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Issue No.06 - Nov.-Dec. (2012 vol.29)
pp: 34-42
Bill Curtis , CAST Software
Jay Sappidi , CAST Software
Alexandra Szynkarski , CAST Software
This article characterizes technical debt across 700 business applications, comprising 357 MLOC. These applications were analyzed against more than 1,200 rules of good architectural and coding practice. The authors present a formula with adjustable parameters for estimating the principal of technical debt from structural quality data.
Investments, Software measurements, Software quality, Risk management, static analysis, technical debt, software structural quality, software metrics
Bill Curtis, Jay Sappidi, Alexandra Szynkarski, "Estimating the Principal of an Application's Technical Debt", IEEE Software, vol.29, no. 6, pp. 34-42, Nov.-Dec. 2012, doi:10.1109/MS.2012.156
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