Technical Debt Management Research Articles

Refining the Scrum Paradigm: A Comprehensive Study of Software Development Practices (2020-2023)

This article presents a complex vision on software production practices aimed at enhancing the Scrum methodology within software project management. The recommended best practices are closely aligned with contemporary trends in the IT sector, including the total digitalization and virtualization of production processes, the transition to fully remote software development models, the incorporation of artificial intelligence technologies, and the implementation of cost-effective models in team organization. The modifications to software production processes discussed herein are grounded in research conducted between 2020 and 2023, encompassing insights from leading Russian, European, and global IT companies. This research underscores a significant transformation in IT business practices, reflecting a shift towards new benchmarks for Scrum team efficiency. These benchmarks emphasize the data-driven formalization of production models, automation facilitated by AI tools, and noticeable cost optimization within engineering teams, which collectively align with the evolving demands of the modern IT landscape. The article details a series of management strategies designed to adapt to these shifts, including the formalization of sprint goals and processes within Scrum, management of technical debt, and the cost-efficient organization of development teams.

Reducing Technical Debt through Strategic Leadership in Retail Technology Systems

In the fast-paced and highly competitive landscape of retail, the management of technical debt has become a critical challenge for organizations striving to maintain robust and scalable technology systems. Technical debt, the accumulated cost of prioritizing quick fixes or suboptimal solutions over more sustainable and efficient options, can significantly hinder an organization's ability to innovate, adapt, and grow. This paper explores the role of strategic leadership in effectively reducing technical debt within retail technology systems. By examining key leadership strategies, such as fostering a culture of continuous improvement, investing in long-term technology planning, and emphasizing cross-functional collaboration, the paper highlights how retail organizations can systematically address and mitigate technical debt. Strategic leadership in the retail sector involves a comprehensive understanding of both business and technological imperatives. Leaders must recognize the implications of technical debt not only in terms of immediate financial costs but also in the broader context of business agility, customer experience, and competitive advantage. The paper emphasizes the need for leaders to adopt a proactive approach, prioritizing technical debt reduction as a strategic objective that aligns with the organization's overall goals. One of the central arguments of the paper is that effective technical debt management requires a shift from reactive to proactive leadership. This involves anticipating potential issues, encouraging innovation, and making informed decisions that balance short-term gains with long-term sustainability. The paper discusses various leadership practices that contribute to this shift, including the implementation of robust governance frameworks, the adoption of agile methodologies, and the promotion of a learning-oriented organizational culture.

Reducing Technical Debt through Strategic Leadership in Retail Technology Systems

In the fast-paced and highly competitive landscape of retail, the management of technical debt has become a critical challenge for organizations striving to maintain robust and scalable technology systems. Technical debt, the accumulated cost of prioritizing quick fixes or suboptimal solutions over more sustainable and efficient options, can significantly hinder an organization's ability to innovate, adapt, and grow. This paper explores the role of strategic leadership in effectively reducing technical debt within retail technology systems. By examining key leadership strategies, such as fostering a culture of continuous improvement, investing in long-term technology planning, and emphasizing cross-functional collaboration, the paper highlights how retail organizations can systematically address and mitigate technical debt.Strategic leadership in the retail sector involves a comprehensive understanding of both business and technological imperatives. Leaders must recognize the implications of technical debt not only in terms of immediate financial costs but also in the broader context of business agility, customer experience, and competitive advantage. The paper emphasizes the need for leaders to adopt a proactive approach, prioritizing technical debt reduction as a strategic objective that aligns with the organization's overall goals.One of the central arguments of the paper is that effective technical debt management requires a shift from reactive to proactive leadership.

Technical Debt Monitoring Decision Making with Skin in the Game

Technical Debt Management (TDM) can suffer from unpredictability, communication gaps and the inaccessibility of relevant information, which hamper the effectiveness of its decision making. These issues can stem from division among decision-makers which takes root in unfair consequences of decisions among different decision-makers. One mitigation route is Skin in the Game thinking, which enforces transparency, fairness and shared responsibility during collective decision-making under uncertainty. This article illustrates characteristics which require Skin in the Game thinking in Technical Debt (TD) identification, measurement, prioritisation and monitoring. We point out crucial problems in TD monitoring rooted in asymmetric information and asymmetric payoff between different factions of decision-makers. A systematic TD monitoring method is presented to mitigate the said problems. The method leverages Replicator Dynamics and Behavioural Learning. The method supports decision-makers with automated TD monitoring decisions; it informs decision-makers when human interventions are required. Two publicly available industrial projects with a non-trivial number of TD and timestamps are utilised to evaluate the application of our method. Mann–Whitney U hypothesis tests are conducted on samples of decisions from our method and the baseline. The statistical evidence indicates that our method can produce cost-effective and contextual TD monitoring decisions.

Advancing Technical Debt Management in Software Systems with a Comprehensive TD Indicator and Question Catalog

The Technical Debt (TD) metaphor was introduced over three decades ago and continues to challenge software development projects. Despite its recognized importance, there is a lack of comprehensive catalog that not only lists TD types and indicators but also elucidates them. This paper significantly extends our previous work by presenting a detailed catalog of TD types and indicators, enriched with specific assessment questions and in-depth explanations for each indicator. We had extracted and refined TD categories from both academic and gray literature to assemble a list of 120 TD indicators across 10 distinct TD types. For each indicator, we provide detailed description and at least two tailored assessment questions in this version, to aid in the practical evaluation of technical debt. This enhanced catalog is designed to advance the specification and management of technical debt in software development, offering practitioners clear, actionable insights for assessing and addressing TD.

Enabling affordances for AI Governance

Organizations dealing with mission-critical AI based autonomous systems may need to provide continuous risk management controls and establish means for their governance. To achieve this, organizations are required to embed trustworthiness and transparency in these systems, with human overseeing and accountability. Autonomous systems gain trustworthiness, transparency, quality, and maintainability through the assurance of outcomes, explanations of behavior, and interpretations of intent. However, technical, commercial, and market challenges during the software development lifecycle (SDLC) of autonomous systems can lead to compromises in their quality, maintainability, interpretability and explainability. This paper conceptually models transformation of SDLC to enable affordances for assurance, explanations, interpretations, and overall governance in autonomous systems. We argue that opportunities for transformation of SDLC are available through concerted interventions such as technical debt management, shift-left approach and non-ephemeral artifacts. This paper contributes to the theory and practice of governance of autonomous systems, and in building trustworthiness incrementally and hierarchically.

Lean and Agile Software Development for Managing Technical Debt on A Large-scale Software: A Systematic Literature Review

Agile methodologies are employed by software development teams for collaboration and adapting to changing requirements. However, this flexibility may lead to technical debt (TD), causing potential bugs in the long term. Lean principles, focusing on waste elimination and continuous process improvement, can be applied to manage TD in agile software development. This research conducts a systematic literature review on using lean and agile methodologies for TD management. The review identifies 34 papers, categorizing TD types, pinpointing lean and agile principles, and aligning technical debt categories with suitable lean and agile principles. Additionally, three existing technical debt management frameworks are identified: the TAP framework, the LTD framework, and the CoDVA framework. The study concludes that integrating lean principles into agile software development assists organizations in effectively managing technical debt. Furthermore, the research offers insights into selecting the most suitable TD management framework based on an organization's needs and available resources.

Software design analysis and technical debt management based on design rule theory

Software design analysis and technical debt management based on design rule theory

Business-driven technical debt management using Continuous Debt Valuation Approach (CoDVA)

Business-driven technical debt management using Continuous Debt Valuation Approach (CoDVA)

Software Industry Perception of Technical Debt and Its Management

Technical debt (TD) expresses the lack of internal quality directly affecting software evolution. Therefore, it has gained the attention of software researchers and practitioners recently. Software researchers have performed empirical studies to observe the perspective of TD in different software cultures and organizations. However, it is important to replicate such studies in more places and with more practitioners to strengthen the perception of TD. In this paper, we present the results of a set of new research questions from an evolved survey design of a survey replication in the Uruguayan software industry to characterize how the software industry professionals understand, perceive, and adopt TD management (TDM) activities. The results allow us to observe that different participant contexts (startups, government, job roles) show different levels of awareness and perception of TD. Details in the form of the adoption of each TDM activity were presented. We could observe some difficulties in conducting some TDM activities that the practitioners consider very important, especially in TDM and monitoring. Differences in specific organizational contexts like startups and government could indicate the need for research efforts in other software engineering communities that meet their specific TD challenges and needs.

Investigating the Point of View of Project Management Practitioners on Technical Debt - A Study on Stack Exchange

Context: Technical debt (TD) can bring short-term benefits to software projects, but its presence is associated with issues such as decreasing product quality. Recent literature has proposed various approaches for identifying and managing TD, but most of them focus on the software developers’ point of view. Little is known about how project management practitioners perceive and manage TD items. Goal: This work aims to investigate how project management practitioners discuss and experience TD. Method: To achieve this goal, our work mines, curates, and selects a total of 108 TD-related discussions on the Stack Exchange Project Management (SEPM) Q&A site. These discussions amount to 547 posts and 882 text comments on the subject. We analyze this data set quantitatively and qualitatively, using open coding to derive TD types, indicators, and management practices. Results: We identified 74 indicators used for recognizing debt items and 126 TD management practices. The types of debt most discussed at SEPM are process and people debts. This contradicts studies done with developers where code and design debts are most discussed. Conclusion: The perspective considered by project management practitioners to analyze the TD phenomenon is different from the one considered by other roles in the software development process. Our work organizes the identified TD indicators and management practices into a Sankey diagram, which may assist TD management practitioners and serve as guidance for future research on the subject.

A Proposed Technical Debt Management Approach Applied on Software Projects in Egypt

Technical Debt (TD) is a metaphor that can be described as the technical issues that are hidden from end users and customers, but in fact hinder the development efforts during system evolution and future enhancements. Due to tight budgets and timelines, TD is frequently incurred, which may lead to technical, financial, and quality issues that make future maintenance more costly or impossible. While business professionals concentrate on external issues related to customer satisfaction, in fact they rarely pay attention to internal software quality defects and maintenance, which would rather cause future interest payments. In this research study, we propose a TD management (TDM) approach with best practices developed using Design Science Research (DSR) and conducted with multiple case studies for the software development team in Small and Medium Enterprises (SMEs). The study demonstrates that the proposed approach for measuring the impact of internal / external software quality leads to increased awareness of TD’s occurrence and thereby provides processes for preventing, identifying, prioritizing, monitoring, and repaying TD to satisfy both customer value and technical requirements, along with halting project failures and cost overruns. In actuality, applying our proposed TDM approach leads to a deeper comprehension of TD contraction in selected software companies, improved team morale and motivation, as well as an enhancement in its maintainability.

Identification and Management of Technical Debt

Technical debt is a concept used to describe the lack of good practices during software development, leading to several problems and costs. Identification and management strategies can help reduce these difficulties. In a previous study, Alves et al. (2016) analyzed the research landscape of such strategies from 2010 to 2014. This paper replicates and updates their study to explore the evolution of technical debt identification and management research landscape over a decade, including literature from 2010 until 2022. We analyzed 117 papers from the ACM Digital Library, IEEE Xplore, Science Direct, and Springer Link. Newly suggested strategies include automatically identifying admitted debt in comments, commits, and source code. Between 2015 and 2022, more empirical evaluations have been performed, and the general research focus has changed to a more holistic approach. Therefore, the research area evolved and reached a new level of maturity compared to previous results from Alves et al. (2016). Not only are code aspects considered for technical debt, but other aspects have also been investigated (e.g., models for the development process).

An Architectural Technical Debt Index Based on Machine Learning and Architectural Smells

A key aspect of technical debt (TD) management is the ability to measure the amount of principal accumulated in a system. The current literature contains an array of approaches to estimate TD principal, however, only a few of them focus specifically on architectural TD, but none of them satisfies all three of the following criteria: being fully automated, freely available, and thoroughly validated. Moreover, a recent study has shown that many of the current approaches suffer from certain shortcomings, such as relying on hand-picked thresholds. In this paper, we propose a novel approach to estimate architectural technical debt principal based on machine learning and architectural smells to address such shortcomings. Our approach can estimate the amount of technical debt principal generated by a single architectural smell instance. To do so, we adopt novel techniques from Information Retrieval to train a learning-to-rank machine learning model (more specifically, a gradient boosting machine) that estimates the severity of an architectural smell and ensure the transparency of the predictions. Then, for each instance, we statically analyse the source code to calculate the exact number of lines of code creating the smell. Finally, we combine these two values to calculate the technical debt principal. To validate the approach, we conducted a case study and interviewed 16 practitioners, from both open source and industry, and asked them about their opinions on the TD principal estimations for several smells detected in their projects. The results show that for 71% of instances, practitioners agreed that the estimations provided were <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">representative</i> of the effort necessary to refactor the smell.

An Empirical Survey on the Prevalence of Technical Debt in Systems Engineering

AbstractThe technical debt metaphor is used within software engineering to describe technical concessions that produce a short‐term benefit but result in long‐term consequences. Systems engineering is subject to these concessions, yet there is a limited amount of research associating technical debt with systems engineering. This paper provides the results of an empirical survey investigating the prevalence of technical debt in systems engineering, including the occurrence of technical debt, the use of the metaphor, and the distribution of technical debt within the systems engineering lifecycle. The results of the survey show that while technical debt is common in systems engineering and occurs throughout the lifecycle, the metaphor and terminology of technical debt is not consistently applied. These results emphasize the need to enrich the usage of the technical debt metaphor within systems engineering to enable the management of technical debt and to reduce the risk of technical bankruptcy.

Investigation on Self-Admitted Technical Debt in Open-Source Blockchain Projects

Technical debt refers to decisions made during the design and development of software that postpone the resolution of technical problems or the enhancement of the software’s features to a later date. If not properly managed, technical debt can put long-term software quality and maintainability at risk. Self-admitted technical debt is defined as the addition of specific comments to source code as a result of conscious and deliberate decisions to accumulate technical debt. In this paper, we will look at the presence of self-admitted technical debt in open-source blockchain projects, which are characterized by the use of a relatively novel technology and the need to generate trust. The self-admitted technical debt was analyzed using NLP techniques for the classification of comments extracted from the source code of ten projects chosen based on capitalization and popularity. The analysis of self-admitted technical debt in blockchain projects was compared with the results of previous non-blockchain open-source project analyses. The findings show that self-admitted design technical debt outnumbers requirement technical debt in blockchain projects. The analysis discovered that some projects had a low percentage of self-admitted technical debt in the comments but a high percentage of source code files with debt. In addition, self-admitted technical debt is on average more prevalent in blockchain projects and more equally distributed than in reference Java projects.If not managed, the relatively high presence of detected technical debt in blockchain projects could represent a threat to the needed trust between the blockchain system and the users. Blockchain projects development teams could benefit from self-admitted technical debt detection for targeted technical debt management.

Characteristics, causes, and consequences of technical debt in the automation domain

Technical Debt (TD) is a significant concern in software development, particularly when interdisciplinary teams collaborate and interact. The goal of the study is to investigate TD causal chains and patterns in the industrial automation sector by analyzing 123 mechatronic TD incidents from 47 expert interviews across ten companies. Findings reveal that Requirements, Process, and Test TD are most common, while Build, Versioning, Manufacturing, Code, and Maintenance/Service TD are less frequent. Key causes include ”other priorities”, ”lack of time”, ”historically grown products”, ”lack of market analysis” and ”copy-paste-modify without revising tolerances.” The research identifies correlations between TD subtypes and causes/consequences in relation to company size, experts’ experience, and position, utilizing the Chi-square test and PrefixSpan algorithm. The study also maps the contagious character of TD using Neo4J graphical representation. This first in-depth analysis of TD causal chains in industrial automation contributes qualitatively to understanding TD patterns, helping researchers and practitioners assess TD contagiousness, comprehend its effects, prevent diffusion, and develop repayment strategies To the best of our knowledge, this study’s quantitative analysis approach provides the foundation that will enable future research identifying TD metrics and TD management in multidisciplinary engineering.

TD Pulse: Assessing the Systematic Management of Technical Debt

Technical Debt requires the management of several technical and non-technical aspects: process, organization, tools, etc. Software companies must identify where TD is not well managed and where to improve. Based on ten years of research and practice, we have created an effective approach, TD Pulse, to assess Technical Debt Management in large software companies and find critical improvement areas. The approach was used by 232 and evaluated by more than 200 practitioners in three large companies, including Siemens and Zenseact. The results show that our approach is valuable and lightweight. We also share lessons learned from the whole assessment experience.

IT managers’ perspective on Technical Debt Management

Context:Technical Debt (TD) is a term for software solutions that are beneficial in the short-term but impede future change. Goal:Previous research on TD indicates various management-related causes. We analyze the perspective of IT managers on TD since they usually have a major influence on deadlines, the project’s budget, and setting up a TD management (TDM) process. Method:To determine the IT managers’ perspective, we obtained and analyzed data from 16 semi-structured interviews and a three-person focus group discussion. Results:We found that all IT managers understood the TD concept. They consider TDM to be an essential topic, though nearly none of them had set up a TDM process so far. We identified three major concerns the IT managers had regarding TDM: communicating about TD, establishing a TDM process, and dealing with vintage systems, i.e., old legacy systems We developed a model specifying causes and consequences visible to business stakeholders, causal chains, and vicious cycles. Conclusions:Our research identifies new research gaps and demonstrates to practitioners that investing in a TDM process may be beneficial. It provides the V4CTD model of Visibility, Cycles & Chains of Causes & Consequences of TD, extending the TD conceptual model and facilitating communication on TD with business stakeholders.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

Technical debt in systems engineering—A systematic literature review

AbstractThe metaphor of “technical debt” is used in software engineering to describe technical solutions that may be pragmatic in the near‐term but may have a negative long‐term impact. Similar decisions and similar dynamics are present in the field of systems engineering. This work investigates the current body of knowledge to identify if, and how, the technical debt metaphor is used within the systems engineering field and which systems engineering lifecycle stages are most susceptible to technical debt. A systematic literature review was conducted on 354 papers in February 2022, of which 18 were deemed relevant for inclusion in the study. The results of the systematic literature review show that the technical debt metaphor is not prevalent within systems engineering research and that existing research is limited to specific fields and theoretical discussions. This paper concludes with recommendations for future work to establish a research agenda on the identification and management of technical debt within systems engineering.