Design and implementation of an Intelligent Cost Estimation Model for Decision Support System software

Abstract

Recently, Decision Support Systems (DSS) have increased in importance and usage. However, these increases have not carried over into developing better models to estimate the real cost of developing the DSS. This thesis explores various estimation methods that seem pertinent to DSS. It advocates the use of a combination of modeling tools particularly tailored to the users' environment. An Intelligent Cost Estimation Model (ICEM) for Decision Support System software is proposed. To promote user-friendliness, ICEM uses a rule based front end interface coupled to a spreadsheet program. For comparison purposes the current version of ICEM includes the Intermediate COCOMO model, the Intermediate COCOMO model particularly calibrated for the in-house DSS development environment, and a parametric model which incorporates the function point size metric.