Estimating the implementation time for discrete-event simulation model building

There are several techniques for estimating cost and time for software development. These are known in software engineering as "software metrics." LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Eve...

Full description

Saved in:
Bibliographic Details
Main Authors: Chwif, L, Banks, J, Barretto, M R P
Format: Conference Proceeding
Language:English
Subjects:
Complexity theory
Lifting equipment
Productivity
Programming
Software
Software metrics
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 1785
container_issue
container_start_page 1774
container_title
container_volume
creator Chwif, L
Banks, J
Barretto, M R P
description There are several techniques for estimating cost and time for software development. These are known in software engineering as "software metrics." LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical software development, it is possible to draw a parallel between these techniques and DESM. This article reviews some of the metrics from software engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects showed that the proposed technique can estimate the time for software development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects.
doi_str_mv 10.1109/WSC.2010.5678891
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5678891</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5678891</ieee_id><sourcerecordid>5678891</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-4eb37a937f0052043b7beb3904ba0f794c21c40c8ed273063da4fac0806fb92e3</originalsourceid><addsrcrecordid>eNo1kEtLAzEUheMLbGv3gpv8gdSbd7KUoT6g0IWKy5LM3NHIPMrMVPDfG2hdHe75DgfOJeSWw4pz8Pcfr8VKQL60sc55fkbmXAmlvDOan5MZ19oxJUFfkKW37p8Zc0lmkPPMWmmuyXwcvwG401zMyHY9TqkNU-o-6fSFNLX7Blvspmz1Hc0Mad0PtEpjOeCEDH8ypGNqD80x0vYVNjQeUlPlkhtyVYdmxOVJF-T9cf1WPLPN9umleNiwxK2emMIobfDS1gBagJLRxmx5UDFAbb0qBS8VlA4rYSUYWQVVhxIcmDp6gXJB7o69CRF3-yFvGH53p8fIPy6bU7s</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Estimating the implementation time for discrete-event simulation model building</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Chwif, L ; Banks, J ; Barretto, M R P</creator><creatorcontrib>Chwif, L ; Banks, J ; Barretto, M R P</creatorcontrib><description>There are several techniques for estimating cost and time for software development. These are known in software engineering as "software metrics." LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical software development, it is possible to draw a parallel between these techniques and DESM. This article reviews some of the metrics from software engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects showed that the proposed technique can estimate the time for software development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects.</description><identifier>ISSN: 0891-7736</identifier><identifier>ISBN: 9781424498666</identifier><identifier>ISBN: 142449866X</identifier><identifier>EISSN: 1558-4305</identifier><identifier>EISBN: 1424498651</identifier><identifier>EISBN: 1424498643</identifier><identifier>EISBN: 9781424498642</identifier><identifier>EISBN: 9781424498659</identifier><identifier>DOI: 10.1109/WSC.2010.5678891</identifier><language>eng</language><publisher>IEEE</publisher><subject>Complexity theory ; Lifting equipment ; Productivity ; Programming ; Software ; Software metrics</subject><ispartof>Proceedings of the 2010 Winter Simulation Conference, 2010, p.1774-1785</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5678891$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,2052,27906,54536,54901,54913</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5678891$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chwif, L</creatorcontrib><creatorcontrib>Banks, J</creatorcontrib><creatorcontrib>Barretto, M R P</creatorcontrib><title>Estimating the implementation time for discrete-event simulation model building</title><title>Proceedings of the 2010 Winter Simulation Conference</title><addtitle>WSC</addtitle><description>There are several techniques for estimating cost and time for software development. These are known in software engineering as "software metrics." LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical software development, it is possible to draw a parallel between these techniques and DESM. This article reviews some of the metrics from software engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects showed that the proposed technique can estimate the time for software development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects.</description><subject>Complexity theory</subject><subject>Lifting equipment</subject><subject>Productivity</subject><subject>Programming</subject><subject>Software</subject><subject>Software metrics</subject><issn>0891-7736</issn><issn>1558-4305</issn><isbn>9781424498666</isbn><isbn>142449866X</isbn><isbn>1424498651</isbn><isbn>1424498643</isbn><isbn>9781424498642</isbn><isbn>9781424498659</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kEtLAzEUheMLbGv3gpv8gdSbd7KUoT6g0IWKy5LM3NHIPMrMVPDfG2hdHe75DgfOJeSWw4pz8Pcfr8VKQL60sc55fkbmXAmlvDOan5MZ19oxJUFfkKW37p8Zc0lmkPPMWmmuyXwcvwG401zMyHY9TqkNU-o-6fSFNLX7Blvspmz1Hc0Mad0PtEpjOeCEDH8ypGNqD80x0vYVNjQeUlPlkhtyVYdmxOVJF-T9cf1WPLPN9umleNiwxK2emMIobfDS1gBagJLRxmx5UDFAbb0qBS8VlA4rYSUYWQVVhxIcmDp6gXJB7o69CRF3-yFvGH53p8fIPy6bU7s</recordid><startdate>201012</startdate><enddate>201012</enddate><creator>Chwif, L</creator><creator>Banks, J</creator><creator>Barretto, M R P</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201012</creationdate><title>Estimating the implementation time for discrete-event simulation model building</title><author>Chwif, L ; Banks, J ; Barretto, M R P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-4eb37a937f0052043b7beb3904ba0f794c21c40c8ed273063da4fac0806fb92e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Complexity theory</topic><topic>Lifting equipment</topic><topic>Productivity</topic><topic>Programming</topic><topic>Software</topic><topic>Software metrics</topic><toplevel>online_resources</toplevel><creatorcontrib>Chwif, L</creatorcontrib><creatorcontrib>Banks, J</creatorcontrib><creatorcontrib>Barretto, M R P</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chwif, L</au><au>Banks, J</au><au>Barretto, M R P</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Estimating the implementation time for discrete-event simulation model building</atitle><btitle>Proceedings of the 2010 Winter Simulation Conference</btitle><stitle>WSC</stitle><date>2010-12</date><risdate>2010</risdate><spage>1774</spage><epage>1785</epage><pages>1774-1785</pages><issn>0891-7736</issn><eissn>1558-4305</eissn><isbn>9781424498666</isbn><isbn>142449866X</isbn><eisbn>1424498651</eisbn><eisbn>1424498643</eisbn><eisbn>9781424498642</eisbn><eisbn>9781424498659</eisbn><abstract>There are several techniques for estimating cost and time for software development. These are known in software engineering as "software metrics." LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical software development, it is possible to draw a parallel between these techniques and DESM. This article reviews some of the metrics from software engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects showed that the proposed technique can estimate the time for software development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects.</abstract><pub>IEEE</pub><doi>10.1109/WSC.2010.5678891</doi><tpages>12</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0891-7736
ispartof Proceedings of the 2010 Winter Simulation Conference, 2010, p.1774-1785
issn 0891-7736
1558-4305
language eng
recordid cdi_ieee_primary_5678891
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Complexity theory
Lifting equipment
Productivity
Programming
Software
Software metrics
title Estimating the implementation time for discrete-event simulation model building
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T12%3A00%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Estimating%20the%20implementation%20time%20for%20discrete-event%20simulation%20model%20building&rft.btitle=Proceedings%20of%20the%202010%20Winter%20Simulation%20Conference&rft.au=Chwif,%20L&rft.date=2010-12&rft.spage=1774&rft.epage=1785&rft.pages=1774-1785&rft.issn=0891-7736&rft.eissn=1558-4305&rft.isbn=9781424498666&rft.isbn_list=142449866X&rft_id=info:doi/10.1109/WSC.2010.5678891&rft.eisbn=1424498651&rft.eisbn_list=1424498643&rft.eisbn_list=9781424498642&rft.eisbn_list=9781424498659&rft_dat=%3Cieee_6IE%3E5678891%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-4eb37a937f0052043b7beb3904ba0f794c21c40c8ed273063da4fac0806fb92e3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5678891&rfr_iscdi=true