The Impact of Forced Working-From-Home on Code Technical Debt: An Industrial Case Study

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 (TD) is a metaphor that reflects the technical compromises that sacrifice the long-term health of a software product to achieve short term benefit. It is important to manage TD to avoid software degradation. In large-scale distributed projects, technical debt management (TDM) becomes more complex and challenging. There is a lack of empirical studies on the TD accumulation in large-scale distributed projects. Then, to address this gap, we conducted a case study in Ericsson (a European Telecom Company) to identify the relationship between TD accumulation and factors such as task complexity, lead time, total of developers, and task scaling. We used data from 33 projects extracted from managerial documents to conduct a regression analysis. We also conducted interviews with seniors developers of the team to interpret the results. We found out that Task Complexity has a strong relationship (p-value = 5.69 × 10-5) with Technical Debt, while Global Distance was mentioned by the interviewees as a relevant factor for TD accumulation (although not statistically significant in our regression analysis). Practitioners should consider avoiding complex/big tasks, breaking down big tasks into small ones (if possible). We also plan to analyze other projects in this company to confirm our findings further. © 2021 IEEE.

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.

Making sub-optimal design decisions during software development leads to the accumulation of Technical Debt (TD) in software projects. There are tools to identify TD Items in software code through static code analysis. However, quantifying TD to support decision-making on whether to keep taking on TD or if it is time to refactor TD is a difficult task, and proposed approaches for this still lack consensus. Prior work observed that TD Interest could be further decomposed into constituents 'New Code Cost' and 'Rework Cost', which gives an interesting direction of research to explore TD quantification in terms of these costs. Therefore, through our empirical study, we plan to explore the relationship between TD, New Code Cost and Rework Cost in Open-Source Software Projects. This paper reports on an initial motivating study, our plan for future work and implications for researchers.

One major problem in using static analyzers to manage, monitor, control, and reason about technical debt is that industrial projects have a huge amount of technical debt which reflects hundreds of quality rule violations (e.g., high complex module or low comment density). Moreover the negative impact of violating quality rules (i.e., technical debt interest) may vary across rules or even across contexts. Thus, without a context-specific validation and prioritization of quality rules, developers cannot effectively manage technical debt. This paper reports on a case study aimed at exploring the interest associated with violating quality rules; i.e., we investigate if and which quality rules are important for software developers. Our empirical method consists of a survey and a quantitative analysis of the historical data of a CMMI Level 5 software company. The main result of the quantitative analysis is that classes violating several quality rules are five times more defect prone than classes not violating any rule. The main result of the survey is that some rules are perceived by developers as more important than others; however, there is no false positive (i.e., incorrect rule or null interest). These results pave the way to a better practical use of quality rules to manage technical debt and describe new research directions for building a scientific foundation to the technical debt metaphor.

Context: Software startups are software-intensive early phase companies with high growth rates. Previous researchers regarded startups’ time to market as short and decisive in establishing the product/service success. This led to shortcuts in software engineering decisions. Researchers in previous investigations documented a high accumulation of technical debt (TD) in early startup phases. However, we found little evidence in the literature concerning TD when startups transition to the growth phase. Aim: Our goal was to evaluate how the transition from early to growth phases affects TD perception in software startups. Methodology: We conducted a pilot study guided by semi-structured interviews from multiple software startup cases. Results: We identified the four following dimensions: (1) managing, (2) accepting, (3) avoiding, and (4) ignoring TD. Contribution: Our study will allow practitioners to address TD in growth-phase software startups. Future researchers can benefit from our findings by conducting exploratory studies and providing educated recommendations.

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.

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

Technical debt (TD) is a concept used to describe a sub-optimal solution of a software artifact that negatively affects its comprehensibility, extendability and maintainability. As such, TD adversely affects the costs or quality associated with the artifact, which is also called interest. TD has through research been identified in all types of software artifacts, from architectural design to automated tests (Testware). However, research into testware technical debt (TTD) is limited and primarily focused on testing on lower level of system abstraction, i.e. unit-and integration tests, leaving a need for more TTD research on GUI-based testing. In this study we explore this gap in knowledge through an industrial case study at a Swedish avionics software development company. Four repositories are studied for the presence of TTD using expert interviews, semi-automated document analysis and automatic metric analysis. Results of the study provide initial support that the concept of TTD is applicable to GUI-based testware and show the presence of both TD items unique to GUI-based testware and items common to software. The implications of these results are that engineering best practices must be established for GUI-based testware to minimize TD interest.

The relation between technical debt and corrective maintenance in PHP web applications

Model‐Based Systems Engineering (MBSE) is the next step in the evolution of systems engineering (SE) in which documents are replaced by descriptive models as the authoritative embodiment of SE knowledge. These descriptive models possess a unique combination of the features and characteristics of documents, software, and data. Conscientiously applying appropriate modeling principles and practices is essential to make informed decisions to moderate the accumulation of model technical debt. This paper briefly explains the concept of technical debt and its adaptation to the domain of descriptive models for MBSE. The paper then describes 18 foundational modeling principles that model architects should consider when making architectural and implementation decisions about their models and describes some of the key model technical debt tradeoffs that result when these principles are not followed. These principles address commonly observed challenges regarding model federation architecture, the selection and use of model layers, the modeling of the domain, and the semantics of modeling constructs. Applying disciplined model architecting practices to conscientiously manage the accrual and payoff of technical debt can make the difference between an enduring model that provides substantial value throughout the life cycle of the modeled entity and a model whose value collapses under the weight of uncontrolled technical debt.

Work from home (WFH) has recently become a common work modality. Scarce evidence exists assessing determinants of 24-hour movement behaviors (24 MBs) in WFH workers. The aim of this study was to identify 24 MB determinants in WFH. Device-measured (activPAL3 Micro, Actiwatch Spectrum Plus) and self-reported (four questionnaires) 24 MB data were assessed quantitatively in 27 WFH desk workers. Qualitative data were gathered using transcripts from five focus groups to identify determinants for 24 MBs in WFH. Participants displayed low adherence to physical activity and sedentary behavior guidelines but healthy sleep patterns. Focus groups revealed three key themes: (1) workspace characteristics, (2) support for healthy living, and (3) non-work-related influences. Device and focus group findings suggest improving waking day behaviors by leveraging the WFH physical environment, garnering social support, and improving self-efficacy could contribute to improving 24 MBs in WFH desk workers.

The article examines the transformation of the technical debt concept amid the rapid proliferation of artificial intelligence and analyzes methods for its forecasting. The aim is to identify the characteristics of the accumulation and evolution of technical debt in AI systems and to develop approaches for its measurement and strategic management. The relevance stems from the fact that technical debt has ceased to be a local engineering problem and has acquired macroeconomic and organizational significance, affecting company productivity, the resilience of business processes, and compliance with regulatory requirements. The novelty of the study is in organizing a multi-layer structure of debt obligations, not by including only classical code and architectural elements, but by adding new layers data debt, model debt, pipeline debt, as well as regulatory and workforce costs. The article presents an approach to forecasting debt risks, hybridizing static metrics, machine classifiers, graph dependency models, time series of operational metrics, and scenario modeling with large language models. A major takeaway is that AI technical debt can only be effectively managed once a full account of all its layers has been brought into consideration and their linkages to business metrics, plus regular monitoring and forecasting, are institutionalized. In practical terms, turning the debt from being just an abstract metaphor into a manageable asset reduces interest expense while, at the same time, increasing the resilience of technological development. The article will be helpful to researchers in software engineering, machine learning practitioners, IT system architects, and leaders of digital transformations.

The COVID-19 outbreak has caused a massive increase in the number of Malaysians working from home. This scenario has put the living and working gap at disposal, questioning the relevance of the ‘living lifestyle’, particularly in new housing township projects. This paper investigates the culture of working from home (WFH) and its influence on the spatial design of developer-designed terraced housing scheme for a new Suburban Township in Malaysia. Using qualitative observation and comparative analysis between developer’s home buying guide and the show unit, the findings suggest that ‘flexible open volume’ plan created through nooks and openings are the speculative future in promoting working from home. Hence, it advocates developers towards a double-frontage housing township that allows integration of living-working lifestyle as everyone works where they live and not vice-versa. Keywords: Working from home; Mindfulness; Spatial innovation; Housing development trend eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6i16.2728

The start of the COVID-19 virus epidemic is having an impact on radical changes in the labor market. The difficult economic situation is a challenge for employers, candidates and recruiters. In recent months, the recruitment market has seen a decline in the work forces, redundancy, and a reduction in salaries. As a result of this situation, some workplaces have used the remote work model. The possibility of remote work can be a good solution for many employees, but in some cases, it can be a significant inconvenience, especially for employees who have underage children and perform their work duties at home. Aim of the article is present positive and negative aspects of remote work during the COVID-19 pandemic. The research presented in the article was aimed at assessing changes in working conditions and starting remote work. The positive effects of changes in workplaces include saving time, adjusting work to personal needs, and work-life balance. The disadvantages of taking up remote work include lack of direct contact with co-workers, blurring the boundaries between private and professional life, maintaining a constant presence at work, lack of social ties and isolation were identified as the most significant obstacles to remote work during the COVID-19 pandemic. Despite the negative aspects of working remotely, the respondents more often declared their willingness to work remotely also after the end of the pandemic.