{"title":"A rule-based decision model to support technical debt decisions: A multiple case study of web and mobile app startups","authors":"Abdullah Aldaeej , Carolyn Seaman","doi":"10.1016/j.infsof.2024.107542","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>Software startups are immature software organizations that focus on the development of a single software product or service. This organizational context accumulates a lot of technical debt to cope with constraints such as limited resources and product-market fit uncertainty. While some research has explored technical debt in startups, there is no study that investigates how software startups should make technical debt decisions throughout the startup evolution stages.</p></div><div><h3>Objective</h3><p>The objective of this study is to understand how technical debt decisions are made, and how such decisions should have been made in hindsight.</p></div><div><h3>Method</h3><p>We conducted a multiple embedded case study to investigate technical debt decisions in five web/mobile app startups. For each case, we interviewed the case founder and developer (a total of 17 participants across cases). In addition, we collected some public documents about the five startups. The data were analyzed using qualitative data analysis techniques.</p></div><div><h3>Results</h3><p>We developed a rule-based decision model that summarizes the logic to effectively make technical debt decisions throughout the startup evolution stages. In addition, we evaluated the model by conducting follow-up interviews with three participants.</p></div><div><h3>Conclusion</h3><p>The study provides a decision model that reflects actual practice, and is designed to help software teams in startups when making technical debt decisions throughout the startup evolution stages.</p></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"175 ","pages":"Article 107542"},"PeriodicalIF":3.8000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information and Software Technology","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0950584924001472","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Context
Software startups are immature software organizations that focus on the development of a single software product or service. This organizational context accumulates a lot of technical debt to cope with constraints such as limited resources and product-market fit uncertainty. While some research has explored technical debt in startups, there is no study that investigates how software startups should make technical debt decisions throughout the startup evolution stages.
Objective
The objective of this study is to understand how technical debt decisions are made, and how such decisions should have been made in hindsight.
Method
We conducted a multiple embedded case study to investigate technical debt decisions in five web/mobile app startups. For each case, we interviewed the case founder and developer (a total of 17 participants across cases). In addition, we collected some public documents about the five startups. The data were analyzed using qualitative data analysis techniques.
Results
We developed a rule-based decision model that summarizes the logic to effectively make technical debt decisions throughout the startup evolution stages. In addition, we evaluated the model by conducting follow-up interviews with three participants.
Conclusion
The study provides a decision model that reflects actual practice, and is designed to help software teams in startups when making technical debt decisions throughout the startup evolution stages.
期刊介绍：
Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal''s scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include:
• Software management, quality and metrics,
• Software processes,
• Software architecture, modelling, specification, design and programming
• Functional and non-functional software requirements
• Software testing and verification & validation
• Empirical studies of all aspects of engineering and managing software development
Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information.
The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.
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