Software Patterns for Traceability of Requirements to Finite State Machine Behavior

Delgoshaei, Parastoo; Austin, Mark

doi:10.1016/j.procs.2012.01.045

Cited by 6 publications

(2 citation statements)

References 2 publications

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“…Railways have primarily used ontologies for describing railway systems in order to support traceability of information in data integration processes and design engineering processes. [67][68][69][70][71] The combination of information from different railway data sources can provide valuable insights about the railway system and its engineering processes; however, it requires a complete and structured data in order to analyse them. For instance, in the TD feed, a piece of track is referred to as a block number but in Close Call, a distance from a station indicates that same piece of track.…”

Section: Ontologiesmentioning

confidence: 99%

The case for IT transformation and big data for safety risk management on the GB railways

Gulijk

Hughes

Figueres-Esteban

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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This paper presents the case for IT transformation and big data for safety risk management on the GB railways. This paper explains why the interest in data driven safety solutions is very high in the railways by describing the drivers that shape risk management for the railways. A brief overview of research projects in the Big Data Risk Analysis (BDRA) programme supports the case and helps understand the research agenda for the transformation of safety and risk on the GB railways. The drivers and the projects provide insight in the current research needs for the transformation and explains why safety researchers have to broaden their skill set to include digital skills and potentially even programming. The case for IT transformation of risk management systems is compelling and the paper describes just the tip of the iceberg of opportunities opening up for safety analysis that, after all, depends on data.

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Section: Ontologiesmentioning

confidence: 99%

The case for IT transformation and big data for safety risk management on the GB railways

Gulijk

Hughes

Figueres-Esteban

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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show abstract

“…To experimentally assess this assertion, we are designing and building a series of progressively complicated software prototypes for requirements to finite state machine traceability. Our first application modeled the operation of a simple lamp that accepts user clicks as input, but also has clock and time model for automatic switching of the lamp state at prescribed times (Delgoshaei and Austin 2012). This section describes our second application, requirements-to-behavior traceability for trains operating in a simplified of the Washington DC Metro, the second largest rail transit system in the US.…”

Section: Application To Rail Transit Systems Design and Managementmentioning

confidence: 99%

Software Patterns for Traceability of Requirements to Finite State Machine Behavior: Application to Rail Transit Systems Design and Management

Delgoshaei

Austin

2012

INCOSE International Symp

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Abstract. This paper describes a software design pattern (e.g., hierarchical graphs of modelview-controllers) and models of visualization for ontology-enabled traceability, where requirements are traced to elements of finite-state machine behavior (e.g., actions, states, transitions and guard conditions). These ontology-enabled traceability mechanisms will play an important role in the team-based development of network-enabled platforms for analysis, design, and early validation and verification of information-age engineering systems. The application of these concepts is illustrated through the study of a simplified rail transit system.

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9.1.1 Semantic Platforms for Cyber‐Physical Systems

Petnga

Austin

2014

INCOSE International Symp

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Abstract. This paper describes the development of semantic platforms to support the modeling, architectural design, realization, and operation of cyber-physical systems. Platform architectures work directly with formal models of domain knowledge (not just raw data) that are determinate, provable (ambiguity free), executable, and with semantic parameters and rule engines that reason with physical quantities and across domains. These concepts are exercised in a case study application: the "decision-dilemma problem" for traffic systems.

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Software Patterns for Traceability of Requirements to Finite State Machine Behavior

Cited by 6 publications

References 2 publications

The case for IT transformation and big data for safety risk management on the GB railways

The case for IT transformation and big data for safety risk management on the GB railways

Software Patterns for Traceability of Requirements to Finite State Machine Behavior: Application to Rail Transit Systems Design and Management

9.1.1 Semantic Platforms for Cyber‐Physical Systems

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