Applications of Genetic Engineering in Software Engineering, Machine Learning and Distributed Computing

Running head: RESEARCH REPORT ON APPLICATIONS OF GENETIC ENGINEERING
Research Report on Applications of Genetic Engineering
Name of the Paper
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RESEARCH REPORT ON APPLICATIONS OF GENETIC ENGINEERING1
Table of Contents
1. Introduction..................................................................................................................................2
2. Discussion over the Presented Article.........................................................................................2
3. Conclusion...................................................................................................................................5
References........................................................................................................................................6
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RESEARCH REPORT ON APPLICATIONS OF GENETIC ENGINEERING2
1. Introduction
In the recent times, there have been major kind of improvements within the types of
approaches based on computation, which includes random, evolutionary and deterministic. This
paper puts a brief focus over the aspect of Genetic Algorithm (GA), which is considered as the
most common form of evolutionary computational technique that is majorly been used in
computing for solving different NP-Hard types of problems in relation to computation.
The following report thus discusses about the critical review on the paper focusing on the
topic based on application of genetic engineering in the field of software engineering, machine
learning and distributed computing [10]. The paper would thus discuss about the highlighted
aspects that are looked upon in the recent times and the views proposed by authors.
The selected article would be chosen based on focusing over the most discussed topics in
the field of software and research industry. Hence, the most favorable topic would be discussed
that would focus upon genetic engineering, which is the primary topic of discussion.
2. Discussion over the Presented Article
The presently discussed paper would be focusing over the wide range of applications that
are supported by genetic algorithm in the field of software engineering, machine learning and
distributed computing. The primary intention of this article is focused over understanding the
most important concepts based on GA, which can be defined as one of the most important
evolutionary technique [1]. This technique is important for solving NP-hard computational
problems. In the discussed article, different authors have put together different views based on
genetic based solutions, which are implemented by various software agencies for presenting their
own ways of research. However, the critique over the presented paper would majorly focus on
the concept of genetic algorithm, their role in genetic engineering and distributed computing and
a brief discussion on machine learning [7]. Different concepts as stated by various authors have
been put together within the article in order to understand the beneficial concepts.
In the introductory part of the article, a brief discussion is focused on understanding the
ways in which GA has been making huge amount of progress within the industry of software and
research. The article presents a strong understanding over the concept of Evolutionary
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