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Predicting Schedule Delay Caused By ...

Alexander, Kelly Dula.

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Predicting Schedule Delay Caused By Errors During Software Integration.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predicting Schedule Delay Caused By Errors During Software Integration./
Author:	Alexander, Kelly Dula.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	132 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
Subject:	Systems science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10640848
ISBN:	9780355472943

Predicting Schedule Delay Caused By Errors During Software Integration.
Alexander, Kelly Dula.

Predicting Schedule Delay Caused By Errors During Software Integration. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 132 p.

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)--The George Washington University, 2018.

This research was conducted to evaluate and quantify the impacts complexity has on schedule based on errors created by organizational and system dependencies that occur during software integration testing. The combination of individually developed and managed systems and their interdependencies results in a complex system (or System of Systems) that is difficult to integrate within the original schedule. During the integration event the requirement that multiple systems provide a holistic capability creates a challenge that is rooted in the emergence of technical and non-technical integration challenges that managers are often unprepared to resolve. These challenges result in multiple errors that require significant collaboration and coordination during the problem resolution cycle that can result in significant schedule delay; however, there is little existing research that quantifies the delay. The inability of engineering managers to accurately predict schedule impact after a software integration test error results in increased schedule risk based on underestimation of the schedule delay. This research will provide engineering managers with a simple approach to support decisions by incorporating evidence-based recommendations for schedule impact that considers both legacy and current data. Knowledge Integration is used to merge known software integration challenges with error reports from US Army software integration test events to define Naive Bayes Model features. The data from the US Army software integration events was used to quantify the schedule delay, which concluded that errors that have a dependency (either technical or non-technical) with another system or organization create longer schedule delays when compared to errors created by systems that are standalone. Additionally, the research concludes that software integration challenges represented as features can be quantified to successfully predict the number of days required to resolve an error. The software integration challenges based on the past ten years of research indicates the following categories: System Interdependencies, Independent Management, Technical Risk, Non-Technical Risk and System of System Complexity. The combined impact of these challenges quantified as features results in a model that predicts schedule delay caused by a software integration error with 90% Global Accuracy that is significantly improved over the 39% to 79% accuracy that is the reported average for the original software resource schedule estimation for software development.

ISBN: 9780355472943Subjects--Topical Terms:

3168411
Systems science.

Predicting Schedule Delay Caused By Errors During Software Integration.
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