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Agile Software Engineering Performance Evaluation A Statistical Analysis of Team Productivity, Requirement Satisfaction, and Delivery Effectiveness Using SPSS

Rajendar Dommeti

2026International Journal of Agile Software Engineering8 citationsDOIOpen Access PDF

Abstract

Through quantitative statistical analysis, the study examines five key performance metrics: team productivity, requirements fulfillment, on-time delivery, code quality, and effective in adhering to agile methodologies. Through quantitative statistical analysis, this study examines five key performance metrics team productivity requirement fulfillment ,on time delivery, code quality and efficiency in adhering to agile methologies. Utilizing SPSS-based reliability and descriptive analysis conducted on a sample of ten respondent, this study demonstrate that these five performance constructs reliably measure the single underlying dimension that determine the success of agile engineering. Pearson correlation analysis revealed strong positive correlation among these variable (Rvalues ranging from 0.885 to 1.000, p<0.005).This confirm that improvement in one dimension of agile performance are closely correlated with advancement in its other dimensions. Keyword: Agile Methodology, scrum, Sprint Planning, Continuous Delivery, Software Quality Assurance

Topics & Concepts

Agile software developmentComputer scienceReliability (semiconductor)Key (lock)Statistical analysisSample (material)Quality (philosophy)SoftwareSample size determinationPearson product-moment correlation coefficientDimension (graph theory)SprintEngineeringMeasure (data warehouse)Software qualityProductivityPerformance indicatorReliability engineeringRelation (database)Extreme programming practicesCode (set theory)Descriptive statisticsSoftware engineeringScrumAgile manufacturingQuality managementQuantitative analysis (chemistry)Software Engineering Techniques and PracticesOrganizational and Employee PerformanceInternet of Things and AI