際際滷shows by User: OnTechnicalDebt / http://www.slideshare.net/images/logo.gif 際際滷shows by User: OnTechnicalDebt / Tue, 12 Jun 2012 08:51:21 GMT 際際滷Share feed for 際際滷shows by User: OnTechnicalDebt Estimating the principal of Technical Debt - Dr. Bill Curtis - WTD '12 /slideshow/estimating-the-principal-of-technical-debt-curtis-wtd12/13293394 estimatingtheprincipaloftechnicaldebt-curtis-wtd12-120612085123-phpapp02
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.]]>
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.]]> Tue, 12 Jun 2012 08:51:21 GMT /slideshow/estimating-the-principal-of-technical-debt-curtis-wtd12/13293394 OnTechnicalDebt@slideshare.net(OnTechnicalDebt) Estimating the principal of Technical Debt - Dr. Bill Curtis - WTD '12 OnTechnicalDebt 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/estimatingtheprincipaloftechnicaldebt-curtis-wtd12-120612085123-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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.
Estimating the principal of Technical Debt - Dr. Bill Curtis - WTD '12 from OnTechnicalDebt
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