Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Systematic code”

The Impact of Code Smells on Software Bugs: a Systematic Literature Review

Aloisio Cairo, Glauco de Figueiredo Carneiro, Miguel P. Monteiro · Preprints.org · 2018

Context: Code smells are associated with poor design and programming style that often degrades code quality and hampers code comprehensibility and maintainability. Goal: Identify reports from the literature that provide evidence of the influence of code smells on the occurrence of software bugs. Method: We conducted a Systematic Literature Review (SLR) to reach the~stated goal. Results: The SLR includes selected studies from July 2007 to September 2017 which analyzed the source code for open source and proprietary projects, as well, as several code smells and anti-patterns. The results of this SLR show that 24 code smells are more influential in the occurrence of bugs according to 16 studies. In contrast, three studies reported that at least 6 code smells are less influential in such occurrences. Evidence from the selected studies also point out tools, techniques and procedures applied to analyze the influence. Conclusion: To the best of our knowledge, this is the first SLR to target this goal. This study provides an up-to-date and structured understanding of the influence of code smells on the occurrence of software bugs based on findings systematically collected from a list of relevant references in the latest decade.

Cited by 4Open access

A Systematic Mapping Study of Code Quality in Education -- with Complete Bibliography

Hieke Keuning, Johan Jeuring, Bastiaan Heeren · arXiv (Cornell University) · 2023

While functionality and correctness of code has traditionally been the main focus of computing educators, quality aspects of code are getting increasingly more attention. High-quality code contributes to the maintainability of software systems, and should therefore be a central aspect of computing education. We have conducted a systematic mapping study to give a broad overview of the research conducted in the field of code quality in an educational context. The study investigates paper characteristics, topics, research methods, and the targeted programming languages. We found 195 publications (1976-2022) on the topic in multiple databases, which we systematically coded to answer the research questions. This paper reports on the results and identifies developments, trends, and new opportunities for research in the field of code quality in computing education.

Cited by 0Open access

QR code learning and video self-learning education: A systematic literature review

Eun-Kyung Jung, Jiyeon Jung · Korean Association For Learner-Centered Curriculum And Instruction · 2024

Objectives This study conducted a systematic literature review to gather fundamental data for the development of a video education model utilizing QR codes. Methods A systematic literature review was conducted to analyze prior research involving QR codes and studies related to video self-learning. Utilizing Korean academic information search services from January 2008 to January 2024, articles were searched using keywords such as ‘Learner,’ ‘student,’ ‘trainee,’ ‘QR,’ ‘QR code,’ ‘learning,’ ‘education,’ ‘video,’ ‘self-learning,’ ‘skill,’ ‘self-efficacy,’ ‘knowledge,’ ‘Attitude,’ etc. A total of 61 studies on QR codes were identified, from which 10 were selected. Additionally, 183 studies on video self-learning were reviewed, resulting in the selection of 9 studies. Results QR code creation was a simple process, and video materials were primarily integrated, and there were various educational media that could be applied to learning using QR codes. QR code-based education demonstrated a positive impact on academic achievement, and self-study through videos was associated with increased self-efficacy. Conclusions It is expected that QR code video education can serve as a supplementary medium for self-directed learning.

Cited by 0

A Systematic Review about Large Language Models (LLMs) applied to Code Generation

Fabio Alecsandro Bacin, Braulio Mello, Giancarlo Salton et al. · Revista Brasileira de Computação Aplicada · 2025

Large Language Models (LLMs) for code generation represent a significant advancement in software development by boosting productivity, simplifying repetitive tasks, enabling automated testing, and promoting best practices. This paper presents a systematic literature review (SLR) of studies focused on LLMs applied to code generation. The review enhances understanding of the capabilities and limitations of these models, outlining both their benefits and challenges. The review protocol included a search on the Google Scholar database using relevant keywords related to LLMs and code generation. A total of 112 articles were initially retrieved, from which 15 were selected based on relevance and quality criteria. Of these, 8 were analyzed in depth to evaluate various approaches and outcomes, while the remaining 7 provided the theoretical foundation for the study. This work contributes to the growing body of knowledge in the field and supports future research and applications of LLMs in software engineering.

Cited by 0Open access

A systematic (12,8) code for correcting single errors and detecting adjacent errors

Jay W. Schwartz, J.K. Wolf · IEEE Transactions on Computers · 1990

A parity check matrix is given for a systematic (12,8) binary code which connects all single errors and detects eight of the nine double adjacent errors within any of the three 4-b nibbles. It is shown that no (12,8) binary systematic parity check code can correct all 12 single errors and simultaneously detect all nine double adjacent errors within 4-b nibbles. A (12,8) binary systematic parity check code is given that corrects all 12 single errors and simultaneously detects eight of the nine double adjacent errors within 4-b nibbles.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 19

METODE NON- HEURISTIC UNTUK DETEKSI REFACTORING NON-SOURCE CODE (SYSTEMATIC LITERATURE REVIEW)

Ratih Nindyasari · Simetris Jurnal Teknik Mesin Elektro dan Ilmu Komputer · 2015

ABSTRAK Refactoring perangat lunak merupakan sebuah teknik untuk mentransformasi struktur internal perangkat lunak tanpa merubah fungsionalitas perangkat lunak itu sendiri. Refactoring termasuk dalam bentuk evolusi perangkat lunak, dimana hal ini bertujuan untuk meningkatkan kualitas perangkat lunak itu sendiri setelah perangkat lunak mengalami perbaikan, modifikasi, penambahan dan aktivitas perubahan lainnya dalam masa hidupnya. Tujuan penulisan pada paper kali ini adalah untuk melakukan Systematic Literature Review (SLR) tentang persoalan deteksi refactoring pada level non-source code yang tergolong pada metode non-heuristic. Dengan dilakukan SLR ini terdapat beberapa teknik seperti clustering, searching, Information Retrieval dan analisis regresi dapat digunakan untuk mendeteksi persoalan refactoring pada level non-source code. Dari beberapa teknik-teknik ini masing-masing memiliki kelebihan dan kekurangan. Teknik yang memiliki tingkat komputasi yang tinggi seperti clustering, searching, dan analisis regresi biasanya mampu menghasilkan refactoring yang lebih optimal dan menyeluruh dibandingkan dengan teknik lainnya seperti NLP dan teknik similaritas. Kata kunci: refactoring, non-source code refactoring, non-heuristic, systematic literature review.

Cited by 0Open access

<scp>porE</scp> : A code for deterministic and systematic analyses of porosities

Kai Trepte, Sebastian Schwalbe · Journal of Computational Chemistry · 2021

Accurate numerical calculations of porosities and related properties are of importance when analyzing metal-organic frameworks (MOFs). We present porE, an open-source, general-purpose implementation to compute such properties and discuss all results regarding their sensitivity to numerical parameters. Our code combines the numerical efficiency of Fortran with the user-friendliness of Python. Three different approaches to calculate porosities are implemented in porE, and their advantages and drawbacks are discussed. In contrast to commonly used implementations, our approaches are entirely deterministic and do not require any stochastic averaging. In addition to the calculation of porosities, porE can calculate pore size distributions and offers the possibility to analyze pore windows. The underlying approaches are outlined, and pore windows are discussed concerning their impact on the analyzed porosities. Comparisons with reference values aim for a clear differentiation between void and accessible porosities, which we provide for a small benchmark set consisting of eight MOFs. In addition, our approaches are used for a bigger benchmark set containing 370 MOFs, where we determine linear relationships within our approaches as well as to reference values. We show how these relationships can be used to derive corrections to a give porosity approach, minimizing its mean error. As a highlight we show how complex workflows can be designed with a few lines of Python code using porE.

Cited by 10

Code and data for "Systematic conservation prioritization with the prioritizr R package"

Hanson, Jeffrey O, Schuster, Richard, Strimas-Mackey, Matthew et al. · Zenodo (CERN European Organization for Nuclear Research) · 2024

Plans for expanding protected area systems (prioritizations) need to fulfill conservation objectives. They also need to account for other factors, such as economic feasibility and anthropogenic land use requirements. Although prioritizations are often generated with decision support tools, most tools have limitations that hinder their use for decision-making. We outline the prioritizr R package (https://prioritizr.net) for systematic conservation prioritization. This decision support tool provides a flexible interface to build conservation planning problems. It can leverage a variety of commercial (e.g., Gurobi) and open source (e.g., CBC and SYMPHONY) exact algorithm solvers to identify optimal solutions in a short period. It is also compatible with a variety of spatially explicit (e.g., ESRI Shapefile, GeoTIFF) and nonspatial tabular (e.g., Microsoft Excel Spreadsheet) data formats. Additionally, it provides functionality for evaluating prioritizations, such as assessing the relative importance of different places selected by a prioritization. To showcase the prioritizr R package, we applied it to a case study based in Washington State (United States) for which we developed a prioritization to improve protected area coverage of native avifauna. We accounted for land acquisition costs, existing protected areas, places that might not be suitable for protected area establishment, and spatial fragmentation. The prioritization identified 12,400 km2 of priority areas for increasing the percentage of species’ distributions covered by protected areas. We also conducted a benchmark analysis to examine the performance of different solvers. Although open source and commercial solvers were able to quickly solve large-scale conservation planning problems, commercial solvers were required for complex, large-scale problems. The prioritizr R package is available on the Comprehensive R Archive Network (CRAN). In addition to reserve selection, it can inform habitat restoration, connectivity enhancement, and ecosystem service provisioning. It has been used in numerous conservation planning exercises to inform best practices and aid real world decision-making.

Cited by 0Open access

Uncovering Systematic Failures of LLMs in Verifying Code Against Natural Language Specifications

Haolin Jin, Huaming Chen · 2025

Large language models (LLMs) have become essential tools in software development, widely used for requirements engineering, code generation and review tasks. Software engineers increasingly rely on LLMs to assess whether system code implementation satisfy task requirements, thereby enhancing code robustness and accuracy. However, it remains unclear whether LLMs can reliably determine whether the code complies fully with the given task descriptions, which is usually natural language specifications. In this paper, we uncover a systematic failure of LLMs in evaluating whether code aligns with natural language requirements. Specifically, using widely adopted benchmarks, we employ unified prompts to judge code correctness. Our results reveal that LLMs frequently misclassify correct code implementations as either "not satisfying requirements" or containing potential defects. Surprisingly, more complex prompting, especially when leveraging prompt engineering techniques involving explanations and proposed corrections, leads to higher misjudgment rate, which highlights the critical reliability issues in using LLMs as code review assistants. We further analyze the root causes of these misjudgments, and propose two improved prompting strategies for mitigation. For the first time, our findings reveals unrecognized limitations in LLMs to match code with requirements. We also offer novel insights and practical guidance for effective use of LLMs in automated code review and task-oriented agent scenarios.

Cited by 0