Semantic Versioning for Python Programs

Authors: Carvalho, Luís

Contributors: NOVALincs, RUN

Subject Terms: Software evolution, type theory, Artificial Intelligence, Human-Computer Interaction, Software

File Description: application/pdf

Relation: 979-8-4007-0384-3; PURE: 83888407

Availability: http://hdl.handle.net/10362/164728

A Scaffolded Approach for Tracing Control-Flow in Simplified Python Programs

Authors: Kulindala, Gnaneswar, Srikanth, Anushka, Choppella, Venkatesh

Source: Proceedings of the 30th ACM Conference on Innovation and Technology in Computer Science Education V. 1. :51-57

Availability: http://dl.acm.org/doi/10.1145/3724363.3729044

Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices

Authors: Khan, Shehroz, Sudheerbabu, Gaadha, Staicu, Bianca Elena, Ahmad, Tanwir, Truscan, Dragos

Source: 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) Software Testing, Verification and Validation Workshops (ICSTW), 2025 IEEE International Conference on. :217-225 Mar, 2025

Relation: 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

FixKit: A Program Repair Collection for Python

Authors: Smytzek, Marius, Eberlein, Martin, Werk, Kai, Grunske, Lars, Zeller, Andreas

Source: 2024 39th IEEE/ACM International Conference on Automated Software Engineering (ASE) ASE Automated Software Engineering (ASE), 2024 39th IEEE/ACM International Conference on. :2342-2345 Oct, 2024

Relation: 2024 39th IEEE/ACM International Conference on Automated Software Engineering (ASE)

Towards understanding the security issues of Python programs

Authors: Fan, Hongcheng, Liu, Di, Wu, Jielun, Feng, Yang, Shi, Qingkai, Xu, Baowen

Source: Proceedings of the 16th International Conference on Internetware. :1-12

Availability: http://dl.acm.org/doi/10.1145/3755881.3755886

RetypeR: Integrated Retrieval-based Automatic Program Repair for Python Type Errors

Authors: Hao, Sichong, Shi, Xianjun, Liu, Hongwei

Source: 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME) ICSME Software Maintenance and Evolution (ICSME), 2024 IEEE International Conference on. :199-210 Oct, 2024

Relation: 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Student Perceptions of Learning through Original and AI-Generated Python Programs from a Software Quality Perspective

Authors: Mark Frydenberg, Anqi Xu, Jennifer Xu

Source: Information Systems Education Journal. 2025 23(4):34-56.

Peer Reviewed: Y

Page Count: 23

Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance, Artificial Intelligence, Computer Science Education, Evaluation, Introductory Courses, Problem Based Learning, Coding, College Students

Leveraging LLMs for abstracting UML and OCL representations from Java and Python programs

Authors: Siala, Hanan Abdulwahab ^⁎, Lano, Kevin

Source: In The Journal of Systems & Software August 2026 238

ESBMC-Python: A Bounded Model Checker for Python Programs

Authors: Farias, Bruno, Menezes, Rafael, de Lima Filho, Eddie B., Sun, Youcheng, Cordeiro, Lucas C.

Source: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis. :1836-1840

Availability: http://dl.acm.org/doi/10.1145/3650212.3685304

An Error-Aware Automatic Grading Framework for Python Programs Based on Structural-Semantic Similarity

Authors: Xue Han, Jinwei Wang, Jiayi Che

Source: 2025 6th International Conference on Information Science and Education (ICISE-IE). :294-298

The Fascinating Path of Prime Numbers - With Python programs

Authors: Gabbianelli, Silvio

Empirical Evaluation of Maintainability Index Accuracy for Measuring Maintainability of Python Programs*

Authors: Morrison, Rachael, Wedyan, Fadi, Abuomar, Osama Sam

Source: 2023 Tenth International Conference on Software Defined Systems (SDS) Software Defined Systems (SDS), 2023 Tenth International Conference on. :1-5 Oct, 2023

Relation: 2023 Tenth International Conference on Software Defined Systems (SDS)

Discovering Parallelisms in Python Programs

Authors: Wei, Siwei, Song, Guyang, Zhu, Senlin, Ruan, Ruoyi, Zhu, Shihao, Cai, Yan

Source: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. :832-844

Availability: http://dl.acm.org/doi/10.1145/3611643.3616259

Type-aware LLM-based Regression Test Generation for Python Programs

Authors: Liu, Runlin, Zhang, Zhe, Hu, Yunge, Lin, Yuhang, Gao, Xiang, Sun, Hailong

Subject Terms: Software Engineering

Access URL: http://arxiv.org/abs/2503.14000

How Dynamic Features Affect API Usages? An Empirical Study of API Misuses in Python Programs

Authors: He, Xincheng, Liu, Xiaojin, Xu, Lei, Xu, Baowen

Source: 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) SANER Software Analysis, Evolution and Reengineering (SANER), 2023 IEEE International Conference on. :522-533 Mar, 2023

Relation: 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

Using LLMs to Extract UML Class Diagrams from Java and Python Programs:An Empirical Study

Authors: Siala, Hanan, Lano, Kevin

Source: Siala, H & Lano, K 2025, 'Using LLMs to Extract UML Class Diagrams from Java and Python Programs : An Empirical Study', CEUR Workshop Proceedings, vol. 4122.

Subject Terms: Unified Modeling Language (UML), Machine Learning, Python programs, Model-driven Reverse Engineering (MDRE), UML Class Diagram, Large Language Models (LLMs), Java programs

File Description: application/pdf

Access URL: https://kclpure.kcl.ac.uk/ws/files/362383754/Using_LLMs_to_extract_UML_class_diagrams_from_Java_and_Version_of_Record.pdf
https://kclpure.kcl.ac.uk/portal/en/publications/73e37044-11bc-48ac-8cff-42d183c617b6
https://ceur-ws.org/Vol-4122/

Using LLMs to Extract OCL Specifications from Java and Python Programs:An Empirical Study

Authors: Siala, Hanan, Lano, Kevin

Source: Siala, H & Lano, K 2025, 'Using LLMs to Extract OCL Specifications from Java and Python Programs : An Empirical Study', CEUR Workshop Proceedings, vol. 4122.

Subject Terms: Machine Learning, Python programs, Object Constraint Language (OCL), Large Language Models (LLMs), Java programs, Reverse engineering

File Description: application/pdf

Access URL: https://kclpure.kcl.ac.uk/ws/files/362382813/Using_LLMs_to_extract_OCL_specifications_from_Java_and_Python_programs_Version_of_Record.pdf
https://kclpure.kcl.ac.uk/portal/en/publications/1badd32b-4bb5-4104-8a41-f0d7543d96bc
https://ceur-ws.org/Vol-4122/

Localizer: A Visual Debugging Assistant for Python Programs

Authors: Khan, Shehroz, Sudheerbabu, Gaadha, Truscan, Dragos, Ahmad, Tanwir

Source: Proceedings of the 2nd ACM International Workshop on Future Debugging Techniques. :34-35

Availability: http://dl.acm.org/doi/10.1145/3678720.3685321

Poster: Improving Spectrum Based Fault Localization For Python Programs Using Weighted Code Elements

Authors: Sarhan, Qusay Idrees, Beszedes, Arpad

Source: 2023 IEEE Conference on Software Testing, Verification and Validation (ICST) ICST Software Testing, Verification and Validation (ICST), 2023 IEEE Conference on. :478-481 Apr, 2023

Relation: 2023 IEEE Conference on Software Testing, Verification and Validation (ICST)

An Approach for Automatically Generating Traces for Python Programs

Authors: Zhong, Xiaoting, Zhang, Nan, Duan, Zhenhua

Source: 2022 9th International Conference on Dependable Systems and Their Applications (DSA) DSA Dependable Systems and Their Applications (DSA), 2022 9th International Conference on. :262-268 Aug, 2022

Relation: 2022 9th International Conference on Dependable Systems and Their Applications (DSA)