抄録
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.
収録刊行物
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- Empirical Software Engineering
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Empirical Software Engineering 25 2020-09
Springer Nature
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詳細情報 詳細情報について
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- CRID
- 1050295834376560768
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- NII論文ID
- 120006900504
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- ISSN
- 15737616
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- HANDLE
- 10061/14139
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- 本文言語コード
- en
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- 資料種別
- journal article
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- データソース種別
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- IRDB
- CiNii Articles