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Critical Thinking and Communicating Assignment

Critical Thinking and Communicating Essay

Assignment 1: Reader Response
Overview
Learning outcomes
This assignment allows you to demonstrate your ability to:
● apply critical reading skills in your response to texts
● apply paraphrasing, summarizing and citation skills
● craft a unified, coherent, and cohesive reader response

Task
Choose ONE article from the two listed below and write a reader response of 700-750 words + 5%:
1. K. Rokis and M. Kirikova, “Challenges of low-code/no-code software development: A literature review,” in Lecture Notes in Business Information Processing, E. Nazaruka, K. Sandkukl, and U. Seigerroth, Eds. Springer, Cham. vol. 462. pp. 3-17, 2022. [Online]. Available: https://doi.org/10.1007/978-3-031-16947-2_1
2. S. Laato, M. Mantymaki, A.K.M. Najmul Islam, S. Hyrynsalmi, T., Birkstedt, “Trends and trajectories in the software industry: Implications for the future of work,”, Information Systems Frontiers, vol. 25, pp. 929-944, 2023. [Online]. Available: https://doi.org/10.1007/s10796-022-10267-4

You could use the structure below to help you write your reader response essay:
Introduction
• Provide a hook to the topic
• Provide the name(s) of the author(s) and the title of thearticle
• Briefly describe what the text is about
• End with your thesis / positionstatement.

Body

• Write a summary of the key points in the article in the past tense.
• Analyse the article. Then provide your response to two key points mentioned in the article:
• Explain your analysis, e.g., why you’ve made a certain claim about the text, and/or why it matters toyou.
• Support your claims with evidence from the text (specific examples) and information from credible sources.

Conclusion

• Summarize your main supporting ideas to remind the reader of your thesis/position.
Do not introduce a new idea at this point as you would like to give the reader a sense of completeness and closure.
• You might also end with what you learned from the analysis / text, and how this could apply to the reader.
Notes:
● Apply your knowledge of effective writing and the Paul-Elder framework to your analysis.
Justify your views, showing insight / depth of analysis.
● Use PEEL to help you write coherent and cohesive paragraphs for your analysis.
● Be sure to integrate information from external credible sources into your essay. Cite these sources in the text and in your reference list using the IEEE citation style. You need to use at least 5 credible secondary sources relevant to your topic.
Submission
Your assignment should be typewritten in Times New Roman, Arial, or Calibri font size 11, with 1.5 spacing.

Solution – Critical Thinking and Communicating Assignment

Introduction

In an era where software is eating the world, the very nature of software development itself is undergoing a radical transformation. As artificial intelligence, cloud computing, and automation reshape industries, how are these forces revolutionizing the world of those who create the code that powers our digital future? In the article “Trends and Trajectories in the Software Industry: Implications for the Future of Work”, Laato et al. (2023) explore the changes in the industry of software development and their influence on the workforce. The authors use expert interviews to identify trends in technology and do a profound analysis of their impact on the nonmaterial culture reasonably. The results of this study are interesting because they describe technology and approaches that are widely used today but also justify long-term implications on the profession of software development. There are four significant trends described by experts: growing scalable solutions, the importance of data solutions, the intersection of IT and other industries, and the domination of the cloud. I consider the article particularly insightful as it not only identifies current trends but also analyzes their potential long-term effects on the software development profession, offering a comprehensive view of the industry’s future trajectory.

Summary

Laato et al.’s (2023) research on software industry trends indicates radical changes reshaping software development and its workforce. Based on interview data with experts, the authors identified four trends affecting the industry: a transition towards solutions that can be scaled, increased importance of data, convergence of IT and non-IT fields, and cloud platforms’ superiority. Tools are being developed to abstract more of the development process, and DevOps is growing in popularity, both of which reduce manual labor in development. Data is becoming a prominent part of the industry, with machine learning reaching routine task levels and better-established procedures for collecting and curating data. It is gradually becoming part of other fields, and cloud platforms are becoming part of software technology. These changes present both threats and opportunities for software developers. Analysis of Key Points

Key Point 1: Shift from Manual Tasks to Scalable Solutions

Laato et al. (2023) concurred that the level of abstraction of development tools across all domains in the software industry is continuing to increase. This is evident in high-level programming languages, standard visual programming tools, and development platforms that hide many implementation details from developers. A considerable decrease in manual labor during software development is another primary driver of this change, with DevOps/MLOps paradigms and related technologies becoming more prominent across the industry (Mboweni et al., 2022). There are few software development or deployment projects today without the use of Docker by system administrators. The broad availability of online repositories allows most developers to receive support and guidance on deploying a piece of software using DevOps technologies with CI/CD pipelines (Benac & Mohd, 2022). In terms of changes for developers, the experts stated that the development time was and will continue to be spent on developing automated tests and using the available tools and pre-developed components instead of manual implementation. At the same time, the increase in the level of abstraction and tools available only allows some things to be automated and is the cause of unplanned changes. Thus, the limits of this change are set by both technological impossibility and nonmaterial cultural aspects, like company culture or developer skills.

Key Point 2: Increased Emphasis on Data

Laato et al. (2023) noted the trend of the increasing availability of machine learning, which is becoming more and more mainstream in the sphere of software development. However, it is essential to note that if the mentioned tools are becoming more common, the models themselves that these tools are used for have increased in complexity. The availability of open-source tools that include ML algorithms, premade APIs facilitating their use, and popular frameworks PyTorch and TensorFlow allowed the use of complex algorithms for solving varied tasks by software engineers who are not specialized in ML (Al-Saqqa et al., 2020). This meant that the quality of data became more emphasized by the market, with high-quality data becoming a significant competitive factor for the companies. This also raised other issues, such as the security of the data, which is supported, for instance, by GDPR legislation. According to Qian et al. (2023), it is not that more data scientists are employed on the market, but the skill set of data scientists is becoming a part of the standard toolbox for all software developers. This trend has serious consequences for recruitment, data accumulation, legal issues related to storage data, and ensuring the quality of training data for ML systems.

Conclusion

The identified trends – the shift to scalable solutions, the increased emphasis on data, the convergence of IT and non-IT industries, and cloud dominance, are changing the nature of software development. An obvious implication of these trends is the necessity of changes in the software development industry. Firstly, they require the developers to enhance their skills continuously. To follow the rapid pace of changes in the industry, organizations also need to change their structure rapidly. The growing cultural lag between the development of industrial technology and nonmaterial culture, in this case, education in the software industry, demonstrates the necessity of corresponding education and training. Secondly, the ongoing process of convergence will likely change the modern IT industry as it exists, despite the fact that the main consequences may be outside software development.

Reference

Al-Saqqa, S., Sawalha, S., & AbdelNabi, H. (2020). Agile software development: Methodologies and trends. International Journal of Interactive Mobile Technologies, 14(11).

Benac, R., & Mohd, T. K. (2022). Recent trends in software development: low-code solutions. In Proceedings of the Future Technologies Conference (FTC) 2021, Volume 3 (pp. 525-533). Springer International Publishing.

Laato, S., Mäntymäki, M., Islam, A. N., Hyrynsalmi, S., & Birkstedt, T. (2023). Trends and Trajectories in the Software Industry: implications for the future of work. Information Systems Frontiers, 25(2), 929-944.

Mboweni, T., Masombuka, T., & Dongmo, C. (2022, July). A systematic review of machine learning devops. In 2022 international conference on electrical, computer and energy technologies (ICECET) (pp. 1-6). IEEE.

Qian, C., Cong, X., Yang, C., Chen, W., Su, Y., Xu, J., … & Sun, M. (2023). Communicative agents for software development. arXiv preprint arXiv:2307.07924, 6.