Estimating the size, cost, and types of Technical Debt

Author

Curtis, Bill ; Sappidi, Jay ; Szynkarski, Alexandra

Author_Institution

CAST, Fort Worth, TX, USA

fYear

2012

fDate

5-5 June 2012

Firstpage

49

Lastpage

53

Abstract

This study summarizes results of a study of Technical Debt across 745 business applications comprising 365 million lines of code collected from 160 companies in 10 industry segments. These applications were submitted to a static analysis that evaluates quality within and across application layers that may be coded in different languages. The analysis consists of evaluating the application against a repository of over 1200 rules of good architectural and coding practice. A formula for estimating Technical Debt with adjustable parameters is presented. Results are presented for Technical Debt across the entire sample as well as for different programming languages and quality factors.

Keywords

business data processing; program diagnostics; programming languages; software architecture; software cost estimation; software performance evaluation; software quality; adjustable parameters; architectural practice; business applications; coding practice; cost estimation; industry segments; programming languages; quality evaluation; quality factors; repository; size estimation; static analysis; technical debt; Encoding; ISO standards; Industries; Organizations; Production; Software; benchmarking; software metrics; software structural quality; static analysis; technical debt;

fLanguage

English

Publisher

ieee

Conference_Titel

Managing Technical Debt (MTD), 2012 Third International Workshop on

Conference_Location

Zurich

Print_ISBN

978-1-4673-1748-1

Type

conf

DOI

10.1109/MTD.2012.6226000

Filename

6226000