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Article
Peer-Review Record

Optimization of DevOps Transformation for Cloud-Based Applications

Electronics 2023, 12(2), 357; https://doi.org/10.3390/electronics12020357
by Ahmed Mateen Buttar 1, Adeel Khalid 1, Mamdouh Alenezi 2, Muhammad Azeem Akbar 3,*, Saima Rafi 4, Abdu H. Gumaei 5 and Muhammad Tanveer Riaz 6,7
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Reviewer 4: Anonymous
Electronics 2023, 12(2), 357; https://doi.org/10.3390/electronics12020357
Submission received: 29 October 2022 / Revised: 22 December 2022 / Accepted: 4 January 2023 / Published: 10 January 2023
(This article belongs to the Special Issue Machine Learning for Service Composition in Cloud Manufacturing)

Round 1

Reviewer 1 Report

This paper elaborates on an essential aspect of today's software development paradigm and its execution using the cloud. I hope this paper gives a good insight into improving DevOps execution with cloud pipelines. 

The write-up of the paper looks promising, and the results seem good.

 There is a need to add give a detail read to the complete paper, especially, Abstract and conclusion.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper reports on an evaluation of the DevOps transformation for cloud applications. This paper proposes an algorithm and a possible cloud for application deployment on cloud employing DevOps techniques.

 

The overall idea is good, but there are many issues with the current form of this report. I will make an attempt to leverage some of the key issues in this review.

 

First, the Introduction Section lacks a well-defined statement of the actual goal of this study, as well as its intended contribution to the state-of-the-art. The authors must clarify those key issues as early as in the Introduction Section.

 

Section 2 mixes related work and background. I suggest splitting the ideas so the text could flow easier.

 

The paragraph starting in line #126 is too long. Please split it into more paragraphs.

 

Line 243 starts another Section 2. That is, there are TWO Sections 2 in the text, which is misleading.

 

Please describe the acronym for “AI approach” in line 246. By the way, what does it stand for?

 

The Algorithm in line 259 should be described as a pseudo-code (a code snippet). Readers would be more comfortable seeing such an algorithm in a more formalized way than plain text.

 

Section 3 (line 275) brings the results. However, the text is not well-structured, enabling us to see the questions the authors aimed to address in this research paper.

 

I also missed a section where the authors could discuss the results; presenting raw data in plots (Figures) is good, but discussing the yielded results is more interesting, as it sheds light on the research's important topics.

 

The research is promising, but the report is not good. There is much to do in terms of reporting the study. I believe the authors have a good study on their hands, but they must work to improve their report to a large extent.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report


Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

please see the attachment

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 4 Report

ok

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