Pouria Alikhanifard

dblp:372/1520 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2025
0009-0005-9816-8032ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
2 papers
Software maintenance and evolution · 58% Empirical software engineering · 42%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering
mining software repositories
1.022025
Refactoring-Aware Block Tracking in Commit History · IEEE Trans. Software Eng. 2024
A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools · ACM Trans. Softw. Eng. Methodol. 2025
Software maintenance and evolution › program differencing
abstract syntax tree differencing
0.912025
A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools · ACM Trans. Softw. Eng. Methodol. 2025
Software maintenance and evolution
code review
0.912025
A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools · ACM Trans. Softw. Eng. Methodol. 2025
Software maintenance and evolution
refactoring
0.912025
A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools · ACM Trans. Softw. Eng. Methodol. 2025
Software maintenance and evolution › refactoring
refactoring detection
0.912025
A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools · ACM Trans. Softw. Eng. Methodol. 2025
Empirical software engineering › mining software repositories › version history analysis
code change history
0.812024
Refactoring-Aware Block Tracking in Commit History · IEEE Trans. Software Eng. 2024
Empirical software engineering › mining software repositories › version history analysis
commit history analysis
0.812024
Refactoring-Aware Block Tracking in Commit History · IEEE Trans. Software Eng. 2024

Methods — techniques the papers use, named apart from their topics

refactoringminer · 0.9abstract syntax tree matching · 0.9abstract syntax tree diffing · 0.8
YearPublicationVenuePosition
2025 A Novel Refactoring and Semantic Aware Abstract Syntax Tree Differencing Tool and a Benchmark for Evaluating the Accuracy of Diff Tools
abstract
Software undergoes constant changes to support new requirements, address bugs, enhance performance, and ensure maintainability. Thus, developers spend a great portion of their workday trying to understand and review the code changes of their teammates. Abstract Syntax Tree (AST) diff tools were developed to overcome the limitations of line-based diff tools, which are used by the majority of developers. Despite the notable improvements brought by AST diff tools in understanding complex changes, they still suffer from serious limitations, such as (1) lacking multi-mapping support, (2) matching semantically incompatible AST nodes, (3) ignoring language clues to guide the matching process, (4) lacking refactoring awareness, and (5) lacking commit-level diff support. We propose a novel AST diff tool based on RefactoringMiner that resolves all aforementioned limitations. First, we improved RefactoringMiner to increase its statement mapping accuracy, and then we developed an algorithm that generates AST diff for a given commit or pull request based on the refactoring instances and pairs of matched program element declarations provided by RefactoringMiner. To evaluate the accuracy of our tool and compare it with the state-of-the-art tools, we created the first benchmark of AST node mappings, including 800 bug-fixing commits and 188 refactoring commits. Our evaluation showed that our tool achieved a considerably higher precision and recall, especially for refactoring commits, with an execution time that is comparable with that of the faster tools.
Pouria Alikhanifard, Nikolaos Tsantalis
ACM Trans. Softw. Eng. Methodol.1
2024 Refactoring-Aware Block Tracking in Commit History
abstract
Tracking the change history of statements in the commits of a project repository is in many cases useful for supporting various software maintenance, comprehension, and evolution tasks. A high level of accuracy can facilitate the adoption of code tracking tools by developers and researchers. To this end, we propose CodeTracker, a refactoring-aware tool that can generate the commit change history for code blocks. To evaluate its accuracy, we created an oracle with the change history of 1,280 code blocks found within 200 methods from 20 popular open-source project repositories. Moreover, we created a baseline based on the current state-of-the-art Abstract Syntax Tree diff tool, namely GumTree 3.0, in order to compare the accuracy and execution time. Our experiments have shown that CodeTracker has a considerably higher precision/recall and faster execution time than the GumTree-based baseline, and can extract the complete change history of a code block with a precision and recall of 99.5% within 3.6 seconds on average.
Mohammed Tayeeb Hasan, Nikolaos Tsantalis, Pouria Alikhanifard
IEEE Trans. Software Eng.3