Software factories seek to develop quality software in a manner comparable to the production of other industrial products, establishing improvements in their production process so as to be more competitive. Productivity, one of the competitiveness pillars, is related to the effort required to fulfill assigned tasks. However, there is no standard way of measuring productivity, making it difficult to establish policies and strategies to improve the factory. In this article, the authors perform a systematic review of the literature on factors affecting productivity of software factories, and models for measuring it. For the period 2005-2017, 74 factors and 10 models are identified. Most of the factors are related to Programming, and a few to Analysis and Design and Testing. Also, most models for measuring productivity only consider activities concerning programming.
Software factories seek to develop quality software in a manner comparable to the production of other industrial products, establishing improvements in their production process so as to be more competitive. Productivity, one of the competitiveness pillars, is related to the effort required to fulfill assigned tasks. However, there is no standard way of measuring productivity, making it difficult to establish policies and strategies to improve the factory. In this article, the authors perform a systematic review of the literature on factors affecting productivity of software factories, and models for measuring it. For the period 2005-2017, 74 factors and 10 models are identified. Most of the factors are related to Programming, and a few to Analysis and Design and Testing. Also, most models for measuring productivity only consider activities concerning programming.
Productivity is very important because it allows organizations to achieve greater efficiency and effectiveness in their activities; however, it is affected by numerous factors. While these factors have been identified for over two decades, all of the previous works limited the software factory to the programming work unit and did not analyze other work units that are also relevant. 90% of a software factory's effort is absorbed by the software production component, 85% of which is concentrated in the efforts of the analysis and design, programming, and testing work units. The present work identifies three new factors that influence the software factory, demonstrating that the use of rules and events influences analysis & design, team heterogeneity negatively affects analysis and design and positively affects programming; and the osmotic communication affects programming. An empirical study on software factories in Peru, determined that 95% of the influence came from these factors, which corroborated as well that team size and trust within the team influences in software production.
El Modelo de Aceptación Tecnológica (TAM) es un modelo que es utilizado por muchos investigadores con el fin de analizar la aceptación tecnológica que permita garantizar el éxito de su implementación. El modelo TAM ha logrado posicionarse como uno de los modelos más utilizados, para probar y validar entre los modelos existentes para la aceptación tecnológica. El principal objetivo de esta investigación es analizar la adopción del Sistema de Gestión Documental (SGD) que utiliza tecnología de Firma Digital en las entidades públicas peruanas, incorporando al modelo TAM dos constructos importantes: la confianza y el riesgo percibido. Los diversos estudios demuestran que la capacidad predictiva de estos constructos psicológicos influye de manera positiva en concordancia con los constructos del modelo TAM. Las conclusiones de la presente investigación pueden permitir mejorar el servicio al ciudadano, el cual aportará de manera positiva a las decisiones de los gestores de la administración pública, académicos, docentes e investigadores en este entorno.
Productivity is very important because it allows organizations to achieve greater efficiency and effectiveness in their activities; however, it is affected by numerous factors. While these factors have been identified for over two decades, all of the previous works limited the software factory to the programming work unit and did not analyze other work units that are also relevant. 90% of a software factory's effort is absorbed by the software production component, 85% of which is concentrated in the efforts of the analysis and design, programming, and testing work units. The present work identifies three new factors that influence the software factory, demonstrating that the use of rules and events influences analysis & design, team heterogeneity negatively affects analysis and design and positively affects programming; and the osmotic communication affects programming. An empirical study on software factories in Peru, determined that 95% of the influence came from these factors, which corroborated as well that team size and trust within the team influences in software production.
Productivity in software factories is very important because it allows organizations to achieve greater efficiency and effectiveness in their activities. One of the pillars of competitiveness is productivity, and it is related to the effort required to accomplish the assigned tasks. However, there is no standard way to measure it, making it difficult to establish policies and strategies to improve the factory. In this work, a model based on data envelopment analysis is presented to evaluate the relative efficiency of the software factories and their projects, to measure the productivity in the software production component of the software factory through the activities that are carried out in their different work units. The proposed model consists of two phases in which the productivity of the software factory is evaluated and the productivity of the projects it conducts is assessed. Numerical tests on 6 software factories with 160 projects implemented show that the proposed model allows one to assess the software factories and the most efficient projects.
Productivity in software factories is very important because it allows organizations to achieve greater efficiency and effectiveness in their activities. One of the pillars of competitiveness is productivity, and it is related to the effort required to accomplish the assigned tasks. However, there is no standard way to measure it, making it difficult to establish policies and strategies to improve the factory. In this work, a model based on data envelopment analysis is presented to evaluate the relative efficiency of the software factories and their projects, to measure the productivity in the software production component of the software factory through the activities that are carried out in their different work units. The proposed model consists of two phases in which the productivity of the software factory is evaluated and the productivity of the projects it conducts is assessed. Numerical tests on 6 software factories with 160 projects implemented show that the proposed model allows one to assess the software factories and the most efficient projects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.