Towards a pattern language for construction and maintenance of software architecture traceability links

Javed, Muhammad Atif; Stevanetic, Srdjan; Zdun, Uwe

doi:10.1145/3011784.3011810

Cited by 4 publications

(5 citation statements)

References 38 publications

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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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“…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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“…pattern languages [9], expert systems [10], and metamodel-based ontologies [12]. Nevertheless, such approaches are limited to generating traces on the specific artifact, lacking generality.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, mockups, models, UIs, and other non-textual artifacts are beyond their scope. Similarly, other approaches limit their artifacts to model-based artifacts [12], requirements [9,13], and source code [9,11,13].…”

Section: Related Workmentioning

confidence: 99%

“…In practice, the effort required to maintain, validate, and generate traces between artifacts outweighs traceability benefits [5]. Therefore, some authors propose novel approaches that allow software development teams to create traces between artifacts [5][6][7][8][9][10][11][12][13]. Although such approaches are helpful, some of them require as input existing traceability data sets or existing traces between artifacts [5,6,8,11], hindering their practical applicability by software development teams that do not currently trace their artifacts.…”

Section: Introductionmentioning

confidence: 99%

“…Although such approaches are helpful, some of them require as input existing traceability data sets or existing traces between artifacts [5,6,8,11], hindering their practical applicability by software development teams that do not currently trace their artifacts. On the other hand, other approaches limit their scope to specific artifacts [7,9,10,12,13], lacking generality.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

OntoTrace: A Tool for Supporting Trace Generation in Software Development by Using Ontology-Based Automatic Reasoning

Mosquera,

Ruiz,

Pastor

et al. 2022

Lecture Notes in Business Information Processing

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Traceability in software development has gained interest due to its software maintainability and quality assurance benefits. Artifacts such as code, requirements, mockups, test cases, among others, are feasible trace sources/targets during the software development process. Existing scientific approaches support tasks like identifying untraced artifacts, establishing new traces, and validating existing traces. However, most approaches require input existing traceability data or are restricted to a certain application domain hindering their practical application. This contemporary challenge in information systems engineering calls for novel traceability solutions. In this paper, we present OntoTrace: a tool for supporting traceability tasks in software development projects by using ontology-based automatic reasoning. OntoTrace allows software development teams for inferring traceability-related data such as i) which are the traceable source/target artifacts; ii) which artifacts are not yet traced; and iii) given a specific artifact, which are the possible traces between it and other artifacts. We demonstrate how OntoTrace works in the context of the Swiss startup LogicFlow AG, supporting the traceability between functional/non-functional requirements and user interface test cases. We conclude the paper by reflecting on the experience from applying the approach in practice, and we draw on future challenges and next research endeavors.

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Ontology-Based Automatic Reasoning and NLP for Tracing Software Requirements into Models with the OntoTrace Tool

Mosquera¹,

Ruiz²,

Pastor³

et al. 2023

Lecture Notes in Computer Science

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Towards a pattern language for construction and maintenance of software architecture traceability links

Cited by 4 publications

References 38 publications

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

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

OntoTrace: A Tool for Supporting Trace Generation in Software Development by Using Ontology-Based Automatic Reasoning

Ontology-Based Automatic Reasoning and NLP for Tracing Software Requirements into Models with the OntoTrace Tool

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