A Semantic Approach for Traceability Link Recovery in Aerospace Requirements Management System

Mahmood, Khalid; Takahashi, Hirokazu; Alobaidi, Mazen

doi:10.1109/isads.2015.33

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…Mahmood et al proposed to use semantic knowledge for automatic traceability chain recovery in aerospace demand supervisory system. The purpose is to cut down the consumption cost of time and resources, help software engineering projects meet business needs, and improve the efficiency of time management (Mahmood et al, 2015).…”

Section: Applications Of Semantics In Aerospacementioning

confidence: 99%

A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data

Liu

et al. 2021

Journal of Organizational and End User Computing

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With the rapid development of satellite technology, remote sensing data has entered the era of big data, and the intelligent processing of remote sensing image has been paid more and more attention. Through the semantic research of remote sensing data, the processing ability of remote sensing data is greatly improved. This paper aims to introduce and analyze the research and application progress of remote sensing image satellite data processing from the perspective of semantic. Firstly, it introduces the characteristics and semantic knowledge of remote sensing big data; Secondly, the semantic concept, semantic construction and application fields are introduced in detail; then, for remote sensing big data, the technical progress in the study field of semantic construction is analyzed from four aspects: semantic description and understanding, semantic segmentation, semantic classification and semantic search, focusing on deep learning technology; Finally, the problems and challenges in the four aspects are discussed in detail, in order to find more directions to explore.

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Section: Applications Of Semantics In Aerospacementioning

confidence: 99%

A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data

Liu

et al. 2021

Journal of Organizational and End User Computing

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“…Our earlier work [40] mentions an application where AD-STLR can be applied on "Weather Services for Air Traffic Aviation in Detroit". This paper presents development of National Aeronautics and Space Administration (NASA) autonomous drone traffic management application.…”

Section: Applicationmentioning

confidence: 99%

Autonomous Decentralized Semantic Based Traceability Link Recovery Framework

Mahmood

Alobaidi

Takahashi³

2016

IEICE Trans. Inf. & Syst.

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SUMMARYThe automation of traceability links or traceability matrices is important to many software development paradigms. In turn, the efficiency and effectiveness of the recovery of traceability links in the distributed software development is becoming increasingly vital due to complexity of project developments, as this include continuous change in requirements, geographically dispersed project teams, and the complexity of managing the elements of a project -time, money, scope, and people. Therefore, the traceability links among the requirements artifacts, which fulfill business objectives, is also critical to reduce the risk and ensures project's success. This paper proposes Autonomous Decentralized Semantic based Traceability Link Recovery (AD-STLR) architecture. According to best of our knowledge this is the first architectural approach that uses an autonomous decentralized concept, DBpedia knowledge-base, Babelnet 2.5 multilingual dictionary and semantic network, for finding similarity among different project artifacts and the automation of traceability links recovery.

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“…Traceability has been mentioned in many software development methodologies as part of software engineering practice. Maintaining the trace links between software artifacts is crucial to perform various software engineering activities including change impact analysis [1], requirements coverage analysis [2], requirements verification and validation [3], test case selection [4], compliance verification [5], issue assignment [6] and bug localization [7]. Over the last few decades, researchers have attempted to recover trace links automatically using Information Retrieval (IR) techniques.…”

Section: Introductionmentioning

confidence: 99%

Interactive Traceability Links Visualization using Hierarchical Trace Map

Aung

Huo

Sui

2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Traceability links between various software artifacts of a system aid software engineers in system comprehension, verification and change impact analysis. Establishing trace links between software artifacts manually is an error-prone and costly task. Recently, studies in automated traceability link recovery area have received broad attention in the software maintenance community aiming to overcome the challenges of manual trace links maintenance process. In these studies, the trace links results generated by an automated trace recovery approach are presented either in a bland textual matrix format (e.g., tabular format) or two-dimensional graphical formats (e.g. tree view, hierarchical leaf node). Therefore, it is challenging for software engineers to explore the inter-relationships between various artifacts at once (e.g., which test cases and source code files/methods are related to a particular requirement). In this position paper, we propose a hierarchical trace map visualization technique to explore inter-relationships between various artifacts at once naturally and intuitively.

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A Semantic Approach for Traceability Link Recovery in Aerospace Requirements Management System

Cited by 9 publications

References 8 publications

A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data

A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data

Autonomous Decentralized Semantic Based Traceability Link Recovery Framework

Interactive Traceability Links Visualization using Hierarchical Trace Map

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