Development

Best Practices for Responsive Web Design

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.

Development

How Predictive Data Analytics Transforms Quality Assurance 

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.

Docker Container Logging during Testing

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 Importance of Code Reviews: Tips and Best Practices

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.

How are you testing your Generative AI ? What testing strategies have you discovered

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.

Collective #884

Have a dialog * tududi * Agree * Tailwind CSS easing classes Source: Read More 

Case Study: Nod Coding Bootcamp

Follow Waaark behind the scenes of Nod Coding Bootcamp’s new website transformation and discover how we turned a lacklustre site…

Development

CodeSOD: Hall of Mirrors

Robert was diagnosing a problem in a reporting module. The application code ran a fairly simple query- SELECT field1, field2,…

QueryBuilder in Action Part 1

In this blog, we’ll cover how to perform basic data operations using the Total.js QueryBuilder. This first part will introduce…