Paper Info
Title
A Development Methodologies Recommender System Based on Knowledge from the Software Industry
Abstract
Software development methodologies are fundamental for the proper development of software projects. However, the most pertinent ones are not always selected depending on the resources available, which could result in failed projects. In fact, several reports show a high rate of failure in software projects. The type of development methodology chosen is one important factor when differentiating between successful from unsuccessful projects. For example, it has been reported that projects that use agile practices have a greater percentage of success. However, agile methodologies are not necessarily appropriate for any type of project. Given the above, a development methodologies recommendation system prototype was developed, that allows guiding developers with low experience or knowledge to select more appropriate methodologies according to different criteria. These criteria were obtained from bibliographic sources and then validated and complemented through an empirical study where surveys were applied to professionals of companies that develop software in Chile.
Year
DOI
Venue
2018
10.1109/SCCC.2018.8705156
2018 37th International Conference of the Chilean Computer Science Society (SCCC)
Keywords
Field
DocType
Software,Instruments,Silicon compounds,Analytical models,Recommender systems,Industries,Prototypes
Recommender system,Agile practices,Engineering management,Computer science,Agile software development,Software,Artificial intelligence,Software development process,Machine learning,Empirical research
Conference
ISSN
ISBN
Citations 
1522-4902
978-1-5386-9233-2
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Elizabeth E. Grandón101.69
Pedro G. Campos21468.92
Richard Fica Inzunza300.34
Fabián Ávila Cáceres400.34