approximations
Time and time again, the software industry struggles to come up with accurate estimates for software development projects, releases, or sprints. Lack of understanding of the performance of development teams in combination with low maturity estimation processes, often result in overly optimistic project estimates that are highly probable to result in failing projects and severe cost and schedule overruns.
A case study of an Agile project. Learn how estimations of: effort, costs of and testing requirements, were produced in a tight timeframe.
This case study describes a validation estimates model based on COSMIC sizing. The model uses a density function to help define validation criteria.
Estimating the effort required to develop software is known as software effort estimation (SEE). The support vector regression (SVR), a machine learning algorithm, has been successfully used for effort estimation of cross company (CC) data sets.
Exploration of cost estimation in the information technology (IT) industry.
This detailed statistical and mathematical study examines the factors that influence productivity and work efficiency . A cost validity model is then proposed to evaluate the proposed cost.
Select the most appropriate ISBSG (International Software Benchmarking Standards Group) data, for use in Software Development Effort Estimation.
A presentation, in Spanish, examining the relationship between software project size, effort and duration.
A discussion of: the key points when undertaking a modernization project and the use of Open Source and the costing of Cloud-based solutions.
A large proportion of software projects are delivered over-budget and behind time. Accurate project estimations are needed to overcome this issue.
