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Application of Hazard and Operability (HAZOP) Methodology to Safety-Related Scientific Software

Gupta, Jatin
http://rave.ohiolink.edu/etdc/view?acc_num=osu1398983873

Abstract Details

2014, Doctor of Philosophy, Ohio State University, Mechanical Engineering.
A number of issues can plague the reliability of results computed using any software. When software is used to make safety critical decisions it is imperative that the results be dependable and that either there be no errors in the computed results or the error in the results be known to the user. This dissertation addresses the issues that can affect the accurate computation of results of scientific software. Scientific software is defined as software that performs extensive computations to model some physical phenomenon and provide results that can support decision making. The primary issues that affect the results of scientific software can be broadly classified into three categories: (1) incorrect requirements (2) coding errors and (3) missing requirements. This dissertation addresses these issues by adapting the Hazard and Operability (HAZOP) method for application to scientific software. Before applying HAZOP method to scientific software, a representation of the system (scientific software) is developed from its requirements written in formal language (Z specification language). Using a formal notation in writing requirements reduces ambiguity in the specification and also offers an opportunity to mathematically verify them. Another advantage of using formal specifications is that test cases can be developed from the resulting representation of the system which tests the functionality of the system. Missing requirements pose a big threat since they cannot be identified from testing and therefore can reduce the dependability on the results without the knowledge of the user. Missing requirements are commonly observed to be related to operational environment of the system. HAZOP analysis helps in the identification of such requirements as it provides a structured approach for exploration of system failure modes by suggesting hypothetical failures. This dissertation provides details on (1) development of system representation from Z-specification language and (2) application of HAZOP methodology to scientific software. The tools developed to automate the process of system representation development and conduct scientific software HAZOP analysis are also discussed. Overall, the scientific software HAZOP methodology helps to identify useful information about the impact of variables in the code that can then be utilized to develop robust code for making safety-critical decisions.
Carol Smidts, Professor (Advisor)
Tunc Aldemir, Professor (Committee Member)
Richard Denning, Professor (Committee Member)
Lei Cao, Professor (Committee Member)
Laura Lindsey, Professor (Committee Member)
186 p.
Engineering; Mathematics; Mechanical Engineering
HAZOP, FSM, Z-specification, Finite State Machine, Formal Language, Software Reliability, Safety Critical System, Domain Partition, Disjunctive Normal Form, DNF

Recommended Citations

Citations

  • Gupta, J. (2014). Application of Hazard and Operability (HAZOP) Methodology to Safety-Related Scientific Software [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398983873

    APA Style (7th edition)

  • Gupta, Jatin. Application of Hazard and Operability (HAZOP) Methodology to Safety-Related Scientific Software. 2014. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1398983873.

    MLA Style (8th edition)

  • Gupta, Jatin. "Application of Hazard and Operability (HAZOP) Methodology to Safety-Related Scientific Software." Doctoral dissertation, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398983873

    Chicago Manual of Style (17th edition)

osu1398983873
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© 2014, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.