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11 results for “Static Analysis Tools”
Alert Type Frequency Assessment of Open-Source Static Analysis Tools and Codebases
<p>This includes all data needed to replicate and validate our frequency analysis of static analysis (SA) alerts produced using open-source SA tools on several OSS codebases. It includes instructions how to get and run the SA tools, a Dockerfile to conveniently get and use the SA tools, raw SA tool output, some python scripts to parse that output, parsed SA data and aggregate analyses, and SA data augmented with CERT coding rule and CWE data. </p> <p>The SA tools used:</p> <ul> <li>clang-tidy version 15.07 </li> <li>cppcheck version 2.9 </li> <li>CERT Rosecheckers </li> </ul> <p>The codebases analyzed:</p> <ul> <li>zeek version 5.1.1</li> <li>git version 2.39.0</li> <li>dos2unix version 7.4.3</li> </ul>
SATune: An Auto-tuning Approach for Configurable Static Analysis Tools
<p>Version 2.0.0 updates: Renamed tool to SATune.</p> <p>-------</p> <p>This contains both the executables and the data for our ICST 2021 submission, "SATune: An Auto-tuning Approach for Configurable Static Analysis Tools." The results are in results.tar.xz, and the SATune source code and experimental environment is is experiments.tar.xz.</p>
Evaluation Artifacts of RESTRuler, a Static Analysis Tool to Detect Design Rule Violations in OpenAPI Definitions
<p>All artifacts related to the empirical evaluation of the RESTRuler CLI, a Java-based tool to identify design rule violations in OpenAPI descriptions</p> <p>You can find the latest version here: <a href="https://github.com/restful-ma/rest-ruler-evaluation">https://github.com/restful-ma/rest-ruler-evaluation</a></p>
Replication Package for "How Developers Engage with Static Analysis Tools in Different Contexts"
<p>This is the replication package for the paper "How Developers Engage with Static Analysis Tools in Different Contexts".</p> <p>We include all the artifacts necessary to replicate the results obtained in our paper. Specifically, we provide (i) the survey questions together with all the valid answers we received including the demographics of our respondents, (ii) the most relevant statements that we extracted from the interviews including the demographics of our interviewees, (iii) the results of the card sorting performed on the development activities where our participants adopt Static Analysis Tools, (iv) all the data related to Krippendorff’s Alpha calculation for the performed card sorting, and (v) mapping of ASATs to the "rules" categories defined by Novak et al. (2010) and script for calculating occurrence, definition, and enforcement of the different ASAT types together with input and output data. Furthermore, we include the list of links to Reddit posts and inspected open-source projects together with their inspection data and the scripts for computing the inter-rater agreement during the inspection. Finally, we provide the Github features computed for each project and script for generating the sets of projects.</p>
[CTD-ES] Automatically Fixing Static Analysis Tools Violations
<p>Video <strong>in Portuguese</strong> with a short presentation summarizing some of the main points of the research conducted during my (Diego) masters' under the supervision of Prof. Dr. Rodrigo Bonifácio.</p>
Using Code Reviews to Automatically Configure Static Analysis Tools
<p>Working dataset (check traceability oracle) used in the paper</p>
Dataset for 'Assessing Golang Static Analysis Tools on Real-World Issues'
<p>Go Linter Evaluation Dataset</p> <p>This is a publicly available dataset for 'An empirical evaluation of Golang static code analysis tools for real-world issues.' Please refer to the data according to the names of the spreadsheets.</p> <p>Authors: Jianwei Wu, James Clause</p> <p>Collected Survey Data:<br>- This Excel file contains the collected survey data for the empirical study in details.</p> <p>R Scripts and Raw Data:<br>- These scripts are used for data analysis and processing.<br>- This is the initial data collected from surveys or other sources before any processing or analysis.</p> <p>Surveys for External Participants:<br>- This Excel file contains survey data collected for the evaluation of Go linters.<br>- This folder contains the surveys sent to external participants for collecting their feedback or data.</p> <p>Recruitment Letter.pdf:<br>- This PDF contains an example of the recruitment letter sent to potential survey participants, inviting them to take part in the study.</p> <p>Outputs from Existing Go Linters and Summarized Categories.xlsx:<br>- This Excel file contains outputs from various Go linters and categorized summaries of these outputs. It helps in comparing the performance and features of different linters.</p> <p>Selection of Go Linters.xlsx:<br>- This Excel file lists the Go linters selected for evaluation, along with criteria or reasons for their selection.</p> <p>UD IRB Exempt Letter.pdf:<br>- This PDF contains the Institutional Review Board (IRB) exemption letter from the University of Delaware (UD), indicating that the study involving human participants was exempt from full review.</p> <p>Survey Template.pdf:<br>- This PDF contains an example of the survey sent to the participants.</p> <p>govet issues.pdf:<br>- This PDF contains a list of reported issues about govet. Collected from various pull requests.</p> <p>Approved linters:<br>- staticcheck gofmt govet revive gosec deadcode errcheck.</p> <p>Table 2.jpg:<br>- A detailed figure to show the technical data in Table 2 of the paper.</p> <p>PR-summary-standalone:<br>- This is the AI tool we used to summarize the content of pull requests. Readme file is avaliable in this folder.</p>
Artifact for An Extensive Empirical Study of Nondeterministic Behavior in Static Analysis Tools
<p>This repository contains data for 'An Extensive Empirical Study of Nondeterministic Behavior in Static Analysis Tools' and the source code of the tool NDDetector that is used for performing the experiments in RQ2.</p><p>There are two directories, data and tool:</p><p><data> contains the data for the conclusion made in the two research questions, RQ1 and RQ2. (rq1 is Research Question 1s data)</p><p>In rq1/ there are:</p><p>final_results.csv - Contains 43 distinct results from 4 repositories (SOOT, WALA, FlowDroid, DroidSafe) that fix or report nondeterminism.</p><p>summary.pdf - Reports the number of nondeterminism results by tool repository at each stage of the qualitative study.</p><p>categorization.pdf - Reports the number of nondeterminism results by root cause categories at each component of analysis codebase in which the nondeterminism takes place</p><p>raw_data.zip - Contains the raw commits and issues extracted from 9 repositories (SOOT, DOOP, WALA, FlowDroid, DroidSafe, AmanDroid, TAJS, Code2Flow, PyCG)</p><p>key_words_results.zip - Contains the results extracted by each keyword (concurrency, concurrent, consistent, determinism, deterministic, different, flakiness, flaky, parallel, thread) from the raw data.</p><p>In rq2/ there are:</p><p>ICSE2024_AGGREGATE_DATA.csv - Contains the result distributions of each combination of target program, configuration hash, and tool aswell as the calculated consistency score.</p><p>analyze_results.py - Script that makes this data.</p><p>node_freqs - Contains the frequency of each node in the nondeterministic results we observed,it also keeps track of whether this particular node is a callee or caller or source/sink.</p><p>edge_dists - Contains the actual edge distributions of all of our results that behaved nondeterministically. it contains, for each result (edge/flow) across repetitions, which repetitions did or did not contain this edge/flow and which did. This means if you are interested in the actual differences across results generated by tool edge_dists/ is the place to look.</p><p>figure_8 - The raw data and occurences per node sheet for generating Figure_8.</p><p><tool> contains the framework and its source code that we used for conducting the experiments as well as the scripts that are used to post-process the detected nondeterminstic behavior and generate the summarized results in Section 4.</p>
Dataset and tool - A Static Analysis for Discovering Type-Related Coding Idioms in Python Programs
<p>The archive file contains the following materials:</p> <ul> <li>`repos.tar.gz`: dataset of the collected Python repositories</li> <li>`tool.tar.gz`: programs used in the case studies</li> </ul>
Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects
<p>This is the dataset for the publication "Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects".</p> <p>It contains just-in-time defect-prediction style data in jit_data2.tar.gz as well as warnings generated by PMD 6.31.0 in warnings_data3.tar.gz.</p> <p>Further information and scripts for generating the plots and tables can be found in the <a href="https://github.com/atrautsch/emse2021a_replication">replication kit</a>.</p>
Dataset for An Empirical Study of Static Analysis Tools for Secure Code Review
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