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The magnificent seven: Towards a systematic estimation of technical debt interest

Antonio Martini (Institutionen för data- och informationsteknik, Software Engineering (Chalmers)) ; Jan Bosch (Institutionen för data- och informationsteknik (Chalmers))
ACM International Conference Proceeding Series - 2017 XP Scientific Workshops, XP 2017, Cologne, Germany, 22-26 May 2017 (2017)
[Konferensbidrag, refereegranskat]

The interest of Technical Debt is difcult to assess. The negative efects (severity) of Technical Debt might depend on the context of the organization and the estimations might be subjective. There is a need for assessing Technical Debt interest in a more systematic way. Based on the results of previous research, we have developed and used a lightweight tool, AnaConDebt, to assess the severity of the interest of 9 Technical Debt items with the stakeholders in 3 Agile teams. The systematic and semi-automatic assessment of seven factors and their growth has been compared to the stakeholders' intuitive estimations. The results show that the outcome of the tool is very close to the estimation given by the stakeholders. The implications are that, if further data support the hypothesis, the severity of the interest can be systematically assessed by the stakeholders by estimating only seven factors in a cost-efective manner with acceptable results.

Nyckelord: Case study , Estimation , Interest , Technical debt , Tool



Denna post skapades 2017-10-11. Senast ändrad 2017-10-25.
CPL Pubid: 252439

 

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