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About 10,000 papers for “source code analysis”

Analysis source code.

Barry Smyth (10826056) · Figshare · 2022

<p>A Jupyter notebook (Python) is provided as part of the supporting information with the code required to reproduce the analysis presented and to generate the graphs and results included in this study. Necessary requirements and dependencies to execute this code are included in the Jupyter notebook file.</p> <p>(IPYNB)</p>

Cited by 0Open access

Source code analysis dataset

Ben Gelman, Banjo Obayomi, Jessica Moore et al. · Data in Brief · 2019

The data in this article pair source code with three artifacts from 108,568 projects downloaded from Github that have a redistributable license and at least 10 stars. The first set of pairs connects snippets of source code in C, C++, Java, and Python with their corresponding comments, which are extracted using Doxygen. The second set of pairs connects raw C and C++ source code repositories with the build artifacts of that code, which are obtained by running the make command. The last set of pairs connects raw C and C++ source code repositories with potential code vulnerabilities, which are determined by running the Infer static analyzer. The code and comment pairs can be used for tasks such as predicting comments or creating natural language descriptions of code. The code and build artifact pairs can be used for tasks such as reverse engineering or improving intermediate representations of code from decompiled binaries. The code and static analyzer pairs can be used for tasks such as machine learning approaches to vulnerability discovery.

Cited by 9Open access

smFISH Analysis Source code

Bouchet, Mathilde · Zenodo (CERN European Organization for Nuclear Research) · 2022

Source code of smFISH image analysis scripts (MATLAB)

Cited by 0Open access

Static control [source-code analysis]

A. Cothard · Electronic Systems and Software · 2006

Source-code analysis lets you pick up programming errors without running the software. Spotting errors early in the process is the cheapest and usually the easiest way of avoiding problems and project delays, as with any design and production process. The problem with software is that you have to have a lot of it ready before you can test it fully. But what if you could subject even individual modules to scrutiny without demanding that the code actually runs? This is where source code analysis (SCA) comes in.

Cited by 0

Source code for climate analysis

Benestad, Rasmus · Figshare · 2018

The version of the R-package esd that was used to produce results submitted to ERL: climate atlas for the Barents region for temperature, precipitation, and storm statistics. <br>Frozen copy of https://github.com/metno/esd<br>

Cited by 0Open access

Source code for climate analysis

Rasmus Benestad · Figshare · 2016

The version of the R-package esd that was used to produce results submitted to ERL: climate atlas for the Barents region for temperature, precipitation, and storm statistics. <br>Frozen copy of https://github.com/metno/esd<br>

Cited by 0Open access

Source Code Analysis and Manipulation

2008

The special section contains nine papers which are extended versions of papers originally published in the proceedings of the IEEE workshop on Source Code Analysis and Manipulation (SCAM 2001). The papers cover the spectrum of analysis and manipulation work from traditional transformation application areas concerned with optimisation through to more novel application areas such as transformation for evolution of websites;

Cited by 0

Supporting Source Code Difference Analysis

2008

The paper describes an approach to easily conduct analysis of source-code differences. The approach is termed meta-differencing to reflect the fact that additional knowledge of the differences can be automatically derived. Meta-differencing is supported by an underlying source-code representation developed by the authors. The representation, srcML, is an XML format that explicitly embeds abstract syntax within the source code while preserving the documentary structure as dictated by the developer. XML tools are leveraged together with standard differencing utilities (i.e., diff) to generate a meta-difference. The meta-difference is also represented in an XML format called srcDiff. The meta-difference contains specific syntactic information regarding the source-code changes. In turn this can be queried and searched with XML tools for the purpose of extracting information about the specifics of the changes. A case study of using the meta-differencing approach on an open-source system is presented to demonstrate its usefulness and validity. 1.

Cited by 0

Source data and analysis code.

Ruihao Gong (11288115), Zijian Feng (223793), Yanyun Zhang (145529) · Figshare · 2025

This ZIP archive includes the dataset and code used to reproduce the results of this study. (ZIP)

Cited by 0Open access

Source code analysis with LDA

David Binkley, Daniel Heinz, Dawn Lawrie et al. · Journal of Software Evolution and Process · 2016

Abstract Latent Dirichlet allocation (LDA) has seen increasing use in the understanding of source code and its related artifacts in part because of its impressive modeling power. However, this expressive power comes at a cost: The technique includes several tuning parameters whose impact on the resulting LDA model must be carefully considered. The aim of this work is to provide insights into the tuning parameters' impact. Doing so improves the comprehension of both researchers who look to exploit the power of LDA in their research and those who interpret the output of LDA‐using tools. It is important to recognize that the goal of this work is not to establish values for the tuning parameters because there is no universal best setting . Rather, appropriate settings depend on the problem being solved, the input corpus (in this case, typically words from the source code and its supporting artifacts), and the needs of the engineer performing the analysis. This work's primary goal is to aid software engineers in their understanding of the LDA tuning parameters by demonstrating numerically and graphically the relationship between the tuning parameters and the LDA output. A secondary goal is to enable more informed setting of the parameters. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Cited by 9

Source Code Analysis Laboratory (SCALe)

Robert C. Seacord, William Dormann, James McCurley et al. · Figshare · 2012

The Source Code Analysis Laboratory (SCALe) is a proof-of-concept demonstration that software systems can be conformance tested against secure coding standards. CERT® secure coding standards provide a detailed enumeration of coding errors that have resulted in vulnerabilities for commonly used software development languages. The SCALe team at the CERT Program, part of Carnegie Mellon University's Software Engineering Institute, analyzes a developer's source code and provides a detailed report of findings to guide the code's repair. After the developer has addressed these findings and the SCALe team determines that the product version conforms to the standard, the CERT Program issues the developer a certificate and lists the system in a registry of conforming systems. This report details the SCALe process and provides an analysis of selected software systems.

Cited by 8Open access

Analysis Source Code Verification Tools

De L&amp;apos;université De Nice-sophia Antipolis, Candidat Antonio Cansado, Frantisek Plasil et al. · 2008

Software Components software modules well-defined interfaces provided and required services composition

Cited by 0

Analysis of Source Code Repositories

Alberto Sillitti, Giancarlo Succi, Tullio Vernazza · 2011

Source code repositories are designed to store a huge amount of source code. They also collect indirectly information useful to analyze the development process. Usually, the last set of data is not used at all due to the lack of specialized tools to collect and analyze such data. This paper presents the early stages of a tool designed to perform acquisition and analysis of data stored in source code repositories. 1.

Cited by 0

Bioimage ANalysis Desktop Source Code

Sun, Yi, Tischer, Christian, Hériché, Jean-Karim · Zenodo (CERN European Organization for Nuclear Research) · 2025

The BAND platform offers cloud based desktops accessible with a web browser so that you can work on your data from anywhere with an internet connection. This project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – NFDI 46/1 – 501864659

Cited by 0Open access

Source Code Analysis Laboratory (SCALe)

Seacord, Robert, Dormann, Will, McCurley, James et al. · KiltHub Repository · 2012

The Source Code Analysis Laboratory (SCALe) is a proof-of-concept demonstration that software systems can be conformance tested against secure coding standards. CERT® secure coding standards provide a detailed enumeration of coding errors that have resulted in vulnerabilities for commonly used software development languages. The SCALe team at the CERT Program, part of Carnegie Mellon University's Software Engineering Institute, analyzes a developer's source code and provides a detailed report of findings to guide the code's repair. After the developer has addressed these findings and the SCALe team determines that the product version conforms to the standard, the CERT Program issues the developer a certificate and lists the system in a registry of conforming systems. This report details the SCALe process and provides an analysis of selected software systems.

Cited by 0Open access