What the developers wish to wish that Gytop Cubelot is a better act

Links table

Abstract and 1. Introduction

2. Methodology and 2.1. Search questions

2.2. Collection

2.3. Place a sign of data

2.4. Data extraction

2.5. Data analysis

3. Results and interpretation and 3.1. Type of problems (RQ1)

3.2. Type of causes (RQ2)

3.3. Solutions type (RQ3)

4. The consequences

4.1. The effects of Copilot users

4.2. The effects of Copilot team

4.3. The effects of researchers

5. Justice threats

6. Related work

6.1. Evaluating the quality of code created by Copilot

6.2. Copilot effect on practical development and 6.3. Conclusive summary

7. Conclusions, data, approval, a statement of credit and references contribution

2. Systematic

The aim of this study is to systematically identify the problems reported by developers when using GitHub Copilot in development, as well as their basic causes and possible solutions. We formulated three RQS to be answered in this study, which was detailed in section 2.1, and Figure 1 provides an overview of the search process.

2.1. Search questions

RQ1: What are the problems that users face while using COPILOT in the practice of software development?

The logical basis: GitHub Copilot is one of the most coding tools that are with the help of AI, and it has been widely used to develop software with 1.3 million paid -paid users until February 2024 (Wilkinson, 2024), and therefore it is important to understand the specific challenges and problems that users face while using this tool in the practice of software development.

RQ2: What are the main causes of these problems?

The logical basisUnderstanding the causes of the problems specified in RQ1 is essential to developing effective solutions to address them. By identifying these reasons, the study can provide an insight into how to improve the design and functions of Copilot.

RQ3: What are the possible solutions to address these problems?

The logical basisExplore the solution solutions specified in the RQ1 and the reasons specified in RQ2 is essential to improving the user experience in practical development using Copilot. By identifying these solutions, the study can gain an insight into possible solutions that enhance functions and ease of use in Copilot.

2.2. Collection

We collected data from three sources: Jaithb issues[1]Gypper’s discussions[2]And so on the publications[3]. GitHub Compes is a common feature on GitHub to track errors and features of features and report other problems related to software development projects, which allow us to capture the specific problems that users faced when coding with Copilot. GitHub discussions are a feature of GitHub for open discussions between the project and community members, which also provides a central center for discussions related to the project and knowledge sharing. Topics in GitHub discussions can vary from technical questions and suggestions to COPILOT use issues. Stack Overflow is a common technology community that provides a platform for public questions and answers dealing with a wide range of topics related to programming, development and technology, which also includes inquiries about the use of Copilot.

Given that Copilot was announced and its technical examination began on June 29, 2021, we chose to collect data that was then created. Data collection was conducted on June 18, 2023. To answer RQ3, that is, solutions to address Copilot problems, we chose to collect closed GitHub problems, as well as the answers that were answered and so on. Specifically, for GitHub problems, we used “Copilot” as a major word to research the problems related to closed Copilot in the entire world, and a total of 4,057 problems have been recovered. We have also used “Copilot” as a major word to research the leaflets that have been answered, which led to 679 recovered posts. Note that we did not use the “Copilot” brand to retrieve it because the keyword -based method allows us to get a more comprehensive data set. It differs from the problems of GitHub and beyond, GitHub discussions are organized in specific sub -categories, with “Copilot” listed as a sub -category within the comprehensive “product” category. Given the high importance of these discussions to Copilot, we collected all 925 discussions that answered under the “Copilot” sub -category.

2.3. Place a sign of data

We have made a sign of data on the data collected to liquidate those that cannot be used for this study. Filter criteria are as follows: The problem, discussion or post must contain specific information related to the use of Github Copilot.

2.3.1. Signs of experimental data

To reduce the personal bias in the process of placing the official marks, the first and third authors made signs of experimental data. For GitHub issues and discussions, we randomly chose 100 and 25 of each of them, which constitutes 2.5 % of the total number. Due to the small amount of publications, we chose random 35, which constitutes 5 % of the total jobs. Choosing a certain percentage of data from different platforms, respectively, is to verify whether the authors’ criteria are consistent with different data sources. A reliability was measured between the interlocutor between the authors through the Cohen Kaba laboratories (Cohen, 1960), which led to values ​​of 0.824, 0.834 and 0.806, which indicates a reasonable level of agreement between the authors. For any differences in the results, the authors participated in discussions with the second author to reach a consensus. The results of a sign of experimental data are collected and recorded in MS Excel (Zhou et al., 2024).

2.3.2. A mark on official data

Then the first and third authors made a sign of official data. During this process, we excluded a large amount of data not related to our research. For example, “Copilot” may indicate other meanings in some situations, such as the “joint pilot” of the plane. In addition, COPILOT may be mentioned directly without additional information, such as a mentioned post, “You can try to use Copilot, which is amazing.”. We also excluded these data cases because it was unable to provide useful information about the use of Copilot. During the process of setting signs, any result does not approve the authors to discuss with the second author until an agreement is reached. Ultimately, the authors collected 476 Jethabb cases, 706 Gypper’s discussions, and 142 publications. Data description results and recorded in MS Excel (Zhou et al., 2024) were collected.