Quality software management: volume 4: anticipating change
Quality software management: volume 4: anticipating change
Conceptual simplicity meets organizational complexity: case study of a corporate metrics program
Proceedings of the 20th international conference on Software engineering
Qualitative Methods in Empirical Studies of Software Engineering
IEEE Transactions on Software Engineering
Proceedings of the Conference on The Future of Software Engineering
An empirical study on the utility of formal routines to transfer knowledge and experience
Proceedings of the 8th European software engineering conference held jointly with 9th ACM SIGSOFT international symposium on Foundations of software engineering
Lessons Learned in Building a Corporate Metrics Program
IEEE Software
Implementing Effective Software Metrics Programs
IEEE Software
Measurement Programs in Software Development: Determinants of Success
IEEE Transactions on Software Engineering
Lessons from Implementing a Software Metrics Program
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 7 - Volume 7
De-motivators for software process improvement: an analysis of practitioners' views
Journal of Systems and Software
Acceptance Issues in Metrics Program Implementation
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
Why do programmers avoid metrics?
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
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Metrics efforts are often impeded by factors such as poor data quality and developer resistance. To better understand and thus to address the developer perspective in a metrics program we undertook a case study at a large multi-national corporation. We identified six projects, and conducted surveys of both project managers and developers. These surveys were based on the Metrics Acceptance Model (MAM) which is a framework (i.e. a model of relationships between factors, operationalized by a survey instrument) for gauging developer opinions toward software metrics. We noticed some interesting differences between developers' and managers' perceptions of metrics. While managers were on the same page as developers when it came to factors such as ease of use of the metrics tool, they over-estimated developers' confidence to report accurate measures. Managers under-estimated developers' beliefs about the usefulness of metrics and about their fear of adverse consequences. These findings suggest that the MAM could provide useful insights to project managers to train and motivate their developers. We also found that the MAM can be an effective diagnostic tool both at an organizational and project level to identify potential impediments in metrics programs.