Publication Type

Journal Article

Version

acceptedVersion

Publication Date

9-2020

Abstract

Self-admitted technical debt refers to situations where a software developer knows that their current implementation is not optimal and indicates this using a source code comment. In this work, we hypothesize that it is possible to develop automated techniques to understand a subset of these comments in more detail, and to propose tool support that can help developers manage self-admitted technical debt more effectively. Based on a qualitative study of 333 comments indicating self-admitted technical debt, we first identify one particular class of debt amenable to automated management: on-hold self-admitted technical debt (on-hold SATD), i.e., debt which contains a condition to indicate that a developer is waiting for a certain event or an updated functionality having been implemented elsewhere. We then design and evaluate an automated classifier which can identify these on-hold instances with an area under the receiver operating characteristic curve (AUC) of 0.98 as well as detect the specific conditions that developers are waiting for. Our work presents a first step towards automated tool support that is able to indicate when certain instances of self-admitted technical debt are ready to be addressed.

Keywords

Self-admitted technical debt, Qualitative study, Classification

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Empirical Software Engineering

Volume

25

Issue

5

First Page

3770

Last Page

3798

ISSN

1382-3256

Identifier

10.1007/s10664-020-09854-3

Publisher

Springer

Additional URL

https://doi.org/10.1007/s10664-020-09854-3

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