Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Improving Software Effort Estimation Using an Expert-centred Approach
Blekinge Institute of Technology, School of Computing.
2012 (English)In: Lecture Notes in Computer Science, Springer , 2012, Vol. 7623, 18-33 p.Conference paper (Refereed) Published
Abstract [en]

A cornerstone of software project management is effort estimation, the process by which effort is forecasted and used as basis to predict costs and allocate resources effectively, so enabling projects to be delivered on time and within budget. Effort estimation is a very complex domain where the relationship between factors is non-deterministic and has an inherently uncertain nature, and where corresponding decisions and predictions require reasoning with uncertainty. Most studies in this field, however, have to date investigated ways to improve software effort estimation by proposing and comparing techniques to build effort prediction models where such models are built solely from data on past software projects - data-driven models. The drawback with such approach is threefold: first, it ignores the explicit inclusion of uncertainty, which is inherent to the effort estimation domain, into such models; second, it ignores the explicit representation of causal relationships between factors; third, it relies solely on the variables being part of the dataset used for model building, under the assumption that those variables represent the fundamental factors within the context of software effort prediction. Recently, as part of a New Zealand and later on Brazilian government-funded projects, we investigated the use of an expert-centred approach in combination with a technique that enables the explicit inclusion of uncertainty and causal relationships as means to improve software effort estimation. This paper will first provide an overview of the effort estimation process, followed by the discussion of how an expert-centred approach to improving such process can be advantageous to software companies. In addition, we also detail our experience building and validating six different expert-based effort estimation models for ICT companies in New Zealand and Brazil. Post-mortem interviews with the participating companies showed that they found the entire process extremely beneficial and worthwhile, and that all the models created remained in use by those companies. Finally, the methodology focus of this paper, which focuses on expert knowledge elicitation and participation, can be employed not only to improve a software effort estimation process, but also to improve other project management-related activities.

Place, publisher, year, edition, pages
Springer , 2012. Vol. 7623, 18-33 p.
Keyword [en]
Cost Estimation, Expert-centred Approach, Process Improvement, Project Management, Software Effort Estimation
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-7133DOI: 10.1007/978-3-642-34347-6_2Local ID: oai:bth.se:forskinfo162E3A128268828DC1257AC90034188EOAI: oai:DiVA.org:bth-7133DiVA: diva2:834715
Conference
4th International Conference on Human-Centered Software Engineering, HCSE
Available from: 2012-12-03 Created: 2012-12-03 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Mendes, Emilia
By organisation
School of Computing
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 4 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf