MultiDimEr

Silva, Lakmal; Unterkalmsteiner, Michael; Wnuk, Krzysztof

doi:10.1145/3524843.3528099

Cited by 2 publications

(3 citation statements)

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“…Looking at the taxonomy proposed by Codabux et al [19], they define documentation debt as deficits in code documentation, as well as build and end-user documentation. In this paper, we focus on customer-facing documentation as we found that this type of documentation contains the most defects in the system we studied [6], further substantiating that documentation debt is the most frequently encountered type of TD.…”

Section: Related Workmentioning

confidence: 63%

“…The customer-facing documents throughout Ericsson are structured and developed according to the Darwin Information Typing Architecture 6 . DITA is an open standard that specifies a set of document types for authoring, organizing topic-oriented information.…”

Section: A Darwin Information Typing Architecture (Dita)mentioning

confidence: 99%

“…Software defects consume a significant amount of time and money [5] for both the development organizations as well the end users. In an effort to identify Technical Debt (TD), we implemented a bug analysis tool called MultiDimEr, a Multi-Dimensional bug analyzEr [6] that analyzes and categorizes bug reports into different dimensions such as architectural components, source code files, and customerfacing documents. The analysis tool revealed that most of the reported defects resulted in updates to customer-facing software documents such as configuration guides, deployment guides and user guides.…”

Section: Introductionmentioning

confidence: 99%

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Towards identifying and minimizing customer-facing documentation debt

Silva

Unterkalmsteiner

Wnuk

2023

2023 ACM/IEEE International Conference on Technical Debt (TechDebt)

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Background: Software documentation often struggles to catch up with the pace of software evolution. The lack of correct, complete, and up-to-date documentation results in an increasing number of documentation defects which could introduce delays in integrating software systems. In our previous study on a bug analysis tool called MultiDimEr, we provided evidence that documentation-related defects contribute to a significant number of bug reports. Aims: First, we want to identify documentation defect types contributing to documentation defects and thereby identifying documentation debt. Secondly, we aim to find pragmatic solutions to minimize most common documentation defects to pay off the documentation debt in the long run. Method: We investigated documentation defects related to an industrial software system. First, we looked at the types of different documentation and associated bug reports. We categorized the defects according to an existing documentation defect taxonomy. Results: Based on a sample of 101 defects, we found that a majority of defects are caused by documentation defects falling into the Information Content (What) category (86). Within this category, the documentation defect types Erroneous code examples (23), Missing documentation (35), and Outdated content (19) contributed to most of the documentation defects. We propose to adapt two solutions to mitigate these types of documentation defects. Conclusions: In practice, documentation debt can easily go undetected since a large share of resources and focus is dedicated to deliver high-quality software. This study provides evidence that documentation debt can contribute to increase in maintenance costs due to the number of documentation defects. We suggest to adapt two main solutions to tackle documentation debt by implementing (i) Dynamic Documentation Generation (DDG) and/or (ii) Automated Documentation Testing (ADT), which are both based on defining a single and robust information source for documentation.

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Section: Related Workmentioning

confidence: 63%

Section: A Darwin Information Typing Architecture (Dita)mentioning

confidence: 99%