Requirements Engineering for Internet of Things (loT) Software Systems Development: A Systematic Mapping Study

Round 1

Reviewer 1 Report

This manuscript applsci-1810239 studies a comprehensive and inclusive review of the RE of loT based system. To do this, a systematic mapping study (SMS) is presented to evaluate using parameters based on the existing literature. SMS is a methodology that has been widely used in research in the medical area and has recently been applied in Software Engineering (SE) to classify and structure the research results that have been published to know the advances in a topic and identify research gaps. This work aims to classify the existing evidence in the current scientific literature on RE proposals for IoT bases systems and implications for future research. This will make it possible to establish lines of research and work that must be addressed to improve the quality of IoT future systems development. My overall impression of this paper is that it is in general well-organized. It was a pleasure reviewing this work and I can recommend it for publication in Applied Sciences after a major revision. I respectfully refer the authors to my comments below.

1.       The English needs to be revised throughout. The authors should pay attention to the spelling and grammar throughout this work. I would only respectfully recommend that the authors perform this revision or seek the help of someone who can aid the authors. For example,

2.       (Page 2, Section 1. Introduction, before the last paragraph) The reviewer suggest to add “main contributions” and list clearly by breaking it down into three points. The reader can understand your contribution easily.

3.       Please adjust the style of all the references as the Applied Sciences. The current reference style is not suitable. Delete the reference [48] in arxiv.

4.       (Page 2, Line 37) The original statement is suggested to revised as “… the needs of this type of system users, and the most common algorithms used in machine learning (1) Facial expression recognition method with multi-label distribution learning for non-verbal behavior understanding in the classroom, (2) MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation (3) ARHPE: Asymmetric Relation-aware Representation Learning for Head Pose Estimation in Industrial Human-machine Interaction”.

5.       All the figures are not very clear. Please redraw the figure as the high-resolution format.

6.       The reviewer suggests authors introduce clearly the overall flow of the proposed method (in the body or in the picture description). The caption should be blew the figures.

7.       Experimental pictures or tables should be described and the results should be analyzed in the picture description so that readers can clearly know the meaning without looking at the body. For example, describe the colorful markers in Figure 3 and describe the results of the analysis of this phenomenon.

8.       (Page 2, Line 43) Please add some related references. The original statement “This network is currently used in a variety of fields, such as smart cities [4], healthcare system [5], image recognition (1)DOI: DOI: 10.1109/TNNLS.2021.3055147, (2) EDMF: Efficient Deep Matrix Factorization with Review Feature Learning for Industrial Recommender System, (3) Anisotropic angle distribution learning for head pose estimation and attention understanding in human-computer interaction), …”

9.       Add a new table to demonstrate the scores of all the comparing methods. And the best scores should be bolded.

10.   (Page 1, Introduction) The reviewer suggests authors don't list a lot of related tasks directly. It is better to select some representative and related literature or models to introduce with certain logic. For example, the latter model is an improvement on one aspect of the former model.

11.   The authors are suggested to add some experiments with the methods proposed in other literatures, then compare these results with yours, rather than just comparing the methods proposed by yourself on different models.

My overall impression of this manuscript is that it is in general well-organized. The work seems interesting and the technical contributions are solid. I would like to check the revised manuscript again.

Author Response

Authors really appreciate your suggestions in order to improves the quality of our article.

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper addresses a very relevant topic, such as software engineering in IoT systems. Provided descriptions are exhaustive and include enough details about the proposed methodology and solution. The proposal is sound, as experiments support the results, and the initial claims are validated through different experimental tests. In my opinion the paper may be accepted.

Author Response

Authors really appreciate your suggestions in order to improves the quality of our article.

Author Response File: Author Response.pdf

Reviewer 3 Report

In the introduction, IoT is commonly adopted in logistics and should be cited (e.g. Consumer perceptions to support IoT-based smart parcel locker logistics in China).

Before drawing the conclusion of key contributions, similar works and the key problems should be identified. The key objectives should be given before the contributions.

The motivation of this study is still not clear.

What are the section 2 fundamentals? Is it a review?

The research method is simple is no scientific details provided.

The RQs should be supported by more references.

More information on the SMS method should be provided.

The figures of discussion should be put in the results part.

More discussion should be provided. What are the impacts and implications?

I wonder if the article fits well with the journal scope and themes.

Author Response

Authors really appreciate your suggestions in order to improves the quality of our article.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

accept in current form.