Improving Effort Estimation by Voting Software Estimation Models

Estimating software development effort is an important task in the management of large software projects. The task is challenging, and it has been receiving the attentions of researchers ever since software was developed for commercial purpose. A number of estimation models exist for effort prediction. However, there is a need for novel models to obtain more accurate estimations. The primary purpose of this study is to propose a precise method of estimation by selecting the most popular models in order to improve accuracy. Consequently, the final results are very precise and reliable when they are applied to a real dataset in a software project. Empirical validation of this approach uses the International Software Benchmarking Standards Group (ISBSG) Data Repository Version 10 to demonstrate the improvement in software estimation accuracy

Estimación de esfuerzo en desarrollo de software ágil: Estudio del estado actual en Bogotá

Context: Over the years, numerous studies have been developed related to estimating effort in agile software development, which allow us to understand the advances that have been made and the need for their use in companies. Objective: To know the perspective of entrepreneurs from different organizations in Bogotá that work in the sector or are related to the development of agile software and those who have had projects related to the subject. Method: For the elaboration of the article, a bibliographic research is carried out. Results: The data obtained are from 314 respondents in the city of Bogotá, the main findings are: 1) For companies it is extremely important with (34%) the adoption of an effort estimation methodology. 2) The most used estimation technique is the use case point with (43.31%). 3) The most used effort predictor is the Code Line (38.85%) and followed by this STORY POINT with (33.76%). 4) The agile methodology adopted in companies is SCRUM with (43.95%). 5) As the most determining factor to estimate the effort, the team experience with (53.50%) is considered. 6) In the percentage of error between estimate of projected effort and real effort (26.75%) of the respondents determine that this 5% -25% is underestimated. 7) Finally, as a difficulty in your company to estimate the effort of projects through agile software development, the respondents recognize (26.11%) that the resources are the greatest. Conclusions: The estimation of effort is relatively variable, for many companies this depends on the needs of each one, on the other hand, the use of agile methodology and estimation techniques varies in its use depending on the cross between them and how they are used. complement each other.Contexto: A lo largo de los años se han desarrollado numerosos estudios relacionados con la estimación de esfuerzo en el desarrollo de software ágil los cuales permiten comprender los avances que han tenido y la necesidad de su uso en las empresas. Objetivo: Conocer la perspectiva de empresarios de distintas organizaciones de Bogotá que trabajan en el sector o estén relacionados con el desarrollo de software ágil y aquellos que han tenido proyectos relacionados con el tema. Método: Para la elaboración del artículo se realizar una investigación a nivel bibliográfico. Resultados: Los datos obtenidos son de 314 encuestados en la cuidad de Bogotá, los principales hallazgos son: 1) Para las compañías es sumamente importante con (34%) la adopción de una metodología de estimación de esfuerzo. 2) La técnica de estimación mas usada es el punto de caso de uso con (43,31%). 3) El predictor de esfuerzo mas utilizado es la Línea de código (38,85%) y seguida de este STORY POINT con (33,76%). 4) Como metodología ágil adoptada en las empresas se encuentra SCRUM con (43,95%). 5) Como factor mas determinante para estimar el esfuerzo es considerado la experiencia de equipo con (53,50%). 6) En el porcentaje de error entre estimación de esfuerzo proyectada y esfuerzo real el (26,75%) de los encuestados hacen determina que esta 5%-25% subestimada. 7) Finalmente, como dificultad en su empresa para estimar el esfuerzo de proyectos mediante desarrollo de software ágil los encuestados reconocer con (26,11%) que los recursos como el mayor. Conclusiones: La estimación de esfuerzo es relativamente variable, para muchas compañías esto depende también de las necesidades de cada una, por otro lado, el uso de metodología ágil y técnicas de estimación varia en su uso dependiendo del cruce que se de entre ellas y como se complementan entre sí

Dynamic capabilities and project characteristics contributing to the success of open source software projects

Nowadays, numerous organisations from different industries and sectors have adopted Open Source Software (OSS) applications, because OSS development has come to be known as a reliable alternative to proprietary software that has the ability to produce cheap software of high quality. However, despite the increasing adoption of OSS applications, most OSS projects are abandoned after a while and experience failure. The objective of this research, therefore, is to extract the factors that drive success in OSS projects by developing and testing a research model that examines the influences of project characteristics and capabilities on the success of OSS projects. To test the relationships hypothesised, I collected data from 1409 OSS projects in a longitudinal fashion (over a period of 16 months). Results derived from my analysis show the following: (1) the number of operating systems with which an OSS project is compatible, the number of spoken languages into which a project is translated, using the OSS community’s preferred programming languages and project age positively impact OSS project success; (2) OSS projects’ capabilities of defect-removal, functionality-enhancement and release management are positively associated with their success; (3) the three measures of OSS project success – namely, user interest, developer interest and development sustainability – are interrelated; (4) overall, project characteristics and project capabilities have more or less equal predictive value to explain user interest, whereas project capabilities have relatively stronger predictive value to explain developer interest than project characteristics; and (5) although few of the relationships proposed are found to change over time, the longitudinal part of this research explores a temporal persistence in the relationship between OSS project success and its determinants in this study (that is, project characteristics and capabilities). In addition to having significant implications for research and theory, this study has several implications for managers of OSS projects, corporations that are interested in adopting OSS products, potential OSS sponsors, the OSS developer community and OSS hosting portals