Ministry of Testing

Back to the basics: Rethinking how we use AI in testing

A simple rule of thumb: In general, AI is best reserved for well-defined, repetitive tasks. This includes anything that ...
GitHub

AgentRun: Run AI Generated Code Safely

AgentRun is a Python library that makes it easy to run Python code safely from large language models (LLMs) with a single line of code. Built on top of the Docker Python SDK and RestrictedPython, it ...
IEEE

Complete Data Using Exploratory Data Analysis and ML Algorithms

Abstract: Often real-world data contains missing values/ information which is not easily obtainable. These missing values can be because of any reason. Some people might not be comfortable providing a ...
IEEE

Boosting Code-line-level Defect Prediction with Spectrum Information and Causality Analysis

Abstract: Code-line-Ievel defect prediction (CLDP) is an effective technique to incorporate comprehensive measures for buggy line identification to optimize efforts in Software Quality Assurance ...
GitHub

indravinesh919-ux/Task-5-Exploratory-Data-Analysis-EDA-

Data loading and inspection Handling missing values analysis Statistical summary using describe() Visual analysis using histograms, boxplots, count plots, scatter plots, and heatmaps Identified ...