Libraries & Frameworks

The blog discusses how autonomous testing redefines software QA by leveraging AI and ML to enhance adaptability, scalability, and efficiency. Unlike traditional QA methods, autonomous testing minimizes human intervention and accelerates testing processes. With intelligent decision-making, self-healing capabilities, and broader test coverage, autonomous testing ensures flawless applications while reducing costs and time to market.
The post How Autonomous Testing is Transforming the Software QA Landscape first appeared on TestingXperts.

What solutions do you use to avoid tight coupling between classes when using utility classes like waithelpers, data formatting, selenium utils etc? I am using these classes having static methods, which is not ideal in terms of coupling

Human Resource Management Systems, or HRMS, are essential for organizations. They make HR processes and hr tasks easier, especially during the hiring process. They also help keep everything compliant and manage employee data management well. This includes things like performance evaluations. An effective HRMS software application is important for testing. It makes sure the system
The post HRMS Testing: A Comprehensive Guide with Checklist appeared first on Codoid.

When working with substantial datasets in Laravel applications, sending all data at once can create performance bottlenecks and memory issues.…

This week, the Laravel team released v11.34, with a Request::fluent() method, a Number spellOrdinal() helper, conditional route definitions, shorthand fakes…

I’ve got a C# framework using Playwright.NET and Reqnroll (formerly SpecFlow).
I’ve moved common steps across multiple projects into a separate project within the same solution to enable easy reuse.
I’ve referenced the binding assembly in the reqnroll.json file and the tests run fine.
All projects have the Reqnroll.NUnit NuGet package installed. I’d like to remove the package from all but the shared project – the dependency should mean that the other projects get the package from my shared project.
I’ve been able to do this with other packages, like Playwright – that’s only installed in the shared project and the other projects all get at it via the project dependencies.
But when I remove Reqnroll.NUnit, code I have in a [BeforeTestRun] hook does not run. [BeforeScenario] does but I need [BeforeTestRun] too. If I re-add the package to the project then [BeforeTestRun] works as normal. But the moment I remove it (keeping it in the shared project) then [BeforeTestRun] gets skipped.
Any idea why?

Testing an algorithm is really important. It ensures the algorithm works correctly. It also looks at how well it performs in various situations. Whether you are dealing with a sorting algorithm, a machine learning model, or a more complex one, a good testing process can find any issues before you start using it. Here’s a
The post How to Test an Algorithm appeared first on Codoid.

When building web applications, dealing with optional inputs and providing default values is a common task. Laravel simplifies this common…

Warden is a Laravel package that performs security audits on your Composer dependencies and provides automated notifications for vulnerabilities. With…

A media picker plugin for FilamentPHP. Source: Read More 

In today’s world, where mobile devices are becoming increasingly popular, ensuring your website and its various user interfaces and elements are accessible and functional on all screen sizes is more important than ever. Responsive web design (RWD) allows your website to adapt its layout to the size of the screen it is being viewed on,
The post Best Practices for Responsive Web Design appeared first on Codoid.

Exception in thread “main” org.openqa.selenium.SessionNotCreatedException: Could not start a new session. Possible causes are invalid address of the remote server or browser start-up failure.
Host info: host: ‘XXXXX’, ip: ‘XXXXX’
Build info: version: ‘4.26.0’, revision: ’69f9e5e’
System info: os.name: ‘Windows 11’, os.arch: ‘amd64’, os.version: ‘10.0’, java.version: ‘23.0.1’
Driver info: io.appium.java_client.android.AndroidDriver
Command: [null, newSession {capabilities=[Capabilities {app: C:UsersxxxxxxOneDriveDoc…, appActivity: app.superssmart.ui.MainActi…, appPackage: app.superssmart, browserName: , deviceName: emulator-5554, noReset: true, platformName: ANDROID}]}]
Capabilities {app: C:UsersxxxxOneDriveDoc…, appActivity: app.superssmart.ui.MainActi…, appPackage: app.superssmart, browserName: , deviceName: emulator-5554, noReset: true, platformName: ANDROID}
at org.openqa.selenium.remote.RemoteWebDriver.execute(RemoteWebDriver.java:563)
at io.appium.java_client.AppiumDriver.startSession(AppiumDriver.java:270)
at org.openqa.selenium.remote.RemoteWebDriver.<init>(RemoteWebDriver.java:174)
at io.appium.java_client.AppiumDriver.<init>(AppiumDriver.java:91)
at io.appium.java_client.AppiumDriver.<init>(AppiumDriver.java:103)
at io.appium.java_client.android.AndroidDriver.<init>(AndroidDriver.java:109)
at appium.test.App_Main.main(App_Main.java:29)
Caused by: java.lang.IllegalArgumentException: Illegal key values seen in w3c capabilities: [app, appActivity, appPackage, deviceName, noReset]
at org.openqa.selenium.remote.NewSessionPayload.lambda$validate$5(NewSessionPayload.java:163)
at java.base/java.util.stream.ReferencePipeline$15$1.accept(ReferencePipeline.java:580)
at java.base/java.util.stream.ReferencePipeline$15$1.accept(ReferencePipeline.java:581)
at java.base/java.util.stream.ReferencePipeline$3$1.accept(ReferencePipeline.java:215)
at java.base/java.util.stream.ReferencePipeline$15$1.accept(ReferencePipeline.java:581)
at java.base/java.util.ArrayList$ArrayListSpliterator.forEachRemaining(ArrayList.java:1709)
at java.base/java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:570)
at java.base/java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:560)
at java.base/java.util.stream.ForEachOps$ForEachOp.evaluateSequential(ForEachOps.java:151)
at java.base/java.util.stream.ForEachOps$ForEachOp$OfRef.evaluateSequential(ForEachOps.java:174)
at java.base/java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:265)
at java.base/java.util.stream.ReferencePipeline.forEach(ReferencePipeline.java:636)
at org.openqa.selenium.remote.NewSessionPayload.validate(NewSessionPayload.java:167)
at org.openqa.selenium.remote.NewSessionPayload.<init>(NewSessionPayload.java:70)
at org.openqa.selenium.remote.NewSessionPayload.create(NewSessionPayload.java:99)
at org.openqa.selenium.remote.NewSessionPayload.create(NewSessionPayload.java:84)
at org.openqa.selenium.remote.ProtocolHandshake.createSession(ProtocolHandshake.java:60)
at io.appium.java_client.remote.AppiumCommandExecutor.createSession(AppiumCommandExecutor.java:176)
at io.appium.java_client.remote.AppiumCommandExecutor.execute(AppiumCommandExecutor.java:237)
at org.openqa.selenium.remote.RemoteWebDriver.execute(RemoteWebDriver.java:545)
… 6 more

Code:
public static AndroidDriver driver;
public static void main(String[] args) throws MalformedURLException, InterruptedException {
File appDir = new File(“C:\Users\keert\OneDrive\Documents\App”);
File app=new File(appDir,”app.apk”);
DesiredCapabilities cap=new DesiredCapabilities();
cap.setCapability(CapabilityType.BROWSER_NAME, “”);
cap.setCapability(“platformName”, “Android”);
cap.setCapability(“app”, app.getAbsolutePath());
cap.setCapability(“deviceName”, “emulator-5554”);
cap.setCapability(“appPackage”, “app.superssmart”);
cap.setCapability(“appActivity”, “app.superssmart.ui.MainActivity”);
cap.setCapability(“noReset”, true);

driver=new AndroidDriver(new URL(“http://127.0.0.1:4723/”),cap);

The blog discusses how predictive data analytics transforms quality assurance by enabling businesses to anticipate software issues and optimize testing. Leveraging AI, ML, and robust data models empowers QA teams to detect patterns, improve test case efficiency, and prioritize tasks for faster releases and superior outcomes.
The post How Predictive Data Analytics Transforms Quality Assurance  first appeared on TestingXperts.

I’m currently working on a project that involves multiple services (some distributed across a cluster like Elasticsearch) running inside Docker containers. The whole system can be started through a docker-compose file with custom setup if required. To validate these services against specific requirements, I’ve set up a separate test project.
We’ve developed a comprehensive test suite to ensure the system functions as expected. However, one challenge remains: collecting logs from individual or multiple Docker services for a given test case. Ideally, I’d like to save the logs generated during each test run in the corresponding test results.
Upon researching common testing frameworks and practices, I identified similar scenarios:

Before running a test, reset the service’s logs
After completing a test, collect the logs

I’ve explored various possible solutions, including:

Using Docker Testcontainers: While this approach is promising, it requires custom-built services and integrating them, which seems overly complex.
Resetting all containers to clear their logs: This method is impractical due to the significant time it takes, given the large number of different services involved.
Truncating logs: Stopping a container, truncating its logs, and then restarting it works but can be slow.
Rotating logs: Could this be achieved through Docker or by utilizing a central log service?

I’m confident that others have encountered similar issues in the past. I would greatly appreciate any suggestions or ideas on how to address this problem.

The code review process is crucial in Software Development, guided by a checklist to ensure the software is high quality and meets standards. During the review, one or more team members examine the source code closely, looking for defects and verifying that it follows coding guidelines. This practice improves the entire codebase by catching bugs
The post The Importance of Code Reviews: Tips and Best Practices appeared first on Codoid.

Generative AI is becoming the new norm, widely used and more accessible to the public via platforms like ChatGPT or Meta AI, which appear on social media platforms like WhatsApp and Instagram Messenger.
Despite its being fundamentally a transformers that break sentences into tokens and predict the next word, the implications and applications are vast. However, these GPT models currently lack human-like understanding. Which might cause reliability issues and others, but considering its capabilities the new trend of agentic AI is on rise this highlights the importance of having a well-defined testing approach.
I wanted to ask:

What are the patterns or testing strategies you are following beyond basic testing strategies?
What’s your approach to identify and fix, do you follow any checkmarks ?

AI Hallucination
Fairness and Bias
Security & Ethical Issue
Coherence and relevance
Robustness and Reliability
Explainability and Interpretability
Include others you have Identified

Here are some of my observations:
Example 1: AI Hallucination
Issue: Generating factually incorrect or nonsensical outputs, The response provided has data that is not reliable however its sounds plausible or true.
Solution: Fact-checking, Human-in-the-loop, Prompt engineering, Training data quality, Model fine-tuning, Post-processing
Example 2: Bias and Fairness
Issue: Based on the data, Generating outputs that unfairly favor certain groups.
Solution: Bias audits, Fairness metrics, Diverse training data
Example 3: Adherence to Instructions
Issue: With tools like Meta AI Agents and similar others in Salesforce, we need to check if the response adheres to the instructions, as sometimes it fails to follow the guidelines and guardrails.
Solution: It might be an issue with the instruction, but we need to go back to basics and test against each instruction to check if it is followed or not.
This might become hectic any alternate
Example 4: Not in Coherence Knowledge Article Boundaries
Issue: GPT models used as chatbots with a set of knowledge articles sometimes provide results outside the set of knowledge articles as a reference.
Solution: Coherence metrics, Prompt design, Feedback
Example 5: Chain of Thought
Issue: In some cases, the generative AI assumes continuity with earlier conversations within the window period, which might cause unnecessary references.
Solution: There should be instructions to cross-verify and provide a note.
Most of these issues can be addressed with effective prompt engineering. However, I am curious about your methods for breaking these issues and any observations you have identified.

SaaSykit is a feature-rich Laravel-based SaaS starter kit designed to accelerate the development of SaaS applications. It provides developers with…

It’s that time of year again. You can save massive amounts of money on everything from training courses to complete…

The blog discusses the transformative capabilities of DevOps consulting services in accelerating product development, enhancing collaboration, and improving software quality. Learn how customized DevOps pipelines, automation, and continuous improvement drive digital evolution and keep organizations competitive in a fast-paced landscape.
The post DevOps Consulting: The Catalyst for Digital Evolution   first appeared on TestingXperts.

I DLed a password-protection supposed-.exe from FH — FolderLock — and it was flagged by Jotti with a good deal of malware, adware, then for giggles with VirusTotal and about half flagged it, including with ‘FileHippo’ in the name. I say ‘supposed’ because the DL ends with .exe, and File Explorer does say it’s an application, but the description is “FH Manager.”