Software engineering: methods and management
Software engineering: methods and management
An experimental study of individual subjective effort estimation and combinations of the estimates
Proceedings of the 20th international conference on Software engineering
Components of Software Development Risk: How to Address Them? A Project Manager Survey
IEEE Transactions on Software Engineering
Software Metrics: A Rigorous and Practical Approach
Software Metrics: A Rigorous and Practical Approach
Software Engineering Economics
Software Engineering Economics
Benchmarking Kappa: Interrater Agreement in Software ProcessAssessments
Empirical Software Engineering
SEL's Software Process Improvement Program
IEEE Software
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Practical Statistics for Medical Research
Practical Statistics for Medical Research
Analysing primary and lower order project success drivers
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Component Certification - What is the Value?
PROFES '02 Proceedings of the 4th International Conference on Product Focused Software Process Improvement
Empirical Software Engineering
Trade-off Analysis in Web Development
3-WoSQ Proceedings of the third workshop on Software quality
Measuring where it matters: Determining starting points for metrics collection
Journal of Systems and Software
Evaluating logistic regression models to estimate software project outcomes
Information and Software Technology
Evaluation of three methods to predict project success: a case study
PROFES'05 Proceedings of the 6th international conference on Product Focused Software Process Improvement
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Project evaluation is essential to understand and assess the key aspects of a project that make it either a success or failure. The latter is influenced by a large number of factors, and many times it is hard to measure them objectively. This paper addresses this by introducing a new method for identifying and assessing key project characteristics, which are crucial for a project's success. The method consists of a number of well-defined steps, which are described in detail. The method is applied to two case studies from different application domains and continents. It is concluded that patterns are possible to detect from the data sets. Further, the analysis of the two data sets shows that the proposed method using subjective factors is useful, since it provides an increased understanding, insight and assessment of which project factors might affect project success.