Here's my recommendation:

1. "A systematic review of the impact of code smells on software quality" by E. Brito, J. P. da Silva, and R. de O. Schmidt (2018)

2. "Automated prediction of effort for code refactoring tasks" by C. Kapser and B. Murphy (2019)

3. "Empirical study of the relationship between architectural design decisions and software evolution" by J. R. Williams and C. Lu (2018)

4. "An empirical study on the impact of code review feedback on software evolution" by S. K. Ray, A. E. Hassan, and R. M. Bell (2019)

5. "Predicting the success of software evolution tasks: A machine learning approach" by X. He, Y. Cai, and L. Zhang (2018)

In The Name of Allah The Merciful And The Compassionate

Hi and Greetings,

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By The Name of Allah,

God Bless You

Thanks,

Qarn Fourteen Ltd.

You are looking for literature highlighting possible solutions to problems already being developed.

Instead, I would like to suggest topics that still need to be set to the proper extent because finding solutions of which is determining progress in solving the main problem for the resolution of which a new branch of science - artificial intelligence, was created.

Until today, the creation of artificial, autonomous rational systems is based on illusions caused by the subjective nature of living beings.

Here are some of the problems caused by such an illusory view:

There is no factual basis for claims regarding the presence of so-called mental functions.

There is no understanding of the following:

What is the reason for the enormous complexity of the human brain?

How do we perceive the world around us?

What is a subjective experience?

How is subjective experience used in shaping the behavior of a subjective system?

How do we manage to communicate and understand each other?

Fully autonomous artificial, subjective rational systems will inevitably threaten biological life’s existence.

At distances that allow such systems to be extrinsically motivated, security can be provided by design measures taken to prevent such systems from having intentions of their own.

However, when using artificial, subjective rational systems over longer distances, where it is impossible to use external motivation given from the environs of the Earth, we have to find a solution to the problem of safety.

There is simply an unlimited field of research for novice scientists.

I wish you good luck.

read this

https://www.geeksforgeeks.org/software-engineering-software-evolution/

In my opinion, understanding evolution is about understanding the problems that have driven that evolution. Fred Brooks still stands out a individual who understood the issues in the software industry. Try reading the Mythical Man Month (https://en.wikipedia.org/wiki/The_Mythical_Man-Month).

[email protected]

Man-month is an approach based on the project managers' subjective

assessment of the complexity of the problem to be solved.

The situation is complicated because, in most cases, programmers

are not familiar with the details of the processes that the created system should manage.

Therefore, they have to take advantage of the wishes of customers,

who, in turn, do not know the details of the software development process.

Increasing the number of programmers involved in the project

rarely helps since it requires the training of new hires and

their motivation for successful work.

Additionally, from my own experience, I can say that only about

one out of five employees works creatively, and there are very few

employees who are interested in the final result.

These difficulties can be overcome by creating semi-autonomous

subjective automatic systems that can be educated and trained,

like a person, in programming methods and the details of the

functioning of systems that should be controlled by the created

software systems.

I have a concept built based on well-known facts, allows the

achievement of that breakthrough and a business plan that will

avoid the need for a large investment in the development of

the entire system.

Who are with me?

Hi Tom,

The topic of software engineering for smart contracts, distributed applications, and blockchain deployment is worth attention. Please consider the following papers as examples:

"Reconfigurable Smart Contracts for Renewable Energy Exchange with Re-Use of Verification Rules" (https://doi.org/10.3390/app12115339)

"Solidity Code Generation From UML State Machines in Model-Driven Smart Contract Development" (https://doi.org/10.1109/ACCESS.2022.3162227)

"Continuous Delivery of Blockchain Distributed Applications" (https://doi.org/10.3390/s22010128)

"iContractML 2.0: A domain-specific language for modeling and deploying smart contracts onto multiple blockchain platforms" (https://doi.org/10.1016/j.infsof.2021.106762)

All of the articles listed above were published last year.

Regards,

Tomasz

They include: