The Perception of Technical Debt in the Embedded Systems Domain:An Industrial Case Study

Technical Debt Management (TDM) has drawn the attention of software industries during the last years, including embedded systems. However, we currently lack an overview of how practitioners from this application domain perceive technical debt. To this end, we conducted a multiple case study in the embedded systems industry, to investigate: (a) the expected life-time of components that have TD, (b) the most frequently occurring types of TD in them, and (c) the significance of TD against run-time quality attributes. The case study was performed on seven embedded systems industries (telecommunications, printing, smart manufacturing, sensors, etc.) from five countries (Greece, Netherlands, Sweden, Austria, and Finland). The results of the case study suggest that: (a) maintainability is more seriously considered when the expected lifetime of components is larger than ten years, (b) the most frequent types of debt are test, architectural, and code debt, and (c) in embedded systems the run-time qualities are prioritized compared to design-time qualities that are usually associated with TD. The obtained results can be useful for both researchers and practitioners: the former can focus their research on the most industrially-relevant aspects of TD, whereas the latter can be informed about the most common types of TD and how to focus their TDM processes

Technical Debt: An empirical investigation of its harmfulness and on management strategies in industry

Background: In order to survive in today\u27s fast-growing and ever fast-changing business environment, software companies need to continuously deliver customer value, both from a short- and long-term perspective. However, the consequences of potential long-term and far-reaching negative effects of shortcuts and quick fixes made during the software development lifecycle, described as Technical Debt (TD), can impede the software development process.Objective: The overarching goal of this Ph.D. thesis is twofold. The first goal is to empirically study and understand in what way and to what extent, TD influences today’s software development work, specifically with the intention to provide more quantitative insight into the field. Second, to understand which different initiatives can reduce the negative effects of TD and also which factors are important to consider when implementing such initiatives.Method: To achieve the objectives, a combination of both quantitative and qualitative research methodologies are used, including interviews, surveys, a systematic literature review, a longitudinal study, analysis of documents, correlation analysis, and statistical tests. In seven of the eleven studies included in this Ph.D. thesis, a combination of multiple research methods are used to achieve high validity.Results: We present results showing that software suffering from TD will cause various negative effects on both the software and the developing process. These negative effects are illustrated from a technical, financial, and a developer’s working situational perspective. These studies also identify several initiatives that can be undertaken in order to reduce the negative effects of TD.Conclusion: The results show that software developers report that they waste 23% of their working time due to experiencing TD and that TD required them to perform additional time-consuming work activities. This study also shows that, compared to all types of TD, architectural TD has the greatest negative impact on daily software development work and that TD has negative effects on several different software quality attributes. Further, the results show that TD reduces developer morale. Moreover, the findings show that intentionally introducing TD in startup companies can allow the startups to cut development time, enabling faster feedback and increased revenue, preserve resources, and decrease risk and thereby contribute to beneficial\ua0effects. This study also identifies several initiatives that can be undertaken in order to reduce the negative effects of TD, such as the introduction of a tracking process where the TD items are introduced in an official backlog. The finding also indicates that there is an unfulfilled potential regarding how managers can influence the manner in which software practitioners address TD

Technical debt-aware and evolutionary adaptation for service composition in SaaS clouds

The advantages of composing and delivering software applications in the Cloud-Based Software as a Service (SaaS) model are offering cost-effective solutions with minimal resource management. However, several functionally-equivalent web services with diverse Quality of Service (QoS) values have emerged in the SaaS cloud, and the tenant-specific requirements tend to lead the difficulties to select the suitable web services for composing the software application. Moreover, given the changing workload from the tenants, it is not uncommon for a service composition running in the multi-tenant SaaS cloud to encounter under-utilisation and over-utilisation on the component services that affects the service revenue and violates the service level agreement respectively. All those bring challenging decision-making tasks: (i) when to recompose the composite service? (ii) how to select new component services for the composition that maximise the service utility over time? at the same time, low operation cost of the service composition is desirable in the SaaS cloud. In this context, this thesis contributes an economic-driven service composition framework to address the above challenges. The framework takes advantage of the principal of technical debt- a well-known software engineering concept, evolutionary algorithm and time-series forecasting method to predictively handle the service provider constraints and SaaS dynamics for creating added values in the service composition. We emulate the SaaS environment setting for conducting several experiments using an e-commerce system, realistic datasets and workload trace. Further, we evaluate the framework by comparing it with other state-of-the-art approaches based on diverse quality metrics

A Financial Approach for Managing Interest in Technical Debt

Technical debt (TD) is a metaphor that is used by both technical and management stakeholders to acknowledge and discuss issues related to compromised design-time qualities. Until now, despite the inherent relevance of technical debt to economics, the TD community has not sufficiently exploited economic methods/models. In this paper we present a framework for managing interest in technical debt, founded on top of Liquidity Preference, a well-known economics theory. To tailor this theory to fit the TD context, we exploit the synthesized knowledge as presented in two recent studies. Specifically, in our framework, we discuss aspects related to technical debt interest, such as: types of TD interest, TD interest characteristics, and a proposed TD interest theory. Finally, to boost the amount of empirical studies in TD research, we propose several tentative research designs that could be used for exploring the notion of interest in technical debt practice