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West Virginia University

Pattern recognition in software engineering trend adapting

Abstract

dc:description.abstract

Whether and when to adapt to certain software engineering trends are difficult questions to be answered by many decision-makers. The main reasons are due to the fact that evolution of software engineering trends itself is determined by various factors, many of which come from the fields outside of the software technology, thus hard to predict. So it is even harder to estimate the cost and benefit when adapting to certain trends. This paper is intended to study ways to decrease the risk involved in such decision making processes, by developing a pattern from past software engineering trends. While the pattern cannot answer all the questions by itself, it can relief the decision makers in a large extent by providing the most important information relevant to the software engineering trends. The pattern recognition is achieved by using neural networks. Our result seems to be very encouraging, which begins to prove that there does exist pattern between the input data that we can observe and the output data that we need to know. Although more trends need to be observed and analyzed before we can reach a more concrete conclusion, it does show that neural network may be a valid approach in future research.

Degree

thesis:*
Name thesis:degree_name
MS
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Lane Department of Computer Science and Electrical Engineering
Year dc:date.available
2001

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chen, Dapeng
Contributors dc:contributor
  • Ali Mili.

Subjects

dc:subject × 1

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:researchrepository.wvu.edu:etd-2249

Chain of custody

source
Harvested from
West Virginia University
Base URL
researchrepository.wvu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Chen, Dapeng. Pattern recognition in software engineering trend adapting. Thesis thesis, 2001. https://doi.org/10.33915/etd.1246