EEF-CAS: An Effort Estimation Framework with Customizable Attribute Selection

摘要: Existing estimation frameworks generally provide one-size-fits-all solutions that fail to produce accurate estimates in most environments. Research has shown the accomplishment of effort is a long-term process that, above all, requires extensive collection data by each organization. Collected characterized set attributes are believed affect development effort. The vary widely depending on type product being developed and environment which it developed. Thus, any new framework must offer flexibility customizable attribute selection. Moreover, such could ability incorporate empirical evidence expert judgment into framework. Finally, because software virtual therefore intangible, important metrics notorious for subjective according experience estimator. Consequently, measurement inference system robust subjectivity uncertainty be place. Effort Estimation Framework with Customizable Attribute Selection (EEF-CAS) presented this paper been designed requirements mind. It accompanied four preparation steps allow organization implementing establish an process. This facilitates collection, customization organization’s needs, its calibration data, capability continual improvement. proposed described was validated real