Bibliographic citations
Crispin, A., Quino, J. (2023). Sistema de atención de requerimientos para control y aseguramiento de calidad de software bancario [Trabajo de suficiencia profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/671610
Crispin, A., Quino, J. Sistema de atención de requerimientos para control y aseguramiento de calidad de software bancario [Trabajo de suficiencia profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/671610
@misc{renati/412794,
title = "Sistema de atención de requerimientos para control y aseguramiento de calidad de software bancario",
author = "Quino Flores, Jorge Angelo",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
The goal of this project was to implement a request service system (SAR, acronym in Spanish) for the Software Factory department in the company Software Enterprise Services S.A.C. This department works with one of the company main clients, the bank Scotiabank Chile, to whom it has provided software development service for more than 10 years. However, in recent years the bank has complained about the service because of many software solutions not fulling quality expectations and being rejected until defects were corrected. Thus, the Software Factory management sought to standardize its service flow prioritizing quality assurance and control of its delivered software and introducing the SAR system as its main tool for managing and monitoring the bank requests, available for all the department staff. Software technologies used in the development of SAR were Angular for its web interface and .NET framework for its REST API. For validation it was determined a first sample of 15 requests would follow SAR service flow and a second sample of also 15 requests would not, then both samples would be measured by rejection percentage. This value expressed how many requests had their deliveries rejected by the bank, and the expectation from the management was to lower rejections by using SAR. The first sample of requests that followed SAR performed well by obtaining a rejection rate of 40,00% compared to 60,00% from the second sample. This concludes that SAR helped to reduce rejections and as result contributed to improve the Software Factory service.
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