Waydev helps managers to move from a feeling driven to a data-driven approach. Waydev includes concrete metrics for your daily stand-ups, 1-to-1 meetings, checking the history of the engineers work and benchmarking your stats with the industry.
Based on our record, Waydev should be more popular than Lavagna. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
For example, in our traditional approach, every step and process is defined and has to be adhered to. Any change has to go through multiple approvals. The scope in itself has a very limited scope or flexibility towards change. I am on the fence looking for resources and tools that will help to slowly execute and implement these changes. With regards to resources, I am currently looking at the scrum guide and with... Source: almost 2 years ago
When you’re ready to translate data into greater visibility, and this visibility into faster, more efficient teams, you can start looking at development analytics platforms like Waydev. - Source: dev.to / over 2 years ago
Lavagna - Java is bad, looks updated recently, no demo, not better than OP. Source: almost 2 years ago
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
SourceForge - The Complete Open-Source and Business Software Platform.
LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
openDesktop.org - The website openDesktop.
Haystack Analytics - Ship faster and improve team satisfaction with engineering analytics powered by your Github data.
OSOR - OSOR is the Open Source Observatory, a project to provide a framework for developing and executing autonomous observations.