International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 06 | Jun 2025
p-ISSN: 2395-0072
www.irjet.net
Leveraging Machine Learning for Software Code Review Evaluation Ms. Anuyoksha Singh, Mr. Shrish Tiwari, Dr. Vivek Shukla MTech Scholar, Assistant Professor, Head of Department of Computer Science and Engineering, Dr. C.V. Raman University, Kota, Bilaspur, Chhattisgarh, India ---------------------------------------------------------------------------***-------------------------------------------------------------------------Abstract— Code review is the methodical analysis of the and resources. Additionally, because identifying the
fundamental cause of a bug and fixing it at its source is typically a laborious and time-consuming process, the fix may only be temporary and the bug may resurface later.
source code for a software system. Among other advantages, it is meant to identify errors missed during the first stages of development, enhancing the overall quality of the program and lowering the possibility of problems. Reviews can take many different forms, including official inspections, casual walkthroughs, and pair programming. It has been discovered that code review speeds up and simplifies the software development process more than most other software development approaches. In this research, we provide a machine learning method for software system code reviews. This would facilitate quicker and more thorough evaluations of the code that was checked in. The viability of the suggested method is assessed using Eclipse, an open source system.[7], [6]
Check-ins are made often in large software systems with constantly shifting requirements. In these situations, there is a significant risk of introducing latent defects due to improper evaluation. This could then lead to numerous software problems and waste a significant amount of time and money on rework. To further explain the time required to identify the underlying cause of the issues and then address them in order to prevent future occurrences and preserve the software system's quality. The aforementioned defects would never have been able to enter the code base if the code modifications had been thoroughly examined before being committed. This would have saved a significant amount of resources and raised the standard of software systems overall.
Index Terms—Code Review, Software development process, Machine learning.
I. INTRODUCTION
A supervised machine learning technique is suggested in combination with a version control system and a bug tracking system to address the aforementioned issue. A basic degree of code review will always be in place for any check-ins because of the automated machine learning technique, which lowers the chance that a problem will enter the code base unnoticed. Additionally, this code review might be used in conjunction with the human review process to help the human reviewers determine how much attention a code check-in requires. This would increase the efficiency of the entire review process, which would ultimately lead to higherquality software products.
Active software development is a series of modifications that improve the value of already-existing software by adding new features, removing old ones, improving the current implementation, organizing the code base according to best practices, and increasing scalability and robustness. All of the aforementioned actions run the risk of causing software system bugs. The code is typically peer-reviewed before being added to the code base in order to mitigate this risk. However, because peer review is a manual procedure, mistakes might happen. Errors can occur for a variety of human factors, such as unclear code, the reviewer's workload, domain knowledge, or a lack of a review deadline. Due to deadline constraints, it frequently occurs that code changes are submitted straight into the code base without first undergoing reviews. Therefore, there is a good chance that the code review will fall short. [10]
The remainder of the document is structured as follows: We provide an overview of the systems in section II. We then give a detailed discussion of the problem for which we intend to offer a solution in section? We next discuss possible fixes for the problem in part IV. We provide our response in section V. In section VI, we then discuss the results of the experiments. Section VII discusses the future scope, while Section VIII provides a conclusion.
Because there is no review, the defects can enter the software code base undetected. Usually, these flaws are discovered after they have already begun to exist. A developer is then tasked with fixing these. Fixing the bug usually requires the developer to reacquaint themselves with the code. In the process of developing software, this consumes a lot of time
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