Technical Debt estimates and stats by technology

As detailed in the Indicator & Methodology deck, CAST Highlight leverages software quality measures and statistics provided by the application benchmarking solution CAST Appmarq to estimate the amount and density of technical debt that your application code base may have accumulated across iterations. The table below lists the technical debt statistics per line of code technology-wise.

 

Technology Min. Lower Quartile
(25%)
Median
(50%)
Upper Quartile
(75%)
Max.
Abap/SAP 0.031606 1.09276 1.614014 1.76796 3.659672718
C 0.035744 1.202878 2.100075 2.937979 15.22273
COBOL 0.02 1.127387 1.881467 2.751253 8.799646
C++ 0.55435 1.982766 3.544059 5.793916 20.76226334
C# 0.054696 2.539813 3.493363 4.89939 13.78143
Java 0.022764 3.712118 5.88523 7.856834 20.00208
JavaScript 0.022764 3.712118 5.88523 7.856834 20.00208
SHELL, BASH, KSH 0.031606 1.09276 1.614014 1.76796 3.659672718
Objective-C 0.55435 1.982766 3.544059 5.793916 20.76226334
PHP 0.022764 3.712118 5.88523 7.856834 20.00208
PL1 0.031606 1.09276 1.614014 1.76796 3.659672718
PL/SQL 1.892085 2.649112 2.863325 3.730918 4.430902
Transact-SQL 1.892085 2.649112 2.863325 3.730918 4.430902
VB/VB.Net 0.054696 2.539813 3.493363 4.89939 13.78143
JSP 0.022764 3.712118 5.88523 7.856834 20.00208
Python 0.031606 1.09276 1.614014 1.76796 3.659672718
Powerbuilder 0.054696 2.539813 3.493363 4.89939 13.78143