Library Catalogue

Amazon cover image
Image from Amazon.com
Image from Google Jackets

Evidence-based Software Engineering Derek Jones

By: Contributor(s): Material type: TextTextSeries: Open textbook libraryDistributor: Minneapolis, MN Open Textbook LibraryPublisher: [Place of publication not identified] Knowledge Software 2020Copyright date: ©2020Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781838291303
Subject(s): LOC classification:
  • QA76
  • QA1
  • QA37.3
Online resources:
Contents:
1 Introduction -- 2 Human cognition -- 3 Cognitive capitalism -- 4 Ecosystems -- 5 Projects -- 6 Reliability -- 7 Source code -- 8 Stories told by data -- 9 Probability -- 10 Statistics -- 11 Regression modeling -- 12 Miscellaneous techniques -- 13 Experiments -- 14 Data preparation -- 15 Overview of R
Subject: This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available. The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster. The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

1 Introduction -- 2 Human cognition -- 3 Cognitive capitalism -- 4 Ecosystems -- 5 Projects -- 6 Reliability -- 7 Source code -- 8 Stories told by data -- 9 Probability -- 10 Statistics -- 11 Regression modeling -- 12 Miscellaneous techniques -- 13 Experiments -- 14 Data preparation -- 15 Overview of R

This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available. The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster. The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data.

Attribution-ShareAlike

In English.

Description based on print resource

There are no comments on this title.

to post a comment.

© 2024, Kenya Medical Training College | All Rights Reserved