AGILE ESTIMATIONS: EMPIRICAL STUDY USING WEIGHTED COMPLEXITY FACTORS

Abstract

Software time and cost estimates are always challenging due to the quickly changing software process. Especially Agile project estimations are complex, and the story points differ from person to person. Due to the person-to-person variations, project managers have difficulty arriving at the project cost for development projects with different sizes or complexity of systems/software. This paper proposes a new estimation model named the WEighted COmplexity Factor Estimation (WECOFE) Model to reduce the complexities of Agile story point estimations. Weighted complexities factors identify Low, Moderate, and High Project Level Factors and Story Level Factors. For each level, multiple factors were defined. Derived Weighted complexity based on Project, Requirement, and Resource Level factors. Each story's point estimation is explained based on weighted complexity defined and assigned factors values. Conducted study on various industry projects, showing that the WECOFE approach is promising by observing the Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE). Also, performed a t-test for one sprint project with 51 stories, and paired sample means are equal for WECOFE with actual story points spent by the team.