article

Free access

Concepts and criteria to assess acceptability of simulation studies: a frame of reference

Author:

Tuncer I. ÖrenAuthors Info & Claims

Communications of the ACM, Volume 24, Issue 4

Pages 180 - 189

https://doi.org/10.1145/358598.358605

Published: 01 April 1981 Publication History

PDF eReader

References

[1]

Allen, B. and Clema, J.K. Independent Verification/Validation Support Software. Proc. Nat'l Aerospace and Electron. Conf., Dayton, Ohio, March 1976, pp. 276-281.

Google Scholar

[2]

Annino, J.S. and Russell, E.C. The ten most frequent causes of simulation analysis failure-and how to avoid them. Simulation Today, 60, (June 1979), pp. 137-140.

Crossref

Google Scholar

[3]

B ahr, D. A note on figures of merit. A CM Performance Evaluations Rev., 4, 3, (July 1975), pp. 1-3.

Digital Library

Google Scholar

[4]

Balci, O. and Sargent, R.G. Bibliography on Validation of Simulation Models. Newsletter-TIMS College on Simulation and Gaming, Spring 1980, pp. 11-15.

Google Scholar

[5]

Beer, S. Platform for Change. Wiley, New York, 1975.

Google Scholar

[6]

Belady, L.A. and Leavenworth, B. Program Modifiability. IBM, Thomas J. Watson Research Center, Res. Rept. RC 8147, 1980.

Google Scholar

[7]

Boulton, J. and Gibson, A.R. First Ann. Rept. Canadian Nuclear Fuel Waste Management Program, Rept AECL-6443, Atomic Energy of Canada Ltd., Pinawa, Manitoba, 1979.

Google Scholar

[8]

Britting, K.R. Backward integration of system dynamics models- A useful validation test? In Worm Modeling: A Dialogue. C.W. Churchman and R.O. Mason (Eds.) Elsevier, New York, 1976, pp. 141-149.

Google Scholar

[9]

Cellier, F.E. Combined continuous/discrete system simulation by use of digital computers: Techniques and tools, Ph.D. Th.,Diss ETH No. 6483, Zurich, Switzerland. 1979, (Chapter 6-Software Robustness, pp. 121-159).

Google Scholar

[10]

Cellier, F.E. How to enhance the robustness of simulation software. In Progress in Modelling and Simulation. F.E. CeUier (Ed.) Academic (London), England, (In press).

Google Scholar

[11]

Cellier, F.E. and Moebius, P.J. Towards robust general purpose simulation software. ACM S1GNUM 14, 2, (June 1979).

Google Scholar

[12]

Cutler, M.M. Proving properties of simulation programs for system verification and validation. Proc., Summer Comptr Simulation Conf. Toronto, Canada, 1979, pp. 610-616.

Google Scholar

[13]

Cutler, M.M. A formal program model for discrete event simulations and its use in the mathematical verification and validation of system models and implementations. Ph.D. Th., UCLA, Calif., 1979.

Digital Library

Google Scholar

[14]

Deeter, C.R. and Hoffman, A.A.J. An Annotated Bibliography of Mathematical Models Classified by Validation and Error Analysis Methods. Texas Christian University, Fort Worth, TX 1978.

Google Scholar

[15]

De Millo, R.A., Lipton, R.J., Perlis, A.J. Social processes and proofs of theorems and programs. Comm. ACM, 22, 5, (May, 1979), pp. 271-280.

Digital Library

Google Scholar

[16]

Dickhoven, S. Software requirements for an improvement of transfer and adaptability of models. In Utility and Use of Large-Scale Mathematical Models, S. Gass (Ed.). Nat'l Bur Stand. Special Publication No. 534, U.S. Dept. of Commerce, Washington, D.C., May 1979, pp. 195-205.

Google Scholar

[17]

Elzas, M.S. Whither simulation? Proc., UKSC Conf. on Comptr Simulation, IPC Science and Technology Press, Chester, England, April 1978, pp. 494-501.

Google Scholar

[18]

Elzas, M.S. Results of a simulation: Can they be "trusted"? Proc. Seminar on Modelling in Business of IFIP Applied Information Processing Group, Amsterdam, The Netherlands, Jan. 1978, pp. 170- 183.

Google Scholar

[19]

Elzas, M.S. What is needed for robust simulation? In Methodology in Systems Modelling and Simulation, B.P. Zeigler et al. (Eds.) North-Holland, Amsterdam, 1979, pp. 57-91.

Google Scholar

[20]

Emshoff, J.R. and Sisson, R.L. Design and Use of Computer Simulation Models, Collier-MacMillan, New York, 1970.

Google Scholar

[21]

Gass, S.I. Evaluation of complex models. Comptrs and Oper. Res. 4. I (March, 1977), pp. 27-35.

Google Scholar

[22]

Gass, S.I. A procedure for the evaluation of complex models. Proc. First Int. Conf. in Mathematical Models, Univ. of Missouri, 1977, pp. 247-258,

Google Scholar

[23]

Gass, S.I. Computer model documentation: A review and an approach. Nat. Bur. Stand. Special Publication No. 500--39, U.S. Dept. of Commerce, Washington, D.C. Feb. 1979.

Google Scholar

[24]

Gass, S.I. (Ed.). Utility and use of large-scale mathematical models. Proc. of a Workshop held at the Nat'l. Bur. Stand., Gaithersburg, Maryland, Apr. 28-29, 1977, National Bureau of Standards, Special Publication 534, Washington, D.C., U.S. Dept. of Commerce, May 1979.

Google Scholar

[25]

Gass, S.I. Bibliography--Model evaluation and assessment. In Utility and Use of Large-Scale Mathematical Models, S.I. Gass (Ed.). Nat'l. Bur. Stand. Special Publication No. 534, U.S. Dept. of Commerce, Washington, D.C., May 1979, pp. 215-217.

Google Scholar

[26]

Gass, S.I. Validation and Assessment Issues of Energy Models. Prepared for the NATO Advanced Research Institute, The Application of Systems Science to Energy Policy Planning. Nov. 12- 16, Brookhaven National Laboratory, Upton, New York, 1979.

Google Scholar

[27]

Greenberger, M. and Richels, R. Assessing energy policy models: Current state and future directions. Ann. Rev. Energy, 4, (1979).

Google Scholar

[28]

Henize, J. Evaluating policy models. Proc. Summer Comptr Simulation Conf., Toronto, Canada, 1979, pp. 550-556.

Google Scholar

[29]

Holling, C.S. Adaptive Environmental Assessment and Management, John Wiley, New Yok, 1978.

Google Scholar

[30]

House, P.W. and McLeod, J. Large-Scale Models for Policy Evaluation, Wiley-Interscience, New York, 1977.

Google Scholar

[31]

Howden, W.E. Applicability of software validation techniques to scientific programs. A CM Trans. Programming Languages and Systems. 2, 3, (July 1980), pp. 307-320.

Digital Library

Google Scholar

[32]

Hunt, R. Large-scale systems theories: Some paradigms from software systems engineering. In Cyberne.tics and Modelling and Simulation of Large-Scale Systems. T.I. Oren (Ed.) Int. Assoc. for Cybernetics, Namur, Belgium, 1978, pp. 141-150.

Google Scholar

[33]

Kahne, S. Model credibility for large-scale systems. IEEE Trans. SMC, (Aug. 1976), pp. 586-590.

Google Scholar

[34]

Karplus, W.J. The spectrum of mathematical modelling and systems simulation. In Simulation of Systems, L. Dekker (Ed.) North- Holland, Amsterdam, 1976, pp. 5-13.

Google Scholar

[35]

Kheir, N.A. and W.M. Homes. On validating simulation models of missile systems. Simulation, 30, 4, (Apr. 1978), pp. 117-128.

Crossref

Google Scholar

[36]

Kleijnen, J.P.C. Statistical design and analysis of simulation experiments. Proc. Simulation '75, Ziirich, Switzerland Acta Press, 1975.

Google Scholar

[37]

Kleijnen, J.P.C. The role of statistical methodology in simulation. In Methodology in Systems Modelling and Simulation, B.P. Zeigler, M.S. Elzas, G.J. Klir, and T.I. Oren (Eds.) North-Holland, Amsterdam, 1979, pp. 425-445.

Google Scholar

[38]

Lee, D.B. Requiem for large-scale models. J. Am. Inst. of Planners, 39, 3 (May 1973), pp. 163-178.

Crossref

Google Scholar

[39]

Marmor-Squires, A.B. Software validation: An annotated bibliography. In Current Trends in Programming Methodology. Vol. II. Program Validation, R.T. Yeh (Ed.) Prentice-Hall, Englewood Cliffs, N.J., 1977, pp. 269-319.

Google Scholar

[40]

McLeod, J. Terms and definitions-'Play it Again, Stew'. Simulation Today, 29, 4 (Oct. 1977) pp. vii-ix.

Google Scholar

[41]

Mihram, G.A. Simulation--Statistical Foundations and Methodology. Academic Press, New York, 1972.

Google Scholar

[42]

Mihram, G.A. Some practical aspects of the verification and validation of simulation models. Operational Res. Quart., 23, (1972) pp. 17-29.

Crossref

Google Scholar

[43]

Mihram, G.A. Four questions regarding the credibility of simulation. Proc. 7th Ann. Pittsburgh Conf., Part 2-Modeling and Simulation, Pittsburgh, PA, Instrum. Soc. Am. Apr 1976, pp. 1225- 1230.

Google Scholar

[44]

Mihram, G.A., G. Innis, E.J. Mastascusa, S. Schlesinger, and T.J. Teorey. Bibliography on simular credibility. Simulation, 23, 5, (Dec. 1974) p. vi.

Google Scholar

[45]

Miller, E., and Howden, W.E. Tutorial: Software Testing and Validation Techniques. IEEE Comptr Soc., New York, NY, 1978.

Google Scholar

[46]

Myers, G.J. The Art of Software Testing. Wiley, New York, 1979.

Digital Library

Google Scholar

[47]

Nance, R.E. The feasibility of and methodology for developing federal documentation standards for simulation models. Rept. Dept. of Comptr Sci. VP1 and State University, Blacksburg, VA, 1977.

Google Scholar

[48]

Newton, O.L. and Weatherbee, J.E. Guidelines for documenting computer simulation models. Project Memorandum MV-068-060- USAF, Federal Computer Performance Evaluation and Simulation Center, Washington, DC, 1979.

Google Scholar

[49]

Newton, O.L. and Whetherbee, J.E. Guidelines for documenting simulation models: A review and procedures. In Simulation with Discrete Models: A State-of-the-Art View, T.I. Oren, C.M. Shub, and P.F. Roth (Eds.). IEEE, New York, 1980 pp. 243-258.

Google Scholar

[50]

Oren, T.I. Deductive general systems theories and simulation of large-scale systems. Proc., Summer Comptr Simulation Conf., Houston, Texas, July 1974 pp. 13-16.

Google Scholar

[51]

Oren, T.I. Simulation-as it has been, is, and should be. Simulation, 29, 5 (Nov. 1977) pp. 182-183.

Crossref

Google Scholar

[52]

Oren, T.I. Modelling, model manipulation and programming concepts in simulation. In Modelling, Identification, and Control in Environmental Systems, G.C. van Steenkiste (Ed.) North-Holland, Amsterdam, 1978 pp. 833-84 Z

Google Scholar

[53]

Oren, T.I. Rationale for large-scale systems simulation software based on cybernetics and general system., theories. In Cybernetics and Modelling of Large-Scale Systems, T.I. Oren (Ed.) Int. Assoc. for Cybe.rnetics, Namur, Belgium, 1978 pp. 151-179.

Google Scholar

[54]

Oren, T.I. Reference manual of GEST 78-Level 1. (A modelling and simulation language for combined systems). Tech. Rept. 78-02, Univ. of Ottawa, Comptr Sci. Dept., Ottawa, Ontario, Canada, 1978.

Google Scholar

[55]

Oren, T.I. Epilogue. In Cybernetics and Modelling of Large-Scale Systems. T.I. Oren (Ed.) Int. Assoc. for Cybernetics, Namur, Belgium, 1978, pp. 181-189.

Google Scholar

[56]

Oren, T.I. Concepts for advanced computer-assisted modelling. In Methodology in Systems Mod.elling and Simulation, B.P. Zeigler, M.S. Elzas, G.J. Klir, and T.I. Oren (Eds.). North-Holland, Amsterdam, 1979, pp. 29-55.

Google Scholar

[57]

Oren, T.I. Computer-aided modelling systems. In Progress in Modelling and Simulation F.E. Cellier (Ed.), Academic (London), Engl. and (In press).

Google Scholar

[58]

Oren, T.I. and Collie, B. Design of SEMA: A software system for computer-aided modelling and simulation of.SEquential MAchines. In Proc. 1980 Winter Simulation Conf., T.I. Oren, C.M. Shub, and P.F. Roth (Eds.), 1980, pp 113-123.

Digital Library

Google Scholar

[59]

Oren, T.I. and den Dulk, J. Ecological models expressed in GEST 78, Rept prepared for the Dept. of Theoretical Production Ecology, Dutch Agricultural Univ., Wageningen, the Netherlands, 1978.

Google Scholar

[60]

Oren, T.I. and Zeigler, B.P. Concepts for advanced simulation methodologies. Simulation, 32, 3 (March 1979) pp. 69-82.

Crossref

Google Scholar

[61]

O'Shaugnessy, J. Inquiry and Decisions. Allen & Unwin, London, 1972.

Google Scholar

[62]

Pugh, R.E. Evaluation of Policy Simulation Models. Information Resources Press, Washington, DC, 1977.

Digital Library

Google Scholar

[63]

Roth, P. F., Gass, S.I., and Lemoine, A.J. Some considerations for improving federal modelling. Proc. 1978 Winter Simulation Conf., Dec. 1978 pp. 213-217.

Digital Library

Google Scholar

[64]

Salaway, G. and Siler, K.F. Validation considerations during parameter development for simulation models. Proc., Summer Comptr Simulation Conf., Toronto, Canada, July 1979 pp. 624-628.

Google Scholar

[65]

Sargent, R.G. Validation of discrete-event simulation models. Proc. NSF Workshop on Validation of Mathematical Models in Energy Related Research and Development. Forth Worth, Texas, 1978.

Google Scholar

[66]

Sargent, R.G. Validation of simulation models. Proc., Winter Simulation Conf., Dec. 1979 pp. 497-503.

Digital Library

Google Scholar

[67]

Sargent, R.G. Verification and validation of simulation models. In Progress in Modelling and Simulation. F.E. Cellier (Ed.), Academic (London), England, (In Press).

Google Scholar

[68]

Saridis, G.N. Comparison of six on-line identification algorithms. Automatica, 10, 1 (Jan. 1974) pp. 69-79.

Digital Library

Google Scholar

[69]

Schellenberger, R.E. Criteria for assessing model validity for managerial purposes. Decision Science, 5, 4 (Oct. 1974) pp. 644-653.

Crossref

Google Scholar

[70]

Schlesinger, S., J.R. Buyan, E.D. Collender, W.K. Clarkson, and F.M. Perkins. Developing standard procedures for simulation validation and verification. Proc. Summer Comptr Simulation Conf., July 1974, pp. 927-933.

Google Scholar

[71]

Schlesinger, S. et al. Terminology for model credibility. Simulation, 32 3, (1979) pp. 103-104.

Google Scholar

[72]

Schruben, L.W. Establishing the credibility of simulations. Simulation,.34, 3 (March 1980) pp. 101-105.

Google Scholar

[73]

Teorey, T.J. Validation criteria for computer systems simulation. Proc. Symp. Simulation of Computer Systems, Boulder, Colorado, Nat'l Bur Stand, Aug. 1975, pp. 161-173.

Digital Library

Google Scholar

[74]

Thissen, W. Investigations into the Club of Rome's World 3 Model - Lessons for understanding complicated models. Ph.D. Th., Dept. of Technical Physics, Eindhoven University of Technology, The Netherlands, 1978.

Google Scholar

[75]

Thissen, W. Investigations into the World 3 Model: Lessons for understanding complicated models. IEEE Trans. on Systems, Man, and Cybernetics, SMC-8, 3 ( March 1978) pp. 183-193.

Google Scholar

[76]

Toffler, A. The Eco-spasm Report. Bantam Books, New York, 1975.

Google Scholar

[77]

U.S. Dep't Justice. Descriptions and assessments of the model evaluation program projects, Stock Number 27-000-00797-0, U.S. Govt Printing Office, Washington, DC., 1979.

Google Scholar

[78]

Waller, J.D., Scanlon, J.W., Kemp, D.M., and Nalley, P.G. Developing useful evaluation capability: Lessons from the model evaluation program, Stock Number 27-000-00798-8, U.S. Govt Printing Office, Washington, DC., 1979.

Google Scholar

[79]

Watt, K.F. Why won't anyone believe us? Simulation, 28 (Jan. 1977), pp. 1-3.

Crossref

Google Scholar

[80]

Wigan, M.R. The fitting, calibration, and validation of simulation models. Simulation, 18, 5, (May 1972) pp. 188-192.

Crossref

Google Scholar

[81]

Wong, C.S.Y. Criteria sensitivity analysis: A new approach to parameter sensitivity. Applied Mathematical Modelling. 4, (Feb. 1980) pp. 7-15.

Crossref

Google Scholar

[82]

Wright, R.D. Retrodictive tests of dynamic models. Proc. Summer Comptr Simulation Conf., Montreal, Canada, July 1973.

Google Scholar

[83]

Wymore, A.W. Systems Engineering Methodology for Interdisciplinary Teams. Wiley, New York, 1974.

Google Scholar

[84]

Yeh, R.T. (Ed.) Current Trends in Programming Methodoloy, Vol. ll--Program Validation. Prentice-Hall, Englewood Cliffs, N J, 1977.

Google Scholar

[85]

Zeigler, B.P. Theory of Modelling and Simulation. Wileylnterscience, New York, 1976.

Digital Library

Google Scholar

[86]

Zeigler, B.P. Structuring the Organization of Partial.Models. In Cybernetics and Modelling of Large-Scale Systems. T.1. Oren (Ed.). Int. Assoc. for Cybernetics, Namur, Belgium, 1978 pp. 127-139.

Google Scholar

Cited By

View all

Ören TGraciano Neto VDavis PZeigler B(2023)Reliability and Quality Assurance of M&SBody of Knowledge for Modeling and Simulation10.1007/978-3-031-11085-6_7(167-204)Online publication date: 28-Jan-2023
https://doi.org/10.1007/978-3-031-11085-6_7
van Schilt IKwakkel JVerbraeck AMense J(2022)Calibrating Simulation Models with Sparse DataProceedings of the Winter Simulation Conference10.5555/3586210.3586251(496-507)Online publication date: 11-Dec-2022
https://dl.acm.org/doi/10.5555/3586210.3586251
van Schilt IKwakkel JMense JVerbraeck A(2022)Calibrating Simulation Models with Sparse Data: Counterfeit Supply Chains During Covid-192022 Winter Simulation Conference (WSC)10.1109/WSC57314.2022.10015241(496-507)Online publication date: 11-Dec-2022
https://doi.org/10.1109/WSC57314.2022.10015241
Show More Cited By

Index Terms

Concepts and criteria to assess acceptability of simulation studies: a frame of reference
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Model verification and validation

Recommendations

Software Reliability Models: Assumptions, Limitations, and Applicability

A number of analytical models have been proposed during the past 15 years for assessing the reliability of a software system. In this paper we present an overview of the key modeling approaches, provide a critical analysis of the underlying assumptions, ...
Read More
A simulation and optimization based method for calibrating agent-based emergency department models under data scarcity
Highlights
- A method to calibrate an emergency department model with incomplete data.
- ...
Abstract
To tackle the problem of efficiently managing increasingly complex systems, simulation models have been widely used. This is because simulation is safer, less expensive, and faster than field implementation and experimenting. To ...
Read More
Planning and Certifying Software System Reliability

An approach to software reliability and certification is presented that is based on the use of three mathematical models: the sampling, component, and certification models. The approach helps reduce reliability analysis to a problem that can be ...
Read More

Comments

Information & Contributors

Information

Published In

Communications of the ACM Volume 24, Issue 4

Special issue on simulation modeling and statistical computing

April 1981

102 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/358598

Editors:
Robert L. Ashenhurst
The Univ. of Chicago, Chicago, IL
,
Nabil R. Adam
Rutgers Univ., Piscataway, NJ

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 1981

Published in CACM Volume 24, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

91
Total Citations
View Citations
891
Total Downloads

Downloads (Last 12 months)68
Downloads (Last 6 weeks)9

Other Metrics

View Author Metrics

Citations

Cited By

View all

Ören TGraciano Neto VDavis PZeigler B(2023)Reliability and Quality Assurance of M&SBody of Knowledge for Modeling and Simulation10.1007/978-3-031-11085-6_7(167-204)Online publication date: 28-Jan-2023
https://doi.org/10.1007/978-3-031-11085-6_7
van Schilt IKwakkel JVerbraeck AMense J(2022)Calibrating Simulation Models with Sparse DataProceedings of the Winter Simulation Conference10.5555/3586210.3586251(496-507)Online publication date: 11-Dec-2022
https://dl.acm.org/doi/10.5555/3586210.3586251
van Schilt IKwakkel JMense JVerbraeck A(2022)Calibrating Simulation Models with Sparse Data: Counterfeit Supply Chains During Covid-192022 Winter Simulation Conference (WSC)10.1109/WSC57314.2022.10015241(496-507)Online publication date: 11-Dec-2022
https://doi.org/10.1109/WSC57314.2022.10015241
Ören T(2022)Security of Cyber-Physical-Social Systems: Impact of Simulation-Based Systems Engineering, Artificial Intelligence, Human Involvement, and EthicsAdvances in Computing, Informatics, Networking and Cybersecurity10.1007/978-3-030-87049-2_26(711-732)Online publication date: 3-Mar-2022
https://doi.org/10.1007/978-3-030-87049-2_26
de Groot LHübl A(2021)Developing a calibrated discrete event simulation model of shops of a Dutch phone and subscription retailer during COVID-19 to evaluate shift plans to reduce waiting timesProceedings of the Winter Simulation Conference10.5555/3522802.3522894(1-12)Online publication date: 13-Dec-2021
https://dl.acm.org/doi/10.5555/3522802.3522894
de Groot LHubl A(2021)Developing a Calibrated Discrete Event Simulation Model of Shops of a Dutch Phone and Subscription Retailer During COVID-19 to Evaluate Shift Plans to Reduce Waiting Times2021 Winter Simulation Conference (WSC)10.1109/WSC52266.2021.9715306(1-12)Online publication date: 12-Dec-2021
https://doi.org/10.1109/WSC52266.2021.9715306
McLaughlin MSarjoughian H(2020)DEVS-scriptingProceedings of the Winter Simulation Conference10.5555/3466184.3466435(2196-2207)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466435
Vendome CRao DGiabbanelli PDel Barrio ABarros FHu XKavak H(2020)How do modelers code artificial societies?Proceedings of the 2020 Spring Simulation Conference10.5555/3408207.3408257(1-12)Online publication date: 19-May-2020
https://dl.acm.org/doi/10.5555/3408207.3408257
McLaughlin MSarjoughian H(2020)DEVS-scripting: A Black-Box Test Frame for Devs Models2020 Winter Simulation Conference (WSC)10.1109/WSC48552.2020.9384024(2196-2207)Online publication date: 14-Dec-2020
https://doi.org/10.1109/WSC48552.2020.9384024
Landwehr MTrott MViebahn C(2020)Computer Simulation as Evaluation Tool of Information Systems: Identifying Quality Factors of Simulation Modeling2020 IEEE 22nd Conference on Business Informatics (CBI)10.1109/CBI49978.2020.00030(211-220)Online publication date: Jun-2020
https://doi.org/10.1109/CBI49978.2020.00030
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

References

Cited By

Index Terms

Recommendations

Software Reliability Models: Assumptions, Limitations, and Applicability

A simulation and optimization based method for calibrating agent-based emergency department models under data scarcity

Planning and Certifying Software System Reliability

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

PDF

eReader

Get Access

Login options

Full Access

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations