Measuring Software Process: A Systematic Mapping Study
García García, Julián Alberto
Ramos Román, Isabel
Escalona Cuaresma, María José
|Department||Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos|
|Published in||ACM Computing Surveys, 51 (3), 58-1-58-32.|
|Abstract||Context: Measurement is essential to reach predictable performance and high capability processes. It provides
support for better understanding, evaluation, management, and control of the development process
and project, ...
Context: Measurement is essential to reach predictable performance and high capability processes. It provides support for better understanding, evaluation, management, and control of the development process and project, as well as the resulting product. It also enables organizations to improve and predict its process’s performance, which places organizations in better positions to make appropriate decisions. Objective: This study aims to understand the measurement of the software development process, to identify studies, create a classification scheme based on the identified studies, and then to map such studies into the scheme to answer the research questions. Method: Systematic mapping is the selected research methodology for this study. Results: A total of 462 studies are included and classified into four topics with respect to their focus and into three groups based on the publishing date. Five abstractions and 64 attributes were identified, 25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the most measured process attributes, while effort and performance were the most measured project attributes. Goal Question Metric and Capability Maturity Model Integration were the main methods and models used in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently identified research contexts.
|Cite||Meidan, A., García García, J.A., Ramos Román, I. y Escalona Cuaresma, M.J. (2018). Measuring Software Process: A Systematic Mapping Study. ACM Computing Surveys, 51 (3), 58-1-58-32.|
Editor´s version: https://dl.acm.org/citation.cfm?doid=3212709.3186888