ABSTRACT Process debt, like technical debt, can be a source of short‐term benefits but often leads to harmful consequences in the long term for a software organization. Despite its impact, the phenomenon of process debt has not been thoroughly explored in current literature, leaving a gap in understanding how it affects and is managed within organizations. This paper addresses this gap by defining process debt, describing its occurrence, the risks of its mismanagement, and showing examples of mitigation strategies. Our study began with an exploratory phase involving semi‐structured interviews with sixteen practitioners across four international organizations, allowing us to gather diverse insights into the occurrence and management of process debt. Then, to deepen our understanding and validate our findings, we conducted a cross‐company focus group with ten additional practitioners and analyzed fifty‐eight observations and thirty‐five interviews from a longitudinal case study. The analysis of the research findings led to a definition of process debt and a novel framework. We also report on the causes, consequences, and occurrence patterns of process debt over time. We present mitigation strategies and discuss which ones need further attention for future research. Our results suggest that the debt metaphor may help companies understand how to manage and improve their processes and make process‐related decisions that are beneficial both in the short and long term.

Abstract Context: The term technical debt (TD) describes the aggregation of sub-optimal solutions that serve to impede the evolution and maintenance of a system. Some claim that the broken windows theory (BWT), a concept borrowed from criminology, also applies to software development projects. The theory states that the presence of indications of previous crime (such as a broken window) will increase the likelihood of further criminal activity; TD could be considered the broken windows of software systems. Objective: To empirically investigate the causal relationship between the TD density of a system and the propensity of developers to introduce new TD during the extension of that system. Method: The study used a mixed-methods research strategy consisting of a controlled experiment with an accompanying survey and follow-up interviews. The experiment had a total of 29 developers of varying experience levels completing system extension tasks in already existing systems with high or low TD density. Results: The analysis revealed significant effects of TD level on the subjects’ tendency to re-implement (rather than reuse) functionality, choose non-descriptive variable names, and introduce other code smells identified by the software tool , all with at least $$95\%$$ 95 % credible intervals. Coclusions: Three separate significant results along with a validating qualitative result combine to form substantial evidence of the BWT’s existence in software engineering contexts. This study finds that existing TD can have a major impact on developers propensity to introduce new TD of various types during development.

When developing software, it is vitally important to keep the level of technical debt down since, based on several studies, it has been well established that technical debt can lower the development productivity, decrease the developers' morale and compromise the overall quality of the software, among others. However, even if researchers and practitioners working in today's software development industry are quite familiar with the concept of technical debt and its related negative consequences, there has been no empirical research focusing specifically on how software managers actively communicate and manage the need to keep the level of technical debt as low as possible. This study aims to understand how software companies give incentives to manage technical debt. This is carried out by exploring how companies encourage and reward practitioners for actively keeping the level of technical debt down add whether the companies use any forcing or penalising initiatives when managing technical debt. As a first step, this paper reports the results of both an online survey providing quantitative data from 258 participants and interviews with 32 software practitioners. As a second step, this study sets out to specifically provide a detailed assessment of additional and in-depth analysis of technical debt management strategies based on an encouraging mindset and attitude from both managers and technical roles to understand how, when and by whom such strategies are adopted in practice. Our findings show that having a technical debt management strategy (specially based on encouragement) can significantly impact the amount of technical debt related to the software. The result indicates that there is considerable unfulfilled potential to influence how software practitioners can further limit and reduce technical debt by adopting a strategy based explicitly on an encouraging mindset from managers where they also specifically dedicate time and resources for technical debt remediation activities.

Abstract Context Software engineering is a human activity. Despite this, human aspects are under-represented in technical debt research, perhaps because they are challenging to evaluate. Objective This study’s objective was to investigate the relationship between technical debt and affective states (feelings, emotions, and moods) from software practitioners. Method Forty participants ( N = 40) from twelve companies took part in a mixed-methods approach, consisting of a repeated-measures ( r = 5) experiment ( n = 200), a survey, and semi-structured interviews. From the qualitative data, it is clear that technical debt activates a substantial portion of the emotional spectrum and is psychologically taxing. Further, the practitioners’ reactions to technical debt appear to fall in different levels of maturity. Results The statistical analysis shows that different design smells (strong indicators of technical debt) negatively or positively impact affective states. Conclusions We argue that human aspects in technical debt are important factors to consider, as they may result in, e.g., procrastination, apprehension, and burnout.

Software companies need to manage and refactor Technical Debt issues. Therefore, it is necessary to understand if and when refactoring of Technical Debt should be prioritized with respect to developing features or fixing bugs. The goal of this study is to investigate the existing body of knowledge in software engineering to understand what Technical Debt prioritization approaches have been proposed in research and industry. We conducted a Systematic Literature Review of 557 unique papers published until 2020, following a consolidated methodology applied in software engineering. We included 44 primary studies. Different approaches have been proposed for Technical Debt prioritization, all having different goals and proposing optimization regarding different criteria. The proposed measures capture only a small part of the plethora of factors used to prioritize Technical Debt qualitatively in practice. We present an impact map of such factors. However, there is a lack of empirical and validated set of tools. We observed that Technical Debt prioritization research is preliminary and there is no consensus on what the important factors are and how to measure them. Consequently, we cannot consider current research conclusive. In this paper, we therefore outline different directions for necessary future investigations.

Process Debt, like Technical Debt, can be the source of short-term benefits but often is harmful in the long term for a software organization. Nonetheless, information about Process Debt is scarce in current literature. We conducted an exploratory study of Process Debt in four international organizations by interviewing 16 practitioners. The findings show that Process Debt can be a harmful phenomenon that needs attention and new practices, as it is different from Technical Debt. We provide an initial framework, composed by a definition and a conceptual model for Process Debt, showing types, causes, consequences, and debt accumulation patterns.

When developing software, it is vitally important to keep the level of technical debt down since it is well established from several studies that technical debt can, e.g., lower the development productivity, decrease the developers' morale, and compromise the overall quality of the software. However, even if researchers and practitioners working in today's software development industry are quite familiar with the concept of technical debt and its related negative consequences, there has been no empirical research focusing specifically on how software managers actively communicate and manage the need to keep the level of technical debt as low as possible.

In recent years in the software industry, the use of safety-critical software is increasing at a rapid rate. However, little is known about the relationship between safety-critical regulations and the management of technical debt. The research is based on interviews with 19 practitioners working in different safety-critical domains implementing software according to different safety regulation standards. The results are three-fold. First, the result shows that performing technical debt refactoring tasks in safety-critical software requires several additional activities and costs, compared to non-safety-critical software. This study has also identified several negative effects due to the impact of these regulatory requirements. Second, the results show that the safety-critical regulations strengthen the implementation of both source code and architecture and thereby initially limit the introduction of technical debt. However, at the same time, the regulations also force the software companies to perform later suboptimal work-around solutions that are counterproductive in achieving a high-quality software since the regulations constrain the possibility of performing optimal TD refactoring activities. Third, the result shows that technical debt refactoring decisions are heavily weighed on the costs associated with the application's recertification process and that these decisions seldom include the benefits of the refactoring activities in a structured way.

Remediation of technical debt through regular refactoring initiatives is considered vital for the software system's long and healthy life. However, since today's software companies face increasing pressure to deliver customer value continuously, the balance between spending developer time, effort, and resources on implementing new features or spending it on refactoring of technical debt becomes vital. The goal of this study is to explore how the prioritization of technical debt is carried out by practitioners within today's software industry. This study also investigates what factors influence the prioritization process and its related challenges. This paper reports the results of surveying 17 software practitioners, together with follow-up interviews with them. Our results show that there is no uniform way of prioritizing technical debt and that it is commonly done reactively without applying any explicit strategies. Often, technical debt issues are managed and prioritized in a shadow backlog, separate from the official sprint backlog. This study was also able to identify several different challenges related to prioritizing technical debt, such as the lack of quantitative information about the technical debt items and that the refactoring of technical debt issues competes with the implementation of customer requirements.

Software companies need to continuously deliver customer value, both from a short- and long-term perspective. However, software development can be impeded by what has been described as Technical Debt (TD). The aim of this study is to explore the negative consequences of TD in terms of wasted software development time. This study also investigates on which additional activities this wasted time is spent and whether different types of TD impact the wasted time differently. This study also sets out to examine the benefits of tracking and communicating the amount of wasted time, both from a developer's and manager's perspective. This paper reports the results of a longitudinal study, surveying 43 software developers, together with follow-up interviews with 16 industrial software practitioners. The analysis of the reported wasted time revealed that developers waste, on average, 23% of their development time due to TD and that they are frequently forced to introduce new TD due to already existing TD. The most common activity on which additional time is spent is performing additional testing.

Software startups are typically under extreme pressure to get to market quickly with limited resources and high uncertainty. This pressure and uncertainty is likely to cause startups to accumulate technical debt as they make decisions that are more focused on the short-term than the long-term health of the codebase. However, most research on technical debt has been focused on more mature software teams, who may have less pressure and, therefore, reason about technical debt very differently than software startups. In this study, we seek to understand the organizational factors that lead to and the benefits and challenges associated with the intentional accumulation of technical debt in software startups. We interviewed 16 professionals involved in seven different software startups. We find that the startup phase, the experience of the developers, software knowledge of the founders, and level of employee growth are some of the organizational factors that influence the intentional accumulation of technical debt. In addition, we find the software startups are typically driven to achieve a "good enough level," and this guides the amount of technical debt that they intentionally accumulate to balance the benefits of speed to market and reduced resources with the challenges of later addressing technical debt.

Large software companies need to support continuous and fast delivery of customer value both in the short and long term. However, this can be hindered if both the evolution and maintenance of existing systems are hampered by Technical Debt. Although a lot of theoretical work on Technical Debt has been produced recently, its practical management lacks empirical studies. In this paper, we investigate the state of practice in several companies to understand what the cost of managing TD is, what tools are used to track TD, and how a tracking process is introduced in practice. We combined two phases: a survey involving 226 respondents from 15 organizations and an in-depth multiple case study in three organizations including 13 interviews and 79 Technical Debt issues. We selected the organizations where Technical Debt was better tracked in order to distill best practices. We found that the development time dedicated to managing Technical Debt is substantial (an average of 25% of the overall development), but mostly not systematic: only a few participants (26%) use a tool, and only 7.2% methodically track Technical Debt. We found that the most used and effective tools are currently backlogs and static analyzers. By studying the approaches in the companies participating in the case study, we report how companies start tracking Technical Debt and what the initial benefits and challenges are. Finally, we propose a Strategic Adoption Model for the introduction of tracking Technical Debt in software organizations.

Background: In the last two decades Technical Debt (TD) has received a considerable amount of attention from software engineering research and practice. Recently, a small group of studies suggests that, in addition to its technical and economic consequences, TD can affect developers' psychological states and morale. However, until now there has been a lack of empirical research clarifying such influences. Aims: In this study, we aim at taking the first step in filling this gap by investigating the potential impacts of TD and its management on developers' morale. Method: Drawing from previous literature on morale, we decided to explore the influence of TD and its management on three dimensions of morale called affective, future/goal, and interpersonal antecedents. In so doing, we conducted an exploratory field study and collected data from software professionals active in different industrial domains through eight qualitative interviews and an online survey (n=33). Results: Our results indicate that TD mainly has a negative influence on future/goal and affective antecedents of morale. This is mainly because the occurrence of TD hinders developers from performing their tasks and achieving their goals. TD management, on the other hand, has a positive influence on all the three dimensions of morale since it is associated with positive feelings and interpersonal feedback as well as a sense of progress. Conclusions: According to the results of this empirical study, the occurrence of TD reduces developers' morale, while its management increases developers' morale.

The negative consequences of Technical Debt is an area of increasing interest, and more specifically the Architectural aspects of it have received increased attention in the last few years. Besides the negative effects of Architectural Technical Debt on the overall software product quality in terms of hindering evolution and causing high maintenance costs, Architectural Technical Debt also has a significant negative impact on software practitioners' daily work. Although a great deal of theoretical work on Architectural Technical Debt has been undertaken, there is a lack of empirical studies that examine the negative effects of Architectural Technical Debt during the software development lifecycle. The aim of this study is to investigate how practitioners perceive and estimate the impact of Architectural Technical Debt during the software development process. This paper reports the results of an online web survey providing quantitative data from 258 participants. The contribution of this paper is threefold: First, it shows that practitioners experience that the Architectural type of Technical Debt has the highest negative impact on daily software development work. Secondly, we provide evidence that does not support the commonly held belief that Architectural Technical Debt increases with the age of the software. Thirdly, we show that despite different responsibilities and working tasks of software professionals, Architectural Technical Debt negatively affects all roles without any significant difference between the roles.

Software companies need to support continuous and fast delivery of customer value both in short and a long-term perspective. However, this can be hindered by evolution limitations and high maintenance efforts due to internal software quality issues by what is described as Technical Debt. Although significant theoretical work has been undertaken to describe the negative effects of Technical Debt, these studies tend to have a weak empirical basis and often lack quantitative data. The aim of this study is to estimate wasted time, caused by the Technical Debt interest during the software life-cycle. This study also investigates how practitioners perceive and estimate the impact of the negative consequences due to Technical Debt during the software development process. This paper reports the results of both an online web-survey provided quantitative data from 258 participants and follow-up interviews with 32 industrial software practitioners. The importance and originality of this study contributes and provides novel insights into the research on Technical Debt by quantifying the perceived interest and the negative effects it has on the software development life-cycle. The findings show that on average, 36% of all development time is estimated to be wasted due to Technical Debt; Complex Architectural Design and Requirement Technical Debt generates most negative effect; and that most time is wasted on understanding and/or measuring the Technical Debt. Moreover, the analysis of the professional roles and the age of the software system in the survey revealed that different roles are affected differently and that the consequences of Technical Debt are also influenced by the age of the software system.

Large software companies need to support continuous and fast delivery of customer value both in the short and long term. However, this can be hindered if both evolution and maintenance of existing systems are hampered by Technical Debt. Although a lot of theoretical work on Technical Debt has been recently produced, its practical management lacks empirical studies. In this paper we investigate the state of practice in several companies in order to understand how they start tracking Technical Debt. We combined different methodologies: we conducted a survey, involving 226 respondents from 15 organizations and a more in-depth multiple case-study in three organizations, where Technical Debt was tracked: we involved 13 interviews and 79 Technical Debt issues analysis. We found that the development time dedicated to manage Technical Debt is substantial (around 25% of the overall development) but not systematic: only a few participants methodically track Technical Debt. By studying the approaches in the companies participating in the case-study, we understood how companies start tracking Technical Debt and what are the initial benefits and challenges. Finally, we propose a Strategic Adoption Model based to define and adopt a dedicated process for tracking Technical Debt.

Fast software deliveries are hindered by high maintenance efforts due to internal quality issues and Technical Debt (TD) and specifically, Architectural Technical Debt (ATD) has received increased attention in the last few years. ATD has a significant influence and impact on system success and, left unchecked, it can cause expensive repercussions, it is, therefore, of maintenance and evolutionary importance to understand the basic underlying factors of ATD. Thus, with this as background, there is a need for a descriptive model to illustrate and explain the different ATD issues. The aim of this study is to synthesize and compile research efforts with the goal of creating new knowledge with a specific interest in the ATD field. The contribution of this paper is the presentation of a novel descriptive model, providing a comprehensive interpretation of the ATD phenomenon. This model categorizes the main characteristics of ATD and reveals their corresponding relations. The model is based on a systematic literature review (SLR) of currently recognized knowledge concerning ATD.