Mining performance hotspots with JProfiler, jQAssistant, Neo4j and Pandas – Part 2: Root Cause Analysis

Mining performance hotspots with JProfiler, jQAssistant, Neo4j and Pandas – Part 2: Root Cause Analysis

All the work before was just there to get a nice graph model that feels more natural. Now comes the analysis part: As mentioned in the introduction, we don’t only want the hotspots that signal that something awkward happened, but also

the trigger in our application of the hotspot combined with
the information about the entry point (e. g. where in our application does the problem happen) and
(optionally) the request that causes the problem (to be able to localize the problem)…

How Philosophy screws up Software Development – Part 1: Introduction

How Philosophy screws up Software Development – Part 1: Introduction

I’ve been wondering why we do the same errors in software development over and over again and are expecting different results. It seems to me that we can’t see the fundamental issues that come with software development and thus aren’t learning that much in our guild. We are creating software professionally for half a century but still fail at completing projects on time, on budget and with suitable quality.

Storing Git commit information into Pandas’ DataFrame

Storing Git commit information into Pandas’ DataFrame

Software version control systems contain a huge amount of evolutionary data. It’s very common to mine these repositories to gain some insight about how the development of a software product works. But there is the need for some preprocessing of that data to avoid false analysis.

That’s why I show you how to read the commit information of a Git repository into Pandas’ DataFrame!