Technical debt from the stakeholder perspective

Theodoropoulos, Ted; Hofberg, Mark; Kern, Daniel

doi:10.1145/1985362.1985373

Cited by 19 publications

(10 citation statements)

References 2 publications

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“…redundant data). According to [17], we further argue that data can carry TD in form of bad data quality. As data is moving through the whole system, it can generate new TD in other parts.…”

Section: Technical Debt Emergence and Proliferation Within Data-inmentioning

confidence: 99%

Technical Debt in Data-Intensive Software Systems

Foidl

Felderer

Biffl

2019

2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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The ever-increasing amount, variety as well as generation and processing speed of today's data pose a variety of new challenges for developing Data-Intensive Software Systems (DISS). As with developing other kinds of software systems, developing DISS is often done under severe pressure and strict schedules. Thus, developers of DISS often have to make technical compromises to meet business concerns. This position paper proposes a conceptual model that outlines where Technical Debt (TD) can emerge and proliferate within such data-centric systems by separating a DISS into three parts (Software Systems, Data Storage Systems and Data). Further, the paper illustrates the proliferation of Database Schema Smells as TD items within a relational database-centric software system based on two examples.

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“…redundant data). According to [17], we further argue that data can carry TD in form of bad data quality. As data is moving through the whole system, it can generate new TD in other parts.…”

Section: Technical Debt Emergence and Proliferation Within Data-inmentioning

confidence: 99%

Technical Debt in Data-Intensive Software Systems

Foidl

Felderer

Biffl

2019

2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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“…We observe four interrelated research streams in the emerging literature on technical debt: (a) taxonomy, frameworks, and perspectives on technical debt [1,2,3,4,5,6,7,8,9]; (b) identifying, measuring, and visualizing technical debt [9,10,11,12,13,14]; (c) measuring and assessing the impact of technical debt on project and firm performance [6,15,16,17,18,19,20,21,22,23]; and (d) decision frameworks for managing technical debt [3,24,25,26,27,28,29]. Moving beyond the metaphorical conceptualization of technical debt, these four streams of research collectively pave a way to develop rigorous empirical models that could be used to derive appropriate policies for managing technical debt.…”

Section: Introductionmentioning

confidence: 99%

Towards a model for optimizing technical debt in software products

Ramasubbu¹,

Kemerer²

2013

2013 4th International Workshop on Managing Technical Debt (MTD)

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There is a growing interest in applying the technical debt metaphor to investigate issues related to the tradeoff of the likely long-term costs associated with software design shortcuts for expected short-term business benefits in terms of increased earlier functionality. We propose an optimization model that contrasts the patterns of technical debt accumulation in a software product with the patterns of consumer adoption of the product throughout its evolution. This facilitates a rigorous and balanced analysis of the pros and cons of accumulating technical debt at various lifecycle stages of a software product. We discuss the use of the optimization model to derive policies for managing technical debt and the potential for empirical tests of the model and other future interdisciplinary research.

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“…Practitioners from the software development community have suggested many good practices to reduce Technical Debt [2] [3] [5] [6]. As described in the table below these practices can be classified into 3 groups: Practices to Identify, Practices to Classify and Practices to Reduce.…”

Section: Introductionmentioning

confidence: 99%

Minimizing technical debt: developer's viewpoint

Krishna¹,

Basu

2012

International Conference on Software Engineering and Mobile Application Modelling and Development (ICSEMA 2012)

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Often we find it difficult to adapt to any changes during later phases of a software development project. Primary reason for this is rigidity in design and code which do not allow major changes to be incorporated. This inflexibility substantially increases the cost of post-delivery enhancement and maintenance and is termed as Technical Debt. As Technical Debt cannot be eliminated completely, we need to reduce its burden.Many practitioners, especially from agile community, have suggested some practices to avoid or overcome the Technical Debt. This paper explores the methods for relief from Technical Debt and proposes thirteen steps that a developer should follow to minimize technical debt. These steps have proved to be effective when implemented in projects as discussed in this paper.

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Technical debt from the stakeholder perspective

Cited by 19 publications

References 2 publications

Technical Debt in Data-Intensive Software Systems

Technical Debt in Data-Intensive Software Systems

Towards a model for optimizing technical debt in software products

Minimizing technical debt: developer's viewpoint

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