---
_id: '62973'
abstract:
- lang: eng
  text: "Large Language Models (LLMs) are increasingly being explored for their potential
    in software engineering, particularly in static analysis tasks. In this study,
    we investigate the potential of current LLMs to enhance call-graph analysis and
    type inference for Python and JavaScript programs. We empirically evaluated 24
    LLMs, including OpenAI's GPT series and open-source models like LLaMA and Mistral,
    using existing and newly developed benchmarks. Specifically, we enhanced TypeEvalPy,
    a micro-benchmarking framework for type inference in Python, with auto-generation
    capabilities, expanding its scope from 860 to 77,268 type annotations for Python.
    Additionally, we introduced SWARM-CG and SWARM-JS, comprehensive benchmarking
    suites for evaluating call-graph construction tools across multiple programming
    languages.\r\n Our findings reveal a contrasting performance of LLMs in static
    analysis tasks. For call-graph generation, traditional static analysis tools such
    as PyCG for Python and Jelly for JavaScript consistently outperform LLMs. While
    advanced models like mistral-large-it-2407-123b and gpt-4o show promise, they
    still struggle with completeness and soundness in call-graph analysis across both
    languages. In contrast, LLMs demonstrate a clear advantage in type inference for
    Python, surpassing traditional tools like HeaderGen and hybrid approaches such
    as HiTyper. These results suggest that, while LLMs hold promise in type inference,
    their limitations in call-graph analysis highlight the need for further research.
    Our study provides a foundation for integrating LLMs into static analysis workflows,
    offering insights into their strengths and current limitations."
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Rose
  full_name: Sunil, Rose
  id: '97670'
  last_name: Sunil
- first_name: Samkutty
  full_name: Sabu, Samkutty
  last_name: Sabu
- first_name: Amir M.
  full_name: Mir, Amir M.
  last_name: Mir
- first_name: Sofia
  full_name: Reis, Sofia
  last_name: Reis
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
citation:
  ama: Shivarpatna Venkatesh AP, Sunil R, Sabu S, Mir AM, Reis S, Bodden E. An Empirical
    Study of Large Language Models for Type and Call Graph Analysis in Python and
    JavaScript. <i>Empirical Software Engineering</i>. 2025;30(6). doi:<a href="https://doi.org/10.48550/ARXIV.2410.00603">10.48550/ARXIV.2410.00603</a>
  apa: Shivarpatna Venkatesh, A. P., Sunil, R., Sabu, S., Mir, A. M., Reis, S., &#38;
    Bodden, E. (2025). An Empirical Study of Large Language Models for Type and Call
    Graph Analysis in Python and JavaScript. <i>Empirical Software Engineering</i>,
    <i>30</i>(6). <a href="https://doi.org/10.48550/ARXIV.2410.00603">https://doi.org/10.48550/ARXIV.2410.00603</a>
  bibtex: '@article{Shivarpatna Venkatesh_Sunil_Sabu_Mir_Reis_Bodden_2025, title={An
    Empirical Study of Large Language Models for Type and Call Graph Analysis in Python
    and JavaScript}, volume={30}, DOI={<a href="https://doi.org/10.48550/ARXIV.2410.00603">10.48550/ARXIV.2410.00603</a>},
    number={6}, journal={Empirical Software Engineering}, publisher={Springer}, author={Shivarpatna
    Venkatesh, Ashwin Prasad and Sunil, Rose and Sabu, Samkutty and Mir, Amir M. and
    Reis, Sofia and Bodden, Eric}, year={2025} }'
  chicago: Shivarpatna Venkatesh, Ashwin Prasad, Rose Sunil, Samkutty Sabu, Amir M.
    Mir, Sofia Reis, and Eric Bodden. “An Empirical Study of Large Language Models
    for Type and Call Graph Analysis in Python and JavaScript.” <i>Empirical Software
    Engineering</i> 30, no. 6 (2025). <a href="https://doi.org/10.48550/ARXIV.2410.00603">https://doi.org/10.48550/ARXIV.2410.00603</a>.
  ieee: 'A. P. Shivarpatna Venkatesh, R. Sunil, S. Sabu, A. M. Mir, S. Reis, and E.
    Bodden, “An Empirical Study of Large Language Models for Type and Call Graph Analysis
    in Python and JavaScript,” <i>Empirical Software Engineering</i>, vol. 30, no.
    6, 2025, doi: <a href="https://doi.org/10.48550/ARXIV.2410.00603">10.48550/ARXIV.2410.00603</a>.'
  mla: Shivarpatna Venkatesh, Ashwin Prasad, et al. “An Empirical Study of Large Language
    Models for Type and Call Graph Analysis in Python and JavaScript.” <i>Empirical
    Software Engineering</i>, vol. 30, no. 6, Springer, 2025, doi:<a href="https://doi.org/10.48550/ARXIV.2410.00603">10.48550/ARXIV.2410.00603</a>.
  short: A.P. Shivarpatna Venkatesh, R. Sunil, S. Sabu, A.M. Mir, S. Reis, E. Bodden,
    Empirical Software Engineering 30 (2025).
date_created: 2025-12-08T13:20:30Z
date_updated: 2025-12-08T13:25:49Z
department:
- _id: '76'
doi: 10.48550/ARXIV.2410.00603
intvolume: '        30'
issue: '6'
language:
- iso: eng
publication: Empirical Software Engineering
publisher: Springer
status: public
title: An Empirical Study of Large Language Models for Type and Call Graph Analysis
  in Python and JavaScript
type: journal_article
user_id: '15249'
volume: 30
year: '2025'
...
---
_id: '53959'
abstract:
- lang: eng
  text: In light of the growing interest in type inference research for Python, both
    researchers and practitioners require a standardized process to assess the performance
    of various type inference techniques. This paper introduces TypeEvalPy, a comprehensive
    micro-benchmarking framework for evaluating type inference tools. TypeEvalPy contains
    154 code snippets with 845 type annotations across 18 categories that target various
    Python features. The framework manages the execution of containerized tools, transforms
    inferred types into a standardized format, and produces meaningful metrics for
    assessment. Through our analysis, we compare the performance of six type inference
    tools, highlighting their strengths and limitations. Our findings provide a foundation
    for further research and optimization in the domain of Python type inference.
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Samkutty
  full_name: Sabu, Samkutty
  last_name: Sabu
- first_name: Jiawei
  full_name: Wang, Jiawei
  last_name: Wang
- first_name: Amir M.
  full_name: Mir, Amir M.
  last_name: Mir
- first_name: Li
  full_name: Li, Li
  last_name: Li
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
citation:
  ama: 'Shivarpatna Venkatesh AP, Sabu S, Wang J, Mir AM, Li L, Bodden E. TypeEvalPy:
    A Micro-benchmarking Framework for Python Type Inference  Tools. In: <i>Proceedings
    of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion
    Proceedings</i>. ICSE-Companion 24. Association for Computing Machinery; 2024:49-53.
    doi:<a href="https://doi.org/10.1145/3639478.3640033">10.1145/3639478.3640033</a>'
  apa: 'Shivarpatna Venkatesh, A. P., Sabu, S., Wang, J., Mir, A. M., Li, L., &#38;
    Bodden, E. (2024). TypeEvalPy: A Micro-benchmarking Framework for Python Type
    Inference  Tools. <i>Proceedings of the 2024 IEEE/ACM 46th International Conference
    on Software Engineering: Companion Proceedings</i>, 49–53. <a href="https://doi.org/10.1145/3639478.3640033">https://doi.org/10.1145/3639478.3640033</a>'
  bibtex: '@inproceedings{Shivarpatna Venkatesh_Sabu_Wang_Mir_Li_Bodden_2024, place={New
    York, NY, USA}, series={ICSE-Companion 24}, title={TypeEvalPy: A Micro-benchmarking
    Framework for Python Type Inference  Tools}, DOI={<a href="https://doi.org/10.1145/3639478.3640033">10.1145/3639478.3640033</a>},
    booktitle={Proceedings of the 2024 IEEE/ACM 46th International Conference on Software
    Engineering: Companion Proceedings}, publisher={Association for Computing Machinery},
    author={Shivarpatna Venkatesh, Ashwin Prasad and Sabu, Samkutty and Wang, Jiawei
    and Mir, Amir M. and Li, Li and Bodden, Eric}, year={2024}, pages={49–53}, collection={ICSE-Companion
    24} }'
  chicago: 'Shivarpatna Venkatesh, Ashwin Prasad, Samkutty Sabu, Jiawei Wang, Amir
    M. Mir, Li Li, and Eric Bodden. “TypeEvalPy: A Micro-Benchmarking Framework for
    Python Type Inference  Tools.” In <i>Proceedings of the 2024 IEEE/ACM 46th International
    Conference on Software Engineering: Companion Proceedings</i>, 49–53. ICSE-Companion
    24. New York, NY, USA: Association for Computing Machinery, 2024. <a href="https://doi.org/10.1145/3639478.3640033">https://doi.org/10.1145/3639478.3640033</a>.'
  ieee: 'A. P. Shivarpatna Venkatesh, S. Sabu, J. Wang, A. M. Mir, L. Li, and E. Bodden,
    “TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference  Tools,”
    in <i>Proceedings of the 2024 IEEE/ACM 46th International Conference on Software
    Engineering: Companion Proceedings</i>, Lisbon, Portugal, 2024, pp. 49–53, doi:
    <a href="https://doi.org/10.1145/3639478.3640033">10.1145/3639478.3640033</a>.'
  mla: 'Shivarpatna Venkatesh, Ashwin Prasad, et al. “TypeEvalPy: A Micro-Benchmarking
    Framework for Python Type Inference  Tools.” <i>Proceedings of the 2024 IEEE/ACM
    46th International Conference on Software Engineering: Companion Proceedings</i>,
    Association for Computing Machinery, 2024, pp. 49–53, doi:<a href="https://doi.org/10.1145/3639478.3640033">10.1145/3639478.3640033</a>.'
  short: 'A.P. Shivarpatna Venkatesh, S. Sabu, J. Wang, A.M. Mir, L. Li, E. Bodden,
    in: Proceedings of the 2024 IEEE/ACM 46th International Conference on Software
    Engineering: Companion Proceedings, Association for Computing Machinery, New York,
    NY, USA, 2024, pp. 49–53.'
conference:
  location: Lisbon, Portugal
date_created: 2024-05-06T11:49:22Z
date_updated: 2024-08-05T07:49:33Z
department:
- _id: '76'
doi: 10.1145/3639478.3640033
external_id:
  arxiv:
  - '2312.16882'
language:
- iso: eng
page: 49-53
place: New York, NY, USA
publication: 'Proceedings of the 2024 IEEE/ACM 46th International Conference on Software
  Engineering: Companion Proceedings'
publication_identifier:
  isbn:
  - '9798400705021'
publisher: Association for Computing Machinery
series_title: ICSE-Companion 24
status: public
title: 'TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference  Tools'
type: conference
user_id: '15249'
year: '2024'
...
---
_id: '55516'
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Samkutty
  full_name: Sabu, Samkutty
  last_name: Sabu
- first_name: Amir M.
  full_name: Mir, Amir M.
  last_name: Mir
- first_name: Sofia
  full_name: Reis, Sofia
  last_name: Reis
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
citation:
  ama: 'Shivarpatna Venkatesh AP, Sabu S, Mir AM, Reis S, Bodden E. The Emergence
    of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks.
    In: <i>Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation
    Models and Software Engineering</i>. ACM; 2024. doi:<a href="https://doi.org/10.1145/3650105.3652288">10.1145/3650105.3652288</a>'
  apa: 'Shivarpatna Venkatesh, A. P., Sabu, S., Mir, A. M., Reis, S., &#38; Bodden,
    E. (2024). The Emergence of Large Language Models in Static Analysis: A First
    Look through Micro-Benchmarks. <i>Proceedings of the 2024 IEEE/ACM First International
    Conference on AI Foundation Models and Software Engineering</i>. <a href="https://doi.org/10.1145/3650105.3652288">https://doi.org/10.1145/3650105.3652288</a>'
  bibtex: '@inproceedings{Shivarpatna Venkatesh_Sabu_Mir_Reis_Bodden_2024, title={The
    Emergence of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks},
    DOI={<a href="https://doi.org/10.1145/3650105.3652288">10.1145/3650105.3652288</a>},
    booktitle={Proceedings of the 2024 IEEE/ACM First International Conference on
    AI Foundation Models and Software Engineering}, publisher={ACM}, author={Shivarpatna
    Venkatesh, Ashwin Prasad and Sabu, Samkutty and Mir, Amir M. and Reis, Sofia and
    Bodden, Eric}, year={2024} }'
  chicago: 'Shivarpatna Venkatesh, Ashwin Prasad, Samkutty Sabu, Amir M. Mir, Sofia
    Reis, and Eric Bodden. “The Emergence of Large Language Models in Static Analysis:
    A First Look through Micro-Benchmarks.” In <i>Proceedings of the 2024 IEEE/ACM
    First International Conference on AI Foundation Models and Software Engineering</i>.
    ACM, 2024. <a href="https://doi.org/10.1145/3650105.3652288">https://doi.org/10.1145/3650105.3652288</a>.'
  ieee: 'A. P. Shivarpatna Venkatesh, S. Sabu, A. M. Mir, S. Reis, and E. Bodden,
    “The Emergence of Large Language Models in Static Analysis: A First Look through
    Micro-Benchmarks,” 2024, doi: <a href="https://doi.org/10.1145/3650105.3652288">10.1145/3650105.3652288</a>.'
  mla: 'Shivarpatna Venkatesh, Ashwin Prasad, et al. “The Emergence of Large Language
    Models in Static Analysis: A First Look through Micro-Benchmarks.” <i>Proceedings
    of the 2024 IEEE/ACM First International Conference on AI Foundation Models and
    Software Engineering</i>, ACM, 2024, doi:<a href="https://doi.org/10.1145/3650105.3652288">10.1145/3650105.3652288</a>.'
  short: 'A.P. Shivarpatna Venkatesh, S. Sabu, A.M. Mir, S. Reis, E. Bodden, in: Proceedings
    of the 2024 IEEE/ACM First International Conference on AI Foundation Models and
    Software Engineering, ACM, 2024.'
date_created: 2024-08-05T09:12:59Z
date_updated: 2024-08-05T09:14:11Z
department:
- _id: '76'
doi: 10.1145/3650105.3652288
language:
- iso: eng
publication: Proceedings of the 2024 IEEE/ACM First International Conference on AI
  Foundation Models and Software Engineering
publication_status: published
publisher: ACM
status: public
title: 'The Emergence of Large Language Models in Static Analysis: A First Look through
  Micro-Benchmarks'
type: conference
user_id: '15249'
year: '2024'
...
---
_id: '41813'
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Jiawei
  full_name: Wang, Jiawei
  last_name: Wang
- first_name: Li
  full_name: Li, Li
  last_name: Li
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
citation:
  ama: 'Shivarpatna Venkatesh AP, Wang J, Li L, Bodden E. Enhancing Comprehension
    and Navigation in Jupyter Notebooks with Static Analysis. In: <i>IEEE International
    Conference on Software Analysis, Evolution and Reengineering (SANER)</i>. ; 2023.'
  apa: Shivarpatna Venkatesh, A. P., Wang, J., Li, L., &#38; Bodden, E. (2023). Enhancing
    Comprehension and Navigation in Jupyter Notebooks with Static Analysis. <i>IEEE
    International Conference on Software Analysis, Evolution and Reengineering (SANER)</i>.
  bibtex: '@inproceedings{Shivarpatna Venkatesh_Wang_Li_Bodden_2023, title={Enhancing
    Comprehension and Navigation in Jupyter Notebooks with Static Analysis}, booktitle={IEEE
    International Conference on Software Analysis, Evolution and Reengineering (SANER)},
    author={Shivarpatna Venkatesh, Ashwin Prasad and Wang, Jiawei and Li, Li and Bodden,
    Eric}, year={2023} }'
  chicago: Shivarpatna Venkatesh, Ashwin Prasad, Jiawei Wang, Li Li, and Eric Bodden.
    “Enhancing Comprehension and Navigation in Jupyter Notebooks with Static Analysis.”
    In <i>IEEE International Conference on Software Analysis, Evolution and Reengineering
    (SANER)</i>, 2023.
  ieee: A. P. Shivarpatna Venkatesh, J. Wang, L. Li, and E. Bodden, “Enhancing Comprehension
    and Navigation in Jupyter Notebooks with Static Analysis,” 2023.
  mla: Shivarpatna Venkatesh, Ashwin Prasad, et al. “Enhancing Comprehension and Navigation
    in Jupyter Notebooks with Static Analysis.” <i>IEEE International Conference on
    Software Analysis, Evolution and Reengineering (SANER)</i>, 2023.
  short: 'A.P. Shivarpatna Venkatesh, J. Wang, L. Li, E. Bodden, in: IEEE International
    Conference on Software Analysis, Evolution and Reengineering (SANER), 2023.'
date_created: 2023-02-06T10:44:08Z
date_updated: 2023-02-06T10:46:00Z
department:
- _id: '76'
language:
- iso: eng
publication: IEEE International Conference on Software Analysis, Evolution and Reengineering
  (SANER)
status: public
title: Enhancing Comprehension and Navigation in Jupyter Notebooks with Static Analysis
type: conference
user_id: '15249'
year: '2023'
...
---
_id: '36522'
abstract:
- lang: eng
  text: "Jupyter notebooks enable developers to interleave code snippets with rich-text
    and in-line visualizations. Data scientists use Jupyter notebook as the de-facto
    standard for creating and sharing machine-learning based solutions, primarily
    written in Python. Recent studies have demonstrated, however, that a large portion
    of Jupyter notebooks available on public platforms are undocumented and lacks
    a narrative structure. This reduces the readability of these notebooks. To address
    this shortcoming, this paper presents HeaderGen, a novel tool-based approach that
    automatically annotates code cells with categorical markdown headers based on
    a taxonomy of machine-learning operations, and classifies and displays function
    calls according to this taxonomy. For this functionality to be realized, HeaderGen
    enhances an existing call graph analysis in PyCG. To improve precision, HeaderGen
    extends PyCG's analysis with support for handling external library code and flow-sensitivity.
    The former is realized by facilitating the resolution of function return-types.
    Furthermore, HeaderGen uses type information to perform pattern matching on code
    syntax to annotate code cells.\r\nThe evaluation on 15 real-world Jupyter notebooks
    from Kaggle shows that HeaderGen's underlying call graph analysis yields high
    accuracy (96.4% precision and 95.9% recall). This is because HeaderGen can resolve
    return-types of external libraries where existing type inference tools such as
    pytype (by Google), pyright (by Microsoft), and Jedi fall short. The header generation
    has a precision of 82.2% and a recall rate of 96.8% with regard to headers created
    manually by experts. In a user study, HeaderGen helps participants finish comprehension
    and navigation tasks faster. All participants clearly perceive HeaderGen as useful
    to their task."
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Jiawei
  full_name: Wang, Jiawei
  last_name: Wang
- first_name: Li
  full_name: Li, Li
  last_name: Li
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
citation:
  ama: 'Shivarpatna Venkatesh AP, Wang J, Li L, Bodden E. Enhancing Comprehension
    and Navigation in Jupyter Notebooks with Static Analysis. In: IEEE SANER 2023
    (International Conference on Software Analysis, Evolution and Reengineering);
    2023. doi:<a href="https://doi.org/10.48550/ARXIV.2301.04419">10.48550/ARXIV.2301.04419</a>'
  apa: Shivarpatna Venkatesh, A. P., Wang, J., Li, L., &#38; Bodden, E. (2023). <i>Enhancing
    Comprehension and Navigation in Jupyter Notebooks with Static Analysis</i>. IEEE
    SANER 2023 (International Conference on Software Analysis, Evolution and Reengineering).
    <a href="https://doi.org/10.48550/ARXIV.2301.04419">https://doi.org/10.48550/ARXIV.2301.04419</a>
  bibtex: '@inproceedings{Shivarpatna Venkatesh_Wang_Li_Bodden_2023, title={Enhancing
    Comprehension and Navigation in Jupyter Notebooks with Static Analysis}, DOI={<a
    href="https://doi.org/10.48550/ARXIV.2301.04419">10.48550/ARXIV.2301.04419</a>},
    publisher={IEEE SANER 2023 (International Conference on Software Analysis, Evolution
    and Reengineering)}, author={Shivarpatna Venkatesh, Ashwin Prasad and Wang, Jiawei
    and Li, Li and Bodden, Eric}, year={2023} }'
  chicago: Shivarpatna Venkatesh, Ashwin Prasad, Jiawei Wang, Li Li, and Eric Bodden.
    “Enhancing Comprehension and Navigation in Jupyter Notebooks with Static Analysis.”
    IEEE SANER 2023 (International Conference on Software Analysis, Evolution and
    Reengineering), 2023. <a href="https://doi.org/10.48550/ARXIV.2301.04419">https://doi.org/10.48550/ARXIV.2301.04419</a>.
  ieee: 'A. P. Shivarpatna Venkatesh, J. Wang, L. Li, and E. Bodden, “Enhancing Comprehension
    and Navigation in Jupyter Notebooks with Static Analysis,” presented at the IEEE
    SANER 2023 (International Conference on Software Analysis, Evolution and Reengineering),
    2023, doi: <a href="https://doi.org/10.48550/ARXIV.2301.04419">10.48550/ARXIV.2301.04419</a>.'
  mla: Shivarpatna Venkatesh, Ashwin Prasad, et al. <i>Enhancing Comprehension and
    Navigation in Jupyter Notebooks with Static Analysis</i>. IEEE SANER 2023 (International
    Conference on Software Analysis, Evolution and Reengineering), 2023, doi:<a href="https://doi.org/10.48550/ARXIV.2301.04419">10.48550/ARXIV.2301.04419</a>.
  short: 'A.P. Shivarpatna Venkatesh, J. Wang, L. Li, E. Bodden, in: IEEE SANER 2023
    (International Conference on Software Analysis, Evolution and Reengineering),
    2023.'
conference:
  name: IEEE SANER 2023 (International Conference on Software Analysis, Evolution
    and Reengineering)
date_created: 2023-01-13T08:03:26Z
date_updated: 2025-04-07T10:18:03Z
ddc:
- '000'
doi: 10.48550/ARXIV.2301.04419
file:
- access_level: open_access
  content_type: application/pdf
  creator: ashwin
  date_created: 2023-01-26T10:48:40Z
  date_updated: 2023-01-26T10:48:40Z
  file_id: '40304'
  file_name: 2301.04419.pdf
  file_size: 1862440
  relation: main_file
file_date_updated: 2023-01-26T10:48:40Z
has_accepted_license: '1'
keyword:
- static analysis
- python
- code comprehension
- annotation
- literate programming
- jupyter notebook
language:
- iso: eng
oa: '1'
publisher: IEEE SANER 2023 (International Conference on Software Analysis, Evolution
  and Reengineering)
status: public
title: Enhancing Comprehension and Navigation in Jupyter Notebooks with Static Analysis
type: conference
user_id: '15249'
year: '2023'
...
---
_id: '22462'
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Eric
  full_name: Bodden, Eric
  id: '59256'
  last_name: Bodden
  orcid: 0000-0003-3470-3647
citation:
  ama: 'Shivarpatna Venkatesh AP, Bodden E. Automated Cell Header Generator for Jupyter
    Notebooks. In: <i>International Workshop on AI and Software Testing/Analysis (AISTA)</i>.
    ; 2021. doi:<a href="https://doi.org/10.1145/3464968.3468410">10.1145/3464968.3468410</a>'
  apa: Shivarpatna Venkatesh, A. P., &#38; Bodden, E. (2021). Automated Cell Header
    Generator for Jupyter Notebooks. <i>International Workshop on AI and Software
    Testing/Analysis (AISTA)</i>. <a href="https://doi.org/10.1145/3464968.3468410">https://doi.org/10.1145/3464968.3468410</a>
  bibtex: '@inproceedings{Shivarpatna Venkatesh_Bodden_2021, title={Automated Cell
    Header Generator for Jupyter Notebooks}, DOI={<a href="https://doi.org/10.1145/3464968.3468410">10.1145/3464968.3468410</a>},
    booktitle={International Workshop on AI and Software Testing/Analysis (AISTA)},
    author={Shivarpatna Venkatesh, Ashwin Prasad and Bodden, Eric}, year={2021} }'
  chicago: Shivarpatna Venkatesh, Ashwin Prasad, and Eric Bodden. “Automated Cell
    Header Generator for Jupyter Notebooks.” In <i>International Workshop on AI and
    Software Testing/Analysis (AISTA)</i>, 2021. <a href="https://doi.org/10.1145/3464968.3468410">https://doi.org/10.1145/3464968.3468410</a>.
  ieee: 'A. P. Shivarpatna Venkatesh and E. Bodden, “Automated Cell Header Generator
    for Jupyter Notebooks,” 2021, doi: <a href="https://doi.org/10.1145/3464968.3468410">10.1145/3464968.3468410</a>.'
  mla: Shivarpatna Venkatesh, Ashwin Prasad, and Eric Bodden. “Automated Cell Header
    Generator for Jupyter Notebooks.” <i>International Workshop on AI and Software
    Testing/Analysis (AISTA)</i>, 2021, doi:<a href="https://doi.org/10.1145/3464968.3468410">10.1145/3464968.3468410</a>.
  short: 'A.P. Shivarpatna Venkatesh, E. Bodden, in: International Workshop on AI
    and Software Testing/Analysis (AISTA), 2021.'
date_created: 2021-06-17T10:14:48Z
date_updated: 2025-04-07T10:21:29Z
department:
- _id: '76'
doi: 10.1145/3464968.3468410
language:
- iso: eng
publication: International Workshop on AI and Software Testing/Analysis (AISTA)
status: public
title: Automated Cell Header Generator for Jupyter Notebooks
type: conference
user_id: '15249'
year: '2021'
...
---
_id: '16726'
author:
- first_name: Hadi
  full_name: Razzaghi Kouchaksaraei, Hadi
  id: '60845'
  last_name: Razzaghi Kouchaksaraei
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: Amey
  full_name: Churi, Amey
  last_name: Churi
- first_name: Marvin
  full_name: Illian, Marvin
  id: '44169'
  last_name: Illian
- first_name: Holger
  full_name: Karl, Holger
  id: '126'
  last_name: Karl
citation:
  ama: 'Razzaghi Kouchaksaraei H, Shivarpatna Venkatesh AP, Churi A, Illian M, Karl
    H. Dynamic Provisioning of Network Services on Heterogeneous Resources. In: <i>European
    Conference on Networks and Communications (EUCNC 2020)</i>.'
  apa: Razzaghi Kouchaksaraei, H., Shivarpatna Venkatesh, A. P., Churi, A., Illian,
    M., &#38; Karl, H. (n.d.). Dynamic Provisioning of Network Services on Heterogeneous
    Resources. In <i>European Conference on Networks and Communications (EUCNC 2020)</i>.
  bibtex: '@inproceedings{Razzaghi Kouchaksaraei_Shivarpatna Venkatesh_Churi_Illian_Karl,
    title={Dynamic Provisioning of Network Services on Heterogeneous Resources}, booktitle={European
    Conference on Networks and Communications (EUCNC 2020)}, author={Razzaghi Kouchaksaraei,
    Hadi and Shivarpatna Venkatesh, Ashwin Prasad and Churi, Amey and Illian, Marvin
    and Karl, Holger} }'
  chicago: Razzaghi Kouchaksaraei, Hadi, Ashwin Prasad Shivarpatna Venkatesh, Amey
    Churi, Marvin Illian, and Holger Karl. “Dynamic Provisioning of Network Services
    on Heterogeneous Resources.” In <i>European Conference on Networks and Communications
    (EUCNC 2020)</i>, n.d.
  ieee: H. Razzaghi Kouchaksaraei, A. P. Shivarpatna Venkatesh, A. Churi, M. Illian,
    and H. Karl, “Dynamic Provisioning of Network Services on Heterogeneous Resources,”
    in <i>European Conference on Networks and Communications (EUCNC 2020)</i>.
  mla: Razzaghi Kouchaksaraei, Hadi, et al. “Dynamic Provisioning of Network Services
    on Heterogeneous Resources.” <i>European Conference on Networks and Communications
    (EUCNC 2020)</i>.
  short: 'H. Razzaghi Kouchaksaraei, A.P. Shivarpatna Venkatesh, A. Churi, M. Illian,
    H. Karl, in: European Conference on Networks and Communications (EUCNC 2020),
    n.d.'
conference:
  end_date: 2020-06-18
  name: European Conference on Networks and Communications (EUCNC 2020)
  start_date: 2020-06-15
date_created: 2020-04-20T09:36:53Z
date_updated: 2022-01-06T06:52:55Z
department:
- _id: '34'
language:
- iso: eng
project:
- _id: '23'
  grant_number: '762057'
  name: 5G Programmable Infrastructure Converging disaggregated neTwork and compUte
    Resources
- _id: '4'
  name: SFB 901 - Project Area C
- _id: '16'
  name: SFB 901 - Subproject C4
- _id: '1'
  name: SFB 901
publication: European Conference on Networks and Communications (EUCNC 2020)
publication_status: accepted
status: public
title: Dynamic Provisioning of Network Services on Heterogeneous Resources
type: conference
user_id: '60845'
year: '2020'
...
---
_id: '20341'
abstract:
- lang: eng
  text: "When implementing secure software, developers must ensure certain\r\nrequirements,
    such as the erasure of secret data after its use and execution in\r\nreal time.
    Such requirements are not explicitly captured by the C language and\r\ncould potentially
    be violated by compiler optimizations. As a result,\r\ndevelopers typically use
    indirect methods to hide their code's semantics from\r\nthe compiler and avoid
    unwanted optimizations. However, such workarounds are\r\nnot permanent solutions,
    as increasingly efficient compiler optimization causes\r\ncode that was considered
    secure in the past now vulnerable. This paper is a\r\nliterature review of (1)
    the security complications caused by compiler\r\noptimizations, (2) approaches
    used by developers to mitigate optimization\r\nproblems, and (3) recent academic
    efforts towards enabling security engineers\r\nto communicate implicit security
    requirements to the compiler. In addition, we\r\npresent a short study of six
    cryptographic libraries and how they approach the\r\nissue of ensuring security
    requirements. With this paper, we highlight the need\r\nfor software developers
    and compiler designers to work together in order to\r\ndesign efficient systems
    for writing secure software."
author:
- first_name: Ashwin Prasad
  full_name: Shivarpatna Venkatesh, Ashwin Prasad
  id: '66637'
  last_name: Shivarpatna Venkatesh
- first_name: A. Bhat
  full_name: Handadi, A. Bhat
  last_name: Handadi
- first_name: Martin
  full_name: Mory, Martin
  id: '65667'
  last_name: Mory
  orcid: 0000-0001-5609-0031
citation:
  ama: Shivarpatna Venkatesh AP, Handadi AB, Mory M. Security Implications Of Compiler
    Optimizations On Cryptography -- A  Review. <i>arXiv:190702530</i>. 2019.
  apa: Shivarpatna Venkatesh, A. P., Handadi, A. B., &#38; Mory, M. (2019). Security
    Implications Of Compiler Optimizations On Cryptography -- A  Review. <i>ArXiv:1907.02530</i>.
  bibtex: '@article{Shivarpatna Venkatesh_Handadi_Mory_2019, title={Security Implications
    Of Compiler Optimizations On Cryptography -- A  Review}, journal={arXiv:1907.02530},
    author={Shivarpatna Venkatesh, Ashwin Prasad and Handadi, A. Bhat and Mory, Martin},
    year={2019} }'
  chicago: Shivarpatna Venkatesh, Ashwin Prasad, A. Bhat Handadi, and Martin Mory.
    “Security Implications Of Compiler Optimizations On Cryptography -- A  Review.”
    <i>ArXiv:1907.02530</i>, 2019.
  ieee: A. P. Shivarpatna Venkatesh, A. B. Handadi, and M. Mory, “Security Implications
    Of Compiler Optimizations On Cryptography -- A  Review,” <i>arXiv:1907.02530</i>.
    2019.
  mla: Shivarpatna Venkatesh, Ashwin Prasad, et al. “Security Implications Of Compiler
    Optimizations On Cryptography -- A  Review.” <i>ArXiv:1907.02530</i>, 2019.
  short: A.P. Shivarpatna Venkatesh, A.B. Handadi, M. Mory, ArXiv:1907.02530 (2019).
date_created: 2020-11-11T17:46:16Z
date_updated: 2022-01-06T06:54:26Z
ddc:
- '000'
file:
- access_level: closed
  content_type: application/pdf
  creator: ashwin
  date_created: 2021-02-17T11:39:14Z
  date_updated: 2021-02-17T11:39:14Z
  file_id: '21255'
  file_name: 1907.02530.pdf
  file_size: 663876
  relation: main_file
  success: 1
file_date_updated: 2021-02-17T11:39:14Z
has_accepted_license: '1'
language:
- iso: eng
publication: arXiv:1907.02530
status: public
title: Security Implications Of Compiler Optimizations On Cryptography -- A  Review
type: preprint
user_id: '66637'
year: '2019'
...