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185 results for “Program Analysis”
Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs
<p>Supplemental data and analysis files for Perron et al.: "Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs" (<a href="https://www.nature.com/articles/s42003-022-03796-w">https://www.nature.com/articles/s42003-022-03796-w</a>). The .tar.gz files contain read counts associated with various RNA-seq analyses. The .rds files are single R object files that contain various analysis results tables. The .csv files also contain analysis results or sample metadata tables. See <a href="http://csg.lab.mcgill.ca/sup/pancancer_stability/">http://csg.lab.mcgill.ca/sup/pancancer_stability/</a> for a full description of the files.</p>
Primary raw observation input file for the Ring Laser Analysis program
<p>This dataset is the primary input for the ring laser analysis program. It comprises a tab-delimited table, containing time information, the observed Sagnac frequency and a fairly large number of auxiliary measurements in order to compute the necessary raw data reductions. </p>
Dataset for Dynamic Analysis of Quantum Annealing Programs
<p>Quantum software engineering is emerging as a relevant field as it deals with the challenges of producing the new quantum software, whose adoption is increasing progressively. One of those challenges is how quantum software is migrated, how it operates in combination with classical software, or how it should be maintained. In this context this research focuses on reverse engineering of quantum annealing software to facilitates its integration in hybrid software systems. Quantum annealing software has gained a certain market penetration, demonstrating a good performance for optimization problems. While there are some preliminary reverse engineering techniques for gate-based quantum software, there is no reverse engineering techniques to discover the underlying optimization problem definitions (Hamiltonians functions to be minimized). Problem definitions are, in turn, dynamically defined through classical software, and can evolve over time, which make it difficult its accurate comprehension and abstract representation. Thereby, this paper presents a dynamic analysis technique for D-Wave (python) programs for reversing Hamiltonians expressions, that are additionally represented according to the Knowledge Discovery Metamodel. Due to the usage of this standard, the reversed Hamiltonians can be represented in combination with other parts of classical-quantum software systems. In order to facilitates its adoption, the proposed technique has been empirically validated through a case study with 27 D-Wave programs that demonstrates the effectiveness and efficiency. This dataset includes measures derived from that case study.</p>
FIGURE 8 in An analysis of fossil identification guides to improve data reporting in citizen science programs
FIGURE 8. Cluster analyses of all subjects as individuals. Subject labels denote which field guide the subject tested, a red 'C' for color photos, a black 'G' for grayscale photos, and a blue 'I' for illustrations. Author names are abbreviated "DaBu" for Dava Butler, "DoEs" for Donald Esker and "KrJu" for Kristopher Juntunen.
FIGURE 1 in An analysis of fossil identification guides to improve data reporting in citizen science programs
FIGURE 1. Map of the United States and surrounding regions, showing the location of the state of Florida and FMMS (Google 2017). 1B: Geologic map of the State of Florida, showing the geographic distribution of rocks and the location of the FMMS (Google 2017; Scott et al. 2001). 1C: Geologic map of the region around the FMMS, showing the distribution of rocks and location of the site (Google 2017; Scott et al. 2001). 1D: Photograph of FMMS, taken by Fred Mazza.
Fig. 5 in Towards incorporating insect isotope analysis using cavity ring-down spectroscopy into area-wide insect pest management programs
Fig. 5. Cumulative standard deviation of the mean carbon isotope signature of individual moths, field-caught LBAM (circles), mass-reared pink bollworm (squares) and mass-reared LBAM (triangles), analysed using the CM-CRDS module.
Fig. 3 in Towards incorporating insect isotope analysis using cavity ring-down spectroscopy into area-wide insect pest management programs
Fig. 3. Carbon isotope signature of common cutworm leg samples from different moths reared on the artificial laboratory diet or caught in the wild (circles, n = 5, Bars +/- 3 SD). The spermatophore data point (triangle) is the carbon isotope signature of spermatophores dissected from laboratory-reared females mated with field-caught males (n = 5, Bars +/- 3 SD). All samples measured using CM-CRDS.
Fig. 1 in Towards incorporating insect isotope analysis using cavity ring-down spectroscopy into area-wide insect pest management programs
Fig. 1. Carbon isotope ratios of 16 different common dietary components measured using either elemental analysis isotope ratio mass spectrometry (EAIRMS) or combustion module cavity ring down spectrometry (CM-CDRS).
Fig. 2 in Towards incorporating insect isotope analysis using cavity ring-down spectroscopy into area-wide insect pest management programs
Fig. 2. Carbon isotope ratios of 3 populations of the common cutworm measured using either elemental analysis isotope ratio mass spectrometry (EA-IRMS) or combustion module cavity ring down spectrometry (CM-CDRS): Field-caught moths: squares; synthetic diet-reared moths: circles and laboratory-reared on castor diet moths: triangles.
Code4Bench: A Multidimensional Benchmark of Codeforces Data for Different Program Analysis Techniques
<p>Reproducible research relies on well-designed benchmarks. However, evaluation on a single benchmark increases the risk of overfitting; that is, an optimization to reach a certain performance. In recent years several well-designed benchmarks have been constructed for different subfields of program analysis. However, they often involve real-world industrial projects in few languages such as C or Java. We provide Code4Bench, a benchmark comprising 3,421,357 programs totaling of 306,053,105 lines of code in 41 versions of 28 programming languages such as C/C++, Java, Python, and Kotlin. We have constructed this benchmark from Codeforces, a famous programming competition website, which is widely used by international programmers. Code4Bench advances the state-of-the-art in conducting reproducible and comparative experiments. It helps mitigate the bias and increase the generality and conclusiveness of the results. We present our methodology in construction of Code4Bench and give various descriptive statistics. We have also conducted an online survey on the users of Codeforces’ website whose code is included in the benchmark. The survey is concerned about the user’s demographic information and programming habits, whose results are also provided in the benchmark. Finally, we leveraged an automatic process by which we localized faults within the faulty versions and categorize them according to a coarse-grained classification. In addition to its usage in empirical studies, Code4Bench can be used to teach programming and evolve algorithmic problems. We release Code4Bench in database format to allow researchers to extract other data of the benchmark by arbitrary queries.</p> <p>Code4Bench version 1.0.0 is publicly available at <a href="https://zenodo.org/record/2582968">https://zenodo.org/record/2582968</a>, with DOI 10.5281/zenodo.2582968, thereby providing long-term storage and versioning. It is released under the terms of Creative Commons Attribution 4.0 International license. Code4Bench is also publicly available at: <a href="https://github.com/code4bench/Code4Bench">https://github.com/code4bench/Code4Bench</a>, in which we have provided some additional information and script examples.</p>
Antibody panel used for multiplexed antibody-based imaging of Human Pancreas Analysis Program (HPAP) samples by CODEX
<p>This data file details antibodies applied to human pancreas tissue samples from the Human Pancreas Analysis Program (HPAP; RRID:SCR_016202) of the <a href="https://hirnetwork.org/">Human Islet Research Network</a> (HIRN; RRID:SCR_014393). Images will be uploaded for interactive analysis on <a href="https://pancreatlas.org/datasets">Pancreatlas</a> (RRID:SCR_018567) and made available for download via <a href="https://hpap.pmacs.upenn.edu/">PANC-DB</a>. Workflow is documented on protocols.io: <a href="https://dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1">dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1</a>.</p><p>Table format adapted from Radtke AJ, Quardokus EM, Saunders DC (2022), <a href="https://doi.org/10.5281/zenodo.7386417">SOP: Construction of Organ Mapping Antibody Panels for Multiplexed Antibody-Based Imaging of Human Tissues</a>. See also: Saunders D; Reihsmann R. <a href="https://doi.org/10.48539/HBM754.BHVR.258">OMAP-13: Organ Mapping Antibody Panel (OMAP) for Multiplexed Antibody-Based Imaging of Human Pancreas with CODEX, v1.0</a>.</p>
Reception of a physical activity intervention program in German older adults. Data from a feedback analysis of PROMOTE II.
<p>As part of the<strong> AEQUIPA </strong>prevention research network, the aim of the <strong>PROMOTE II</strong> study was to gain insights into primary prevention for healthy aging. One focus was on the development and dissemination of ready-to-use tools and work aids to promote physical activity.</p><p>As part of a nine-month randomized trial with a cross-over design among adults aged 60 and above, eligible participants from 14 districts in Bremen in proximity to the two study centers (one in the North and one in the East of the city of Bremen, Germany) were randomly assigned to either a) a print-based intervention (PRINT) or b) a web-based intervention (WEB). Randomly selected thirty percent of the web-based intervention group received an activity tracker in addition (WEB+).</p><p>Usage of program components, attendance of group sessions and acceptance of the intervention were assessed via self-administered paper-based questionnaires three and nine months after baseline as well as feedback interviews and class recordings. Participant feedback was analyzed using quantitative methods on a descriptive basis, as well as using qualitative content analysis of open-ended questions, group-interviews and protocols based on the socio-ecological model as coding framework.</p><p>This publication provides the coding matrix, including the participant feedback data.</p>
Replication package for article 'Parallel Program Analysis on Path Ranges'
<p>This Replication package contains all the results for the article "Parallel Program Analysis on Path Ranges"</p> <p>Abstract. Symbolic execution is a software verification technique symbolically running programs and thereby checking for bugs. <br> Ranged symbolic execution <br> performs symbolic execution on program parts, so called {\em path ranges}, in parallel.<br> Due to the parallelism, verification is accelerated and hence scales to larger programs.</p> <p>In this paper, we discuss a generalization of ranged symbolic execution to arbitrary program analyses.<br> More specifically, we present a verification approach that splits programs into path ranges and<br> then runs arbitrary analyses on the ranges in parallel. Our approach in particular allows to run {\em different}<br> analyses on different program parts.<br> We have implemented this generalization on top of the tool \textsc{CPAchecker} and evaluated it on programs from the SV-COMP benchmark. Our evaluation shows that verification can benefit from the parallelisation of the verification task,<br> but also needs a form of work stealing (between analysis) as to become efficient.</p>
Organisation of gene programs revealed by unsupervised analysis of diverse gene-trait associations
<p>Data used for manuscript 'Organisation of gene programs revealed by unsupervised analysis of diverse gene-trait associations'.<br> </p> <p> </p> <p> </p>
Dataset, test programs and analysis scripts for the related paper "Effects of reverberation on speech intelligibility in noise for hearing-impaired listeners"
<p>This dataset contains the data, test programs and analyses scripts used for a study submitted as a stage 2 registered report for Royal Society Open Science.</p>
Artifact for research regarding Ranged Program Analysis
<div> </div> <div>This artifact is a summary of data regarding ranged program analysis.</div> <div>It contains the most important results from the following three papers:</div> <p> </p> <div>- Jan Haltermann, Marie-Christine Jakobs, Cedric Richter, and Heike Wehrheim. “Parallel Program Analysis via Range Splitting”. In: Proc. FASE. Vol. 13991. 2023, pp. 195–219. doi: 10.1007/978-3-031-30826-0_11.</div> <div>- Jan Haltermann, Marie-Christine Jakobs, Cedric Richter, and Heike Wehrheim. “Ranged Program Analysis via Instrumentation”. In: Proc. SEFM. Vol. 14323. 2023, pp. 145–164. doi: 10.1007/978-3-031-47115-5_9.</div> <div>- Jan Haltermann, Marie-Christine Jakobs, Cedric Richter, and Heike Wehrheim. “Parallel program analysis on path ranges”. In: Sci. Comput. Program. 238 (2024). doi: 10.1016/j.scico.2024.103154.</div> <p> </p> <div>More precisely, it contains all the results from the PhD-thesis of Jan Haltermann.</div> <div>In more detail, it contains all experimental data collected during the experiments, the run-configs to re-run the experiments, the instructions on how to regenerate the BenchExec tables that are used for analysis of the data, and the scripts to reconstruct all the findings from the thesis.</div> <p> </p> <div>It is structured as follows:</div> <div>- `configs` contains all the BenchExec run configs needed to rerun the experiments.</div> <div>- `data` contains the raw data collected during the experiments.</div> <div>- `figures` contains the generated figures</div> <div>- `macros` contains the macros for the Latex document with the evaluation results</div> <div>- `overview-table.xml` is needed to generate the BenchExec result tables.</div> <div>- `scripts` contains the scripts to analyze the results and generate the figures</div> <div>- `tables` contains the tables generated using the raw data and are used for analyzing the results</div> <div>- `used-tools` contains the executables of the tools used for the evaluation (in this case only CPAchecker)</div> <div>- `validation_of_incorrect_results.zip` contains the results of the manual analysis of the incorrect alarms generated, as explained in the paper.</div> <p> </p> <div>The version of CoVeriTeam used can be found [on GitLab](https://gitlab.com/sosy-lab/software/coveriteam/-/tree/rangedAnalysis?ref_type=heads) </div> <div>The latest source code of CPAchecker used can be found [on GitLab](https://gitlab.com/sosy-lab/software/cpachecker/-/tree/ranged_program_analysis)</div> <p><br><br><br><br></p>
FIGURE 10 in An analysis of fossil identification guides to improve data reporting in citizen science programs
FIGURE 10. An example of a †Cosmopolitodus hastalis photo enhanced by illustration.
Fig. 4 in Towards incorporating insect isotope analysis using cavity ring-down spectroscopy into area-wide insect pest management programs
Fig. 4. Decision tree to select an option for using isotopes in an operational program.
Paper: "Sensitivity analysis for linear changes of the constraint matrix of a linear program" output
<p>Output generated from the experiments in the paper "Sensitivity analysis for linear changes of the constraint matrix of a linear program"</p>
Supplementary web page for the paper "SEAL: Integrating Program Analysis and Repository Mining"
<p>This is an archive of the supplementary material for the paper “SEAL: Integrating Program Analysis and Repository Mining” including the website and dataset. The website can also be viewed here: <a href="https://se-sic.github.io/paper-SEAL/">https://se-sic.github.io/paper-SEAL/</a></p>
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