| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | mtc-m16b.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 6qtX3pFwXQZGivnK2Y/QzHHb |
| Repository | sid.inpe.br/mtc-m17@80/2007/06.27.17.46 (restricted access) |
| Last Update | 2008:06.25.17.57.13 (UTC) administrator |
| Metadata Repository | sid.inpe.br/mtc-m17@80/2007/06.27.17.46.46 |
| Metadata Last Update | 2018:06.05.03.30.25 (UTC) administrator |
| Secondary Key | INPE--PRE/ |
| DOI | 10.1016/j.jss.2007.05.011 |
| ISSN | 0164-1212 |
| Citation Key | TrontoSilvSant:2008:InArNe |
| Title | An investigation of artificial neural networks based prediction systems in software project management  |
| Year | 2008 |
| Month | Mar. |
| Access Date | 2024, May 05 |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 266 KiB |
| 2. Context | |
| Author | 1 Tronto, Iris Fabiana de Barcelos 2 Silva, José Demísio Simões da 3 Sant'Anna, Nilson |
| Group | 1 LAC-CTE-INPE-MCT-BR 2 LAC-CTE-INPE-MCT-BR 3 LAC-CTE-INPE-MCT-BR |
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Journal | Journal of Systems and Software |
| Volume | 81 |
| Number | 3 |
| Pages | 356-367 |
| History (UTC) | 2008-12-15 12:47:15 :: simone -> administrator :: 2012-07-13 22:22:57 :: administrator -> simone :: 2013-02-20 15:20:00 :: simone -> administrator :: 2008 2018-06-05 03:30:25 :: administrator -> marciana :: 2008 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Keywords | software effort estimation predictive accuracy artificial neural networks linear regression data mining |
| Abstract | A critical issue in software project management is the accurate estimation of size, effort, resources, cost, and time spent in the development process. Underestimates may lead to time pressures that may compromise full functional development and the software testing process. Likewise, overestimates can result in noncompetitive budgets. In this paper, artificial neural network and stepwise regression based predictive models are investigated, aiming at offering alternative methods for those who do not believe in estimation models. The results presented in this paper compare the performance of both methods and indicate that these techniques are competitive with the APF, SLIM, and COCOMO methods. |
| Area | COMP |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > An investigation of... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| Target File | an investigation.pdf |
| User Group | administrator simone |
| Visibility | shown |
| Archiving Policy | denypublisher denyfinaldraft24 |
| Read Permission | deny from all and allow from 150.163 |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/3ESGTTP |
| Dissemination | WEBSCI; PORTALCAPES; COMPENDEX. |
| Host Collection | lcp.inpe.br/ignes/2004/02.12.18.39 cptec.inpe.br/walmeida/2003/04.25.17.12 |
| 6. Notes | |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel documentstage e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url versiontype |
| 7. Description control | |
| e-Mail (login) | marciana |
| update | |