TestBash is a software testing and quality engineering conference led by the community and the team behind Ministry of Testing. It has been running since 2012 with many iterations and different locations. In the modern day MoTaverse it is hosted in Brighton (UK) annually. There are many things that make TestBash unique: it's an extension of a 24/7/365 community every talk is a keynote due to the single track nature a commitment to diversity a commitment to elevating new voices a commitment to new ideas a commitment to strong community ethics it is living proof of building an ethical business with the community at the heart every contributor gets rewarded the same (all travel expenses covered)

Change is inevitable, we explore how it is happening

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The image is a meme based on a scene from Toy Story featuring Woody and Buzz Lightyear. Woody looks concerned, while Buzz is enthusiastically gesturing with his arm. The meme contains two captions: Woody's caption (bottom left): "I DON'T KNOW HOW TO TEST" Buzz's caption (top right): "IT'S OK, WE HAVE THE MOTAVERSE" The meme humorously portrays someone unsure about testing, reassured by another person who believes the "Motaverse" (a likely reference to a testing tool, methodology, or system) will solve the problem.

Quality, testing and product building is a continuous effort, learn how from those that are exploring!

The MoTaverse is here to answer your questions you never knew needed answering!

We explore 5 ways to look at the difference between Test and Quality Engineers roles

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How essential are testing skills for a modern day Quality Engineering professional?

What is test efficiency?Test efficiency measures how well a testing process finds defects while using minimal time, effort, and resources. It shows how testing activities boost software quality and help meet delivery deadlines. Do you have any examples of test efficiency?Test efficiency uses metrics like defects found per test case, execution time, and defect leakage rate. For instance, if a team runs 100 test cases and finds 80 defects, the test suite's efficiency depends on how it uncovered these issues with minimal effort and without redundant tests. Why is test efficiency important?Test efficiency helps teams optimize testing strategies, cut unnecessary work, and maximize defect detection. Efficient testing creates faster development cycles, reduces costs, and makes software more reliable. What are the challenges of improving test efficiency?Challenges include finding the right balance between speed and quality, eliminating redundant tests, and achieving good coverage without excessive runtime. Poor test design and ineffective automation hurt efficiency. Teams improve efficiency through regular monitoring, refined test strategies, and smart automation tool use.

What is recovery testing?Recovery testing checks how well software bounces back from crashes and failures. It tests whether an application can restore itself after issues like power outages, network drops, or system failures. The goal is to confirm the system returns to normal operation with minimal data loss. Do you have any examples of recovery testing?Testers create failures on purpose to see how systems respond. They might:  Force-shutdown a database server and verify the app reconnects properly Cut network connections to see if the application handles the interruption Corrupting data files to test if backup systems work correctly Simulating power outages during critical operations Why is recovery testing important?Systems fail—it's pretty much inevitable. Recovery testing ensures applications handle these failures gracefully. It protects business operations from extended downtime, maintains data integrity during disruptions, builds user confidence in system reliability, and confirms disaster recovery plans actually work. What are the challenges of recovery testing?Recreating realistic failures poses several challenges.  Setting up environments that mimic production systems is difficult, as is determining acceptable recovery timeframes for different failures. Testers struggle to replicate complex scenarios like hardware failures or cyberattacks, and need to make sure automated recovery mechanisms work consistently. The process requires careful balance between thorough testing and avoiding damage to test environments.

What is defect density?Defect density measures how many bugs exist within a specific amount of code. It helps you quantify software quality objectively, and you can use it to compare modules, track improvements over time, and identify problematic code areas.  Defect density works by normalizing defect counts against code size, creating a consistent measurement across different components. Do you have any examples of defect density?Here's an example calculation that shows defect density for a typical software module: Total lines of code: 10,000 Number of defects found: 15 Size measurement: thousand lines of code (KLOC) = 10,000 ÷ 1,000 = 10 KLOC The formula for defect density is: Defect Density = Number of defects ÷ Size in KLOC So: Defect Density = 15 ÷ 10 = 1.5 defects/KLOC This means your module contains 1.5 bugs per thousand lines of code, which helps you compare its quality against industry standards or other modules. Why is defect density important?Defect density provides an objective quality measure. It lets you track improvements, compare components, and identify areas that need additional testing or refactoring. Lower defect density usually indicates better quality. What challenges exist with defect density?Defect density depends on accurate defect reporting and doesn't account for variations in complexity. A low score might indicate high quality… or insufficient testing. Different languages and projects also have different acceptable ranges.