Published April 26, 2017 | Version v1

Quality Assessment in DevOps: Automated Analysis of a Tax Fraud Detection System

  • 1. Universidad de Zaragoza
  • 2. Netfective Technology

Description

The dataset includes the results of the performance analysis of Big Blu case study under different workloads, number of available resources and execution demand of activities

Notes

This work has received funding from the European Union's Horizon 2020 research and innovation framework programme under grant agreement No. 644869 (DICE), the Spanish Government (Ministerio de Economía y Competitividad) under project No. TIN2013- 46238-C4-1-R and The Aragonese Goverment Ref. T27 – DIStributed COmputation (DISCO) research group.

Files

180secondsLaunchDetection.txt

Files (9.6 kB)

Name Size
md5:c0819cd5b239239df3448db058c90195
1.2 kB Preview Download
md5:bd9f1266bb00859744dd800c79625432
717 Bytes Preview Download
md5:68449a0f1b1fe33eb4d77a0b4adc50d1
708 Bytes Preview Download
md5:a12caf49ec32cf528996e03db0a07903
1.3 kB Preview Download
md5:ac364b8b55b397d49c3bb3ea7ffd8a1e
1.2 kB Preview Download
md5:7c98b9a07e5f5b32bea53b65afdb57e8
1.2 kB Preview Download
md5:b10802d26db2d2166defb0fa3cb7cb98
2.8 kB Preview Download
md5:2d6cbb37bd8f0ea9e4aa9cc7db4d0f67
204 Bytes Preview Download
md5:093bed888083b7b691d4e9ebbcb4f392
243 Bytes Preview Download

Additional details

Funding

European Commission
DICE - Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements 644869