This is the dataset and source code of the paper: On the Detection of Performance Regression Introducing Code Changes: Experience from the Git Project The STEP-1-AND-2 folder is for doig things on digitalocean The STEP-3 folder is for running lizard on each commit The STEP-4 folder is for basically everything else "messing-with-understand" is the code i used to run understand on every commit "nn" is the code i used when toying with neural nets instead of perphec
Regression benchmarking is a methodology for detecting performance changes in software by periodic ...
In order to find performance changes at code level, Peass (https://github.com/DaGeRe/peass) uses uni...
Performance regression testing is a cost-intensive task as it delays the system development. The pro...
The objective of this work is to improve look up for changes in source code performance and help to ...
During software evolution, the source code of a system frequently changes due to bug fixes or new fe...
ii Author’s Declaration for Electronic Submission of a Thesis I hereby declare that I am the sole au...
Even the addition of a single extra field or control statement in the source code of a large-scale s...
This dataset accompanies the article ICPE 2016 "Learning from Source Code History to Identify Perfor...
As a software application is developed and maintained, changes to the source code may cause unintent...
1. The spreadsheet "Perf Issue Empirical Data Package.xlsx" contains the details of data extraction...
The development cycle of large software is necessarily prone to introducing software errors that are...
The quality of code can be measured using source code metrics. Looking at the trends of these metric...
Modern software development is performed by developing features in isolated branches by each member ...
<p>The code base for the automated performance regression detection in microservice architectures pr...
Node-level performance is one of the factors that may limit applications from reaching the supercomp...
Regression benchmarking is a methodology for detecting performance changes in software by periodic ...
In order to find performance changes at code level, Peass (https://github.com/DaGeRe/peass) uses uni...
Performance regression testing is a cost-intensive task as it delays the system development. The pro...
The objective of this work is to improve look up for changes in source code performance and help to ...
During software evolution, the source code of a system frequently changes due to bug fixes or new fe...
ii Author’s Declaration for Electronic Submission of a Thesis I hereby declare that I am the sole au...
Even the addition of a single extra field or control statement in the source code of a large-scale s...
This dataset accompanies the article ICPE 2016 "Learning from Source Code History to Identify Perfor...
As a software application is developed and maintained, changes to the source code may cause unintent...
1. The spreadsheet "Perf Issue Empirical Data Package.xlsx" contains the details of data extraction...
The development cycle of large software is necessarily prone to introducing software errors that are...
The quality of code can be measured using source code metrics. Looking at the trends of these metric...
Modern software development is performed by developing features in isolated branches by each member ...
<p>The code base for the automated performance regression detection in microservice architectures pr...
Node-level performance is one of the factors that may limit applications from reaching the supercomp...
Regression benchmarking is a methodology for detecting performance changes in software by periodic ...
In order to find performance changes at code level, Peass (https://github.com/DaGeRe/peass) uses uni...
Performance regression testing is a cost-intensive task as it delays the system development. The pro...