Technical Debt estimates and stats by technology
This documentation page is deprecated as the Technical Debt calculation methodology has been revisited. See this page instead.
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 |