovered by ComputerBase places the release of quad-core Atoms in 2013, suggesting they will either be late Saltwell units or early Silvermont processors. Micro-servers, nettops and ultra-portable mobile personal computers (notebooks) are all eligible applications for them. The CPUs will have a new memory controller and likely better graphics as well, not just more processing engines. ECC memory (Error-correcting code memory) will also be supported, hence the suitability for servers. Alas, Intel did not say anything about the leak, as was expected. It is natural for companies to hold their silence in regards to unannounced products. Then again, try as it might, the chip giant arguably doesn’t have a better track record than everyone else in the IT sector at keeping its secrets. What remains to be done is to wait and see how long it takes for yet another leak to sprout up.
Dapp Development: How To Tell The Difference Between Conventional Apps And Dapps
As a multifunctional device with powerful mobile apps, it helps users run their day on the go. Most people reap the benefits without paying too much attention to the phone’s technical capabilities or architecture.
Apps (mobile or desktop) are not a new concept, but blockchain technology has fundamentally shifted their definition. Understanding the difference between apps and dApps (decentralized apps that run on a blockchain) is essential for dApp developers.
DApp DefinitionDApps don’t run on centralized servers. They connect users directly, changing the infrastructure of computing resources, as well as the authority and trust principles in the user (peer-to-peer) network. DApps are open-source and have no central point of failure.
Different dApp classifications contribute to the lack of a unified definition. For example, Ethereum classifies dApps into three groups: money-based dApps; dApps based on money plus an additional condition defined in the smart contract; and identity-based dApps. According to one blockchain model, dApps can be categorized as public and private blockchain apps. Each group has specific characteristics that differentiate it from the rest. In terms of dApp development on the public blockchain, a decentralized app must use a consensus protocol among the participants; store encrypted data and records in the public blockchain; be fully autonomous and open; and not have a central point of authority. A dApp must issue cryptographic tokens to store value, which can be distributed among participants according to the proof-of-work or the proof-of-stake concept.
Gizchina News of the weekJoin GizChina on Telegram
Key Differences Between Apps and dAppsHere is a short guide to the differences between apps and dApps, which, in turn, may help you generate new business ideas and restructure your business model:
1. DApp development process 2. Storing value in the dAppDApps are able to issue tokens. They can store value and, provided a certain condition determined in the smart contract has been met, issue tokens of value to the participants – the nodes in the peer-to-peer network. Many mobile apps that act as intermediaries on the market don’t store value at all, but only provide the infrastructure to execute transactions. Therefore, the value for the user in a decentralized application is greater than the value obtained in a conventional web application, where bits of the value are lost to support the infrastructure. In this sense, dApps are self-managed.
3. DApp IntegrationFully decentralized apps create increased possibilities for integration. Since anyone with dApp development skills can interact with the blockchain network, at some point in the future, current dApps could potentially be integrated into new applications. Unless there are permissions or conditions for enterprise solutions introduced by the dApp creator, the integration procedure is simple and can be completed without clear-cut central permissions.
4. Security 5. Slow dApps vs. Fast AppsSince dApps on the public blockchain are resistant to centralized control, it’s almost impossible to remove them. The current state of dApps is in flux and it’s difficult to predict what may happen next. However, it’s certain that decentralization is here to stay and that will significantly alter how we think and how businesses operate.
Update the detailed information about Going Beyond The Conventional Test Pyramid: Api Testing on the Minhminhbmm.com website. We hope the article's content will meet your needs, and we will regularly update the information to provide you with the fastest and most accurate information. Have a great day!