The increase in software size and complexity in automotive and industrial domains not only leads to the improvement of new functionality but also to an increase in the defect rate. Defect rate is a measure of the relative number of units that are defective per release. This affects the quality and has a strong influence on the business. This will strongly influence the product costs for the development of a high-quality product. Automotive products have a long lifecycle compared to the development lifecycle, which explains the development efforts put into such fail-safe products. One of the important boundaries for an industrial project is the budget, where changes to any project parameters can easily lead to negative effects on the planned budget. Such changes are classified into two types: the changes pushed by the customer as new requirements or changed requirements, and the correction changes in the project because of improvements of the system and identified bugs with their fixes. This classification is important to control the project budget. The effort for the realization of new customer changes can be estimated and added to the budget. The correction changes also cause huge efforts, which can lead to a negative budget in the project, which is a big challenge for the project management and the automated calculation of effort estimations for the complete development lifecycle. This study offers a new model to improve the effort estimation from multiple perspectives. The newly developed model was successfully evaluated in the automotive domain. The overall accuracy of the effort estimations was improved by 80%.
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