Insights from Git Logs for Testing teams

As testers, we are always looking for various tools that can help us enhance our testing. Our go-to tools are mostly defect tracking tools, exploratory testing of the product, and documentation. While these have been important, what if we could gain a fresh perspective by exploring the development activity? How might this aid us in aligning our testing efforts more […]

Build a microVM using Firecracker

This post will cover how to create a custom microVM using Firecracker. We will add a simple Flask app to the microVM. By doing so, you will learn how to install custom packages to your own microVM. This post assumes that you have used Firecracker and tried out a basic example already. Why this post? AWS Lambda stands out as […]

A brief introduction to Accessibility Testing using Axe

This post will discuss accessibility testing – specifically the portions of using Axe on your browser as well as integrating Axe with your automated test suite. We will also briefly discuss few nuances of introducing Accessibility testing into your team’s workflow. This post will NOT cover the basics of Accessibility tests, the standards used, etc. Overview Qxf2’s clients are startups […]

Data Validation Using Assistants API: Exploring AI-driven approach

This post extends my previous exploration of conducting data validation tasks using Large Language Models like ChatGPT. To provide context, at Qxf2, we execute a series of data quality tests using Great Expectations. Initially, we explored the possibility of employing ChatGPT for these validations, but it faced challenges in performing them effectively. Now, with the recent release of more advanced […]

Fine Tuning Model Evaluation using ROC and Precision Recall curves

Evaluating machine learning models is crucial for understanding their performance characteristics. In this blog post, we explore how ROC and Precision Recall curves can be used to improve the way we evaluate models. Additionally, we delve into the practical aspect of using these curves across various thresholds, customizing the model for specific requirements and achieving optimal performance. Why this post […]

Understanding Text Classification Models with LIME

Why this post? I’ve always been wondering how Machine learning models functions as black boxes, making predictions based on patterns learned from data. Despite the impressive accuracy, understanding the factors and features that influenced a particular prediction and the decision-making process is crucial and challenging task. The lack of transparency in these models adds complexity making their internal workings less […]

Tcases: Auto-generating API Tests

Most development teams that Qxf2 works with, describe and document their APIs using Open API specification. This means, there is a set structure for folks to write tests. Handcrafting the simple test cases can be cumbersome and time consuming. Given there is a set structure, we started to look out for solutions that could create API tests based on an […]

Testing Charts using GPT-4 with Vision model

This post builds upon my prior exploration of testing charts with Transformers using the Visual Question Answering approach. I had presented charts to Transformers models like Pix2Struct and matcha from Google (which were specifically trained on charts) and then queried with questions. The outcomes proved satisfactory when the charts were well-defined with clearly labeled data points. Now, with the recent […]

Testing DALL-E by creating single panel cartoons

I tested DALL-E for a specific real-world use case. I wanted to see how good it was for producing single panel cartoons. My testing has uncovered several promising aspects, some problems that need to be addressed and an interesting testing technique for DALL-E and ChatGPT like applications. I tried summarizing my findings in a blog post like an engineer would. […]