Decision knowledge triggers in continuous software engineering

Kleebaum, Anja; Johanßen, Jan Ole; Paech, Barbara; Alkadhi, Rana; Bruegge, Bernd

doi:10.1145/3194760.3194765

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…In addition, we are working on the implementation of the presented CURES vision. We are incrementally implementing the proposed components in the form of tool and platform support. Using this work in progress, we are evaluating the acceptance of the implementations by applying them in a multi‐project course that provides access to a real‐world development setting.…”

Section: Resultsmentioning

confidence: 99%

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Continuous software engineering and its support by usage and decision knowledge: An interview study with practitioners

Johanßen

Kleebaum

Paech

et al. 2019

J Software Evolu Process

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Continuous software engineering (CSE) emerged as a process that is increasingly applied by practitioners. However, different perceptions impede its adoption in industry. Furthermore, opportunities through utilizing usage and decision knowledge remain unexploited. We conducted a semi‐structured interview study with 24 practitioners from 17 companies to study how practitioners apply CSE during software evolution and how usage and decision knowledge can support CSE. Regarding the application of CSE, we identified five perspectives on CSE with tool‐ and methodology‐driven definitions most prevalent. Automated tests, involved users, and shared rulesets are perceived as most relevant for CSE. Practitioners report more positive than negative experiences; however, more than half of their responses were neutral. Practitioners' future plans for CSE focus on enhancement, expansion, and on‐demand adaption. Regarding the integration of usage and decision knowledge into CSE, practitioners perceive accountability and traceability as major benefits, while raising concerns about its feasibility and user groups. As short‐term extensions, practitioners expect improvements regarding automation and role aspects, while long‐term additions to integration and experimentation capabilities are demanded. We conclude that CSE remains partially difficult to capture for practitioners, while their attitude toward integrating usage and decision knowledge into CSE is positive.

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Section: Resultsmentioning

confidence: 99%

“…CSE offers new opportunities to overcome this capture problem since it provides multiple practices and documentation locations in which developers can capture decision knowledge. () For example, developers capture decisions when they commit code in commit messages …”

Section: Foundationsmentioning

confidence: 99%

Continuous software engineering and its support by usage and decision knowledge: An interview study with practitioners

Johanßen

Kleebaum

Paech

et al. 2019

J Software Evolu Process

Self Cite

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show abstract

“…We aim to provide solution proposals for these findings applicable for practitioners [12]. In [7] and [13], we describe ideas for a continuous decision knowledge management (ConDec) as part of CSE and in [14] we present a dashboard for knowledge visualization. The ConDec tool support 1 integrates with existing tools to minimize the intrusiveness of the decision knowledge management, e. g., with the issue tracking system.…”

Section: Discussionmentioning

confidence: 99%

How do Practitioners Manage Decision Knowledge during Continuous Software Engineering? (S)

Kleebaum¹,

Johanßen²,

Paech³

et al. 2019

International Conferences on Software Engineering and Knowledge Engineering

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Continuous software engineering (CSE) is an agile process that supports lightweight, flexible, and rapid software development. Decision-making is crucial for CSE, and developers need to know the decisions made and the related rationale to evolve the software. This knowledge is called decision knowledge. The management of decision knowledge in CSE environments remains unexplored. The agile manifesto suggests to value working software over comprehensive documentation as well as individuals and interactions over processes and tools. What does this mean for the documentation, exploitation, and sharing of decision knowledge? We report on results from an interview study with 24 practitioners from 17 companies on how decision knowledge is managed during CSE. The practitioners mainly capture decision knowledge in an informal way, for example, in natural language discussions. Wiki and issue tracking systems represent the preferred medium to preserve decision knowledge. Mentioned benefits are an improved decision-making process, accountability, knowledge sharing, and reuse. However, the exploitation of the captured decision knowledge remains partly unclear.

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“…System Tool [24], [48], [16], [36], [4], [50], [31], [39] 8 23.53% Design Complement Tool [22], [55], [49], [7], [5], [51], [52],…”

Section: Papers Count Percentagementioning

confidence: 99%

Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study

Hyun,

Hurtado

2023

Foundations of Computing and Decision Sciences

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The definition of architecture is a crucial task in software development, where the architect is responsible for making the right decisions to meet specific functional and quality requirements. These architectural design decisions form the foundation that shapes the arrangement of elements within a system. Unfortunately, these decisions are often poorly documented, implicit in various artifacts, or inadequately updated, leading to negative consequences on the maintainability of a system and resulting in rework and cost overruns. The objective of this systematic mapping study is to comprehend the current state regarding approaches for traceability of architectural design decisions and how these decisions are linked with the different artifacts used in software development. To achieve this, an information extraction protocol is followed, utilizing databases with search strings, inclusion, and exclusion criteria. The findings demonstrate that this knowledge is highly relevant; however, it is rarely explicitly documented. As a result, most works propose diverse approaches to extract this knowledge from existing technical documentation, commonly used tools, and other sources of product and process information. In contrast, it is evident that there is no standard for documenting design decisions, leading each author to present a subjective version of what is important and where to trace these decisions. This suggests that there is still a significant amount of research to be conducted regarding the traceability of these architectural design decisions and their connection with software artifacts. Such research could lead to intriguing new proposals for investigation.

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Decision knowledge triggers in continuous software engineering

Cited by 9 publications

References 16 publications

Continuous software engineering and its support by usage and decision knowledge: An interview study with practitioners

Continuous software engineering and its support by usage and decision knowledge: An interview study with practitioners

How do Practitioners Manage Decision Knowledge during Continuous Software Engineering? (S)

Traceability of Architectural Design Decisions and Software Artifacts: A Systematic Mapping Study

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