Experience in developing system requirements specification for a sensor failure detection and identification scheme

Gobbo, D. Del; Napolitano, M.; Callahan, John R.; Čukić, Bojan

doi:10.1109/hase.1998.731614

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…Another study found that failed or abandoned systems cost $100 Billion in the USA [6]. According to the [7], The Standish Group's CHAOS survey of over 350 organizations and 8000 projects produced the following results [4,8,9] Therefore, it can be concluded that for software development process, a sequence of steps must be performed in order to complete a set of tasks. Requirement engineering plays an important role for the success of software product and building a high-quality software product.…”

Section: Requirements Engineeringmentioning

confidence: 99%

Requirements Engineering: A Survey

Shukla¹,

Pandey²,

Shree³

2015

CAE

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Software development process is the collection of a variety of phases. Requirement engineering is one of phases that involve in software development processes. From all the phases, Requirement Engineering phase play an important role for every software product. During requirement engineering phase, development team interacts with representative of stakeholders and uses these requirements to build up software product that satisfy the stakeholder's needs. After collecting all the requirements, these requirements can be divided into two categories. First category will take requirements those are important and necessary for software development at present time while the other category take requirements those are not important for the software product at present but can be important in future. The motive of requirement engineering is to find out exact requirement of the stakeholders with the help of step by step predefined procedure. Collected requirements can be first verified by stakeholders. At last, stakeholder and developer team sign contract. It cannot be concluded that requirement engineering phase completed at the beginning of the product development but incorporates parts of next phase of software engineering. In this paper, researcher tries to give basic information about software requirement engineering phase and present why requirement engineering is important for software development? General TermsSoftware Engineering KeywordsRequirement engineering, types of requirements, requirement engineering framework.

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Section: Requirements Engineeringmentioning

confidence: 99%

Requirements Engineering: A Survey

Shukla¹,

Pandey²,

Shree³

2015

CAE

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“…Recent work by both researchers [7] and practitioners has investigated how to model NFRs and to express them in a form that is measurable or testable. There also is a growing body of research concerned with particular kinds of NFRs, such as safety security [6], reliability [9], and usability.…”

Section: Modeling Non-functional Requirements (Nfrs)mentioning

confidence: 99%

Analysis and Need of Requirements Engineering

Kaur¹,

Singh²

2010

IJCA

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This paper presents outline of the field of software systems requirements engineering (RE). It describes the main areas of RE practice, and highlights some key open Research issues for the future and what is RE all about? When is it needed? What kinds of activities are involved in doing RE? Requirements engineering applies to the development of all software-intensive systems, but not necessarily to the development of all software, as we shall see. There are a huge range of different kinds of software-intensive system, and the practice of RE varies across this range. Our aim throughout this paper is to explore both what is common and what varies across these different types of system. The key techniques used in requirements engineering for dealing with complexity.

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“…Prior to adopting relational algebra an attempt was made to adopt SCR (Software Cost Reduction) encouraged by the mature development environment and the rich set of automatic tools that support the SCR specification language; results of this effort are documented in [DelGobbo98], [DelGobbo99], [CortellessaOO], and [AlexanderOO]. A number of issues prevented the SCR specification from ever reaching a mature status.…”

Section: Table 52 -Refinement Of Fault Hypothesesmentioning

confidence: 99%

“…The V&C for these neural schemes must start from a clear definition of the SFDIA and AFDIA system requirements followed by the introduction of ad-hoc analytical tools for assessing the closed-loop stability of the system leading to the final system certification. These issues are not trivial and their resolution is a critical phase prior to the actual implementation of artificial intelligence fault-tolerant control schemes on on-board computers [27][28][29][30].…”

Section: /(Xt/ld^t-^ + L (1)mentioning

confidence: 99%

YF22 Model With On-Board On-Line Learning Microprocessors-Based Neural Algorithms for Autopilot and Fault-Tolerant Flight Control Systems

Napolitano¹

2002

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing inslruclio data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect < this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 13 Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to con 1MB control number. PERFORMING ORGANIZATION REPORT NUMBER SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES)Dr ABSTRACTThis project focused on investigating the potential of on-line learning "hardware-based" neural approximators and controllers to provide fault tolerance capabilities following sensor and actuator failures. Following a phase of simulation studies a set of selected architectures for neural estimators and neural controllers were flown on a semi-scale YF-22 aircraft model. The YF-22 model was designed, built, and flown at research facilities at West Virginia University. Additionally, a customized electronic payload featuring these fault tolerant schemes was designed, built, tested and interfaced with the YF-22 flight control system. A series of 33 flight tests were conducted with the aircraft; the flight data confirmed the potential of neural estimators and controllers for fault tolerance purposes. Another research objective was to start addressing system requirements leading to the problem of software validation and verification for this new class of algorithms for fault tolerant flight control systems. SUBJECT TERMS ABSTRACTThis project focused on investigating the potential of on-line learning "hardwarebased" neural approximators and controllers to provide fault tolerance capabilities following sensor and actuator failures.Following a phase of simulation studies a set of selected architectures for neural estimators and neural controllers were flown on a semi-scale YF-22 aircraft model. The YF-22 model was designed, built, and flown at research facilities at West Virginia University. Additionally, a customized electronic payload featuring these fault tolerant schemes was also designed, built, tested and interfaced with the YF-22 flight control system. A series of 33 flight tests were conducted with the aircraft; the flight data confirmed the potential of neural estimators and controllers for fault tolerance purposes.Another research objective was to start addressing system requirements leading to the problem of software validation and verification for this new class of algorithms for fault tolerant flight control systems. Section #4: Development of a mathematical model for the WVU YF-22 using parameter estimation from flight data and development of a Matlab simulation code featuring online learning neural networks for fault tolerant flight control systems (sensor and actuator failures). INTRODUCTIONThis document presents a summary o...

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Experience in developing system requirements specification for a sensor failure detection and identification scheme

Cited by 7 publications

References 8 publications

Requirements Engineering: A Survey

Requirements Engineering: A Survey

Analysis and Need of Requirements Engineering

YF22 Model With On-Board On-Line Learning Microprocessors-Based Neural Algorithms for Autopilot and Fault-Tolerant Flight Control Systems

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