The broken windows theory applies to technical debt
Artikel i vetenskaplig tidskrift, 2024

Context: The term technical debt (TD) describes the aggregation of sub-optimal solutions that serve to impede the evolution and maintenance of a system. Some claim that the broken windows theory (BWT), a concept borrowed from criminology, also applies to software development projects. The theory states that the presence of indications of previous crime (such as a broken window) will increase the likelihood of further criminal activity; TD could be considered the broken windows of software systems. Objective: To empirically investigate the causal relationship between the TD density of a system and the propensity of developers to introduce new TD during the extension of that system. Method: The study used a mixed-methods research strategy consisting of a controlled experiment with an accompanying survey and follow-up interviews. The experiment had a total of 29 developers of varying experience levels completing system extension tasks in already existing systems with high or low TD density. Results: The analysis revealed significant effects of TD level on the subjects’ tendency to re-implement (rather than reuse) functionality, choose non-descriptive variable names, and introduce other code smells identified by the software tool SonarQube, all with at least 95% credible intervals. Coclusions: Three separate significant results along with a validating qualitative result combine to form substantial evidence of the BWT’s existence in software engineering contexts. This study finds that existing TD can have a major impact on developers propensity to introduce new TD of various types during development.

thematic analysis

Bayesian data analysis

Software engineering

broken windows theory

technical debt

controlled experiment

Författare

William Levén

Göteborgs universitet

Hampus Broman

Göteborgs universitet

Terese Besker

RISE Research Institutes of Sweden

Richard Torkar

Chalmers, Data- och informationsteknik

Göteborgs universitet

Empirical Software Engineering

1382-3256 (ISSN) 1573-7616 (eISSN)

Vol. 29 4 73

Ämneskategorier

Programvaruteknik

DOI

10.1007/s10664-024-10456-6

Mer information

Senast uppdaterat

2024-06-19