Estimating the cost and schedule of agile software projects is critical at an early phase to establish baseline budgets and schedules for the selection of competitive bidders. The challenge is that common agile sizing measures such as story points and user stories are not practical for early estimation as these are often reported after contract award in DoD. This study provides a set of effort and schedule estimation models for agile projects using a sizing measure that is available before proposal evaluation based on data from 36 DoD agile projects. The results suggest that initial software requirements, defined as the sum of functions and external interfaces, is an effective sizing measure for early estimation of effort and schedule of agile projects. The models’ accuracy improves when application domain groups and peak staff are added as inputs.

Background: Software effort estimates are necessary and critical at an early phase for decision makers to establish initial budgets, and in a government context to select the most competitive bidder for a contract. The challenge is that estimated software requirements is the only size information available at this stage, compounded with the newly increasing adoption of agile processes in the US DoD. Aims: The objectives are to improve cost estimation by investigating available sizing measures, and providing practical effort estimation models for agile software development projects during the contract bidding phase or earlier. Method: The analysis explores the effects of independent variables for product size, peak staff, and domain on effort. The empirical data for model calibration is from 20 industrial projects completed recently for the US DoD, among a larger dataset of recent projects using other lifecycle processes. Results: Statistical results showed that initial software requirements is a valid size metric for estimating agile software development effort. Prediction accuracy improves when peak staff and domain are added as inputs to the cost models. Conclusion: These models may be used for estimates of agile projects, and evaluating software development contract cost proposals with inputs available during the bidding phase or earlier.

Context: An effort estimation model with more than 20 parameters is not very useful at early conceptual phase if you don't have a logical approach for specifying the input values.

Enterprise Resource Planning (ERP) projects are considered commercial-off-the-shelf (COTS) solutions where one substantial COTS product (e.g. Oracle, SAP) is tailored to provide automated business functions. This paper presents effort and schedule estimating models for predicting ERP implementation. The first two models use product size to predict software development effort. Product size is measured in terms of the number of report, interface, conversion, and extension (RICE) objects that are tailored or modified in the COTS product suite. The third model predicts the duration of software development phase as a function of RICE objects and full time equivalent staff. These statistical models are based on empirical data collected from 22 programs implemented within the federal government over the course of ten years beginning in 2001. Result shows that number of RICE objects is a good predictor of ERP software development effort and duration.

The article of record as published may be found at http://dx.doi.org/10.1109/ESEM.2011.56