The magnificent seven: Towards a systematic estimation of technical debt interest
Paper in proceeding, 2017

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.

Interest

Estimation

Technical debt

Case study

Tool

Author

Antonio Martini

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Jan Bosch

Chalmers, Computer Science and Engineering (Chalmers)

ACM International Conference Proceeding Series

Vol. Part F129907 a7
978-1-4503-5264-2 (ISBN)

Subject Categories

Software Engineering

DOI

10.1145/3120459.3120467

ISBN

978-1-4503-5264-2

More information

Latest update

7/12/2024