One of the most important and valuable goal of software development life cycle is software cost estimation or SCE. During the recent years, SCE has attracted the attention of researchers due to huge amount of software project requests. There have been proposed so many models using heuristic and meta-heuristic algorithms to do machine learning process for SCE. COCOMO81 is one of the most popular...

Defect prediction can be a powerful tool to guide the use of quality assurance resources. However, while lots research covered methods for defect as well methodological aspects research, actual cost saving potential is still unclear. Within this article, we close gap and formulate model software prediction. We derive mathematically provable boundary conditions that must fulfilled by models such...

Size related measures have traditionally been the basis for effort estimation models to predict costs of software activities along the entire software product life cycle. Object-Oriented (OO) systems are developed and evolve by adding/removing new classes and modifying existing entities. We propose an approach to predict the size of changes of evolving OO systems based on the analysis of the cl...

The ability to generate sufficiently accurate effort estimates can be seen as a key success factor for multiorganizational projects focusing on the development of large and critical software systems. This is caused, for instance, by the need for synchronizing multiple development and verification and validation processes. Paradoxically, effort predictions in the critical software systems domain...

farm machinery managers often need to make complex economic decisions on machinery replacement. repair and maintenance costs can have significant impacts on this economic decision. the farm manager must be able to predict farm machinery repair and maintenance costs. this study aimed to identify a regression model that can adequately represent the repair and maintenance costs in terms of machine...

Reliable effort and cost estimation remains to be a challenging issue even for mature software organizations. Although, these organizations collect historical data to base their future estimates, changes in circumstances (such as application type, development platform, etc.) prevent their successful utilization. As a result, companies often suffer from underestimated and unrealistic schedules. ...