Technical Debt in Large-Scale Distributed Projects: An Industrial Case Study

Identification and management of technical debt: A systematic mapping study

Technical debt (TD) is a technical compromise wherein the ability to maintain information technology (IT) applications over the long term is sacrificed for short-term goals. TD occurs when software development teams undergo constant pressure to release applications swiftly, on a tight schedule. The accumulation of TD, which often leads to a significant cost surplus, presents a ubiquitous challenge in technology-driven organisations. To keep TD levels under control, many organisations implement top-down mechanisms that impose enterprise-wide principles on software development teams. This clinical research presents a complementary but distinct approach to managing TD. A digital nudge was introduced at Credit Suisse, a global financial services company, to help raise awareness and understanding, and stimulate actions related to TD decision-making in software development teams. This paper reports on the nudge’s clinical design, implementation, impact, and evaluation. As the nudge was effective in reducing TD in IT applications after one year of use, we demonstrate that digital nudges are viable means for guiding collective decisions in complex decision environments like that of TD management. Our findings have several implications for research and practice.

Costs and obstacles encountered in technical debt management – A case study

Background: The COVID-19 outbreak interrupted regular activities for over a year in many countries and resulted in a radical change in ways of working for software development companies, i.e., most software development companies switched to a forced Working-From-Home (WFH) mode. Aim: Although several studies have analysed different aspects of forced WFH mode, it is unknown whether and to what extent WFH impacted the accumulation of technical debt (TD) when developers have different ways to coordinate and communicate with peers. Method: Using the year 2019 as a baseline, we carried out an industrial case study to analyse the evolution of TD in five components that are part of a large project while WFH. As part of the data collection, we carried out a focus group with developers to explain the different patterns observed from the quantitative data analysis. Results: TD accumulated at a slower pace during WFH as compared with the working-from-office period in four components out of five. These differences were found to be statistically significant. Through a focus group, we have identified different factors that might explain the changes in TD accumulation. One of these factors is responsibility diffusion which seems to explain why TD grows faster during the WFH period in one of the components. Conclusion: The results suggest that when the ways of working change, the change between working from office and working from home does not result in an increased accumulation of TD.

Prevalence, common causes and effects of technical debt: Results from a family of surveys with the IT industry

The technical debt metaphor is increasingly being used to describe the effect of delaying certain software maintenance tasks on software projects. Practitioners understand intuitively how technical debt can turn into a serious problem if it is left unattended. However, it remains unknown how serious the problem is and whether explicit measurement and management of technical debt is useful. In this paper, we explore the effect of technical debt by tracking a single delayed maintenance task in a real software project throughout its lifecycle and simulate how explicit technical debt management might have changed project outcomes. The results from this study demonstrate how and to what extent technical debt affects software projects. The study also sheds light on the research methodologies that can be used to investigate the technical debt management problem.

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.

Background. The need to release our products under tough time constraints has required us to take shortcuts during the implementation of our products and to postpone the correct implementation, thereby accumulating Technical Debt. Objective. In this work, we report the experience of a Finnish SME in managing Technical Debt (TD), investigating the most common types of TD they faced in the past, their causes, and their effects. Method. We set up a focus group in the case-company, involving different roles. Results. The results showed that the most significant TD in the company stems from disagreements with the supplier and lack of test automation. Specification and test TD are the most significant types of TD. Budget and time constraints were identified as the most important root causes of TD. Conclusion. TD occurs when time or budget is limited or the amount of work are not understood properly. However, not all postponed activities generated ”debt”. Sometimes the accumulation of TD helped meet deadlines without a major impact, while in other cases the cost for repaying the TD was much higher than the benefits. From this study, we learned that learning, careful estimations, and continuous improvement could be good strategies to mitigate TD These strategies include iterative validation with customers, efficient communication with stakeholders, meta-cognition in estimations, and value orientation in budgeting and scheduling.

Technical debt are those convenience tasks that developers perform to obtain short-term benefits but that in the future can produce activities that are difficult to perform or more costly. The impact of technical debt is perceived in all project resources, becoming a present and future problem in software development, affecting the quality of the software. This study uses a qualitative analysis, through interviews with a software development team, explores the knowledge and perception of technical debt, the practices used to manage it, the factors that influence its appearance and accumulation, the impact that development suffers, as well as the team and the maintainability of the software, as a result, ideas and solutions are proposed to address it effectively. The study was carried out with a qualitative investigative approach, which was based on the study of a single case with which the experiences and practices in the perception and management of technical debt are investigated. The data obtained reveal that technical debt affects the normal development of the development team and that it is present in the activities carried out by the team. Although the development team has a perception of the debt, it does not address it directly, and it is necessary to implement good practices to identify it and integrate it into the software development process. Addressing technical debt with the implementation of a formal process to manage it will ensure that scheduled time is controlled and resources are optimized, which will result in a culture of good practices that will ensure product quality, improving team performance and guaranteeing software maintainability

Cross-disciplinary and cross-life-cycle-phase Technical Debt in automated Production Systems: two industrial case studies and a survey

When the culture and processes of software development companies do not support technical debt management, unintentional technical debt accumulates in the system and becomes excessive. Encouragement, dedicated time, and proper processes can reduce and avoid unintentional debt, and the skill of contextual ambidexterity can be applied by creating an encouraging context that supports technical debt management. However, existing literature discussing which contextual factors are required to achieve this skill is scarce, and practitioners call for approaches to reduce and avoid technical debt. This paper presents a systematic literature review of 48 papers to identify contextual factors for achieving contextual ambidexterity in knowledge-driven contexts. The results reveal seven categories of core and support contextual factors. This paper informs small- and medium-sized software development companies which contextual factors establish an encouraging context, and it theoretically examines the IT managers’ responsibility for technical debt management.

Technical Debt arises from decisions that favour short-term outcomes at the cost of longer-term disadvantages. They may be taken knowingly or based on missing or incomplete awareness of the costs; they are taken in different roles, situations, stages and ways. Whatever technical or business factor motivate such decisions, they always imply a trade-off in time, a 'now vs. later'. How exactly are such decisions made, and how have they been studied? This paper analyzes how decisions on technical debt are studied in software engineering via a systematic literature review. It examines the presently published Software Engineering research on Technical Debt, with a particular focus on decisions involving time. The findings reveal surprising gaps in published work on empirical research in decision making. We observe that research has rarely studied how decisions are made, even in papers that focus on the decision process. Instead, most attention is focused on engineering measures and feeding them into an idealized decision making process. These findings lead to a set of recommendations for future empirical research on Technical Debt.

The impact of Technical Debt (TD) on software maintenance and evolution is of great concern, but recent evidence shows that a considerable amount of TD is fixed by the same developers who introduced it; this is termed self-fixed TD. This characteristic of TD management can potentially impact team dynamics and practices in managing TD. However, the initial evidence is based on low-level source code analysis; this casts some doubt whether practitioners repay their own debt intentionally and under what circumstances. To address this gap, we conducted an online survey on 17 well-known Java and Python open-source software communities to investigate practitioners' intent and rationale for self-fixing technical debt. We also investigate the relationship between human-related factors (e.g., experience) and self-fixing. The results, derived from the responses of 181 participants, show that a majority addresses their own debt consciously and often. Moreover, those with a higher level of involvement (e.g., more experience in the project and number of contributions) tend to be more concerned about self-fixing TD. We also learned that the sense of responsibility is a common self-fixing driver and that decisions to fix TD are not superficial but consider balancing costs and benefits, among other factors. The findings in this paper can lead to improving TD prevention and management strategies.

Technical Debt (TD) is a metaphor to refer to events that bring quality loss in the code. A large volume of Technical Debt in an application may bring losses for the organisation that keeps it. For those organisations that outsource software development, monitoring TD in the influx of development packages may be an efficient strategy to ensure the quality of the product acquired. This works bring an account on the search for a TD management model, to allow a given Brazilian Federal Administration body to inspect how much debt an application has, as acquired in an outsourced way.

Studying the causes of technical debt (TD) could aid in TD prevention, thus easing the job of TD management. On the other hand, better understanding of the effects of TD could also aid in TD management by facilitating more informed decisions about incurring and paying off debt. Create a deeper understanding, and confirming existing evidence, of the causes and effects of TD by collecting new evidence from real-world TD examples. InsighTD is a globally distributed family of industrial surveys on the causes and effects of TD. It is designed to run as a large-scale study based on continuous and independent replications in different countries. The survey instrument asks practitioners to describe in detail a real example of TD from their experience. We present in this paper the design of InsighTD, which has the primary goal of replication at a large-scale, with the results of the study in Brazil as a small part of the larger puzzle. The first iteration of the InsighTD survey, carried out in Brazil, yielded 107 responses. We identified a total of 78 causes and 66 effects, which confirm and also extend the current knowledge on causes and effects of TD. Then, we organized the identified set of causes and effects in probabilistic cause-effect diagrams. The proposed diagrams highlight the causes that can most contribute to the occurrence of TD as well as the most common effects that occur as a result of debt. We intend to reduce the problem of isolated TD investigations that are not yet representative and build a continuous and generalizable empirical basis for understanding practical problems and challenges of TD.