IEICE TRANSACTIONS on Information
Lightweight Operation History Graph for Traceability on Program Elements
Summary :
History data of edit operations are more beneficial than those stored in version control systems since they provide detailed information on how source code was changed. Meanwhile, a large number of recorded edit operations discourage developers and researchers from roughly understanding the changes. To assist with this task, it is desirable that they easily obtain traceability links for changed program elements over two source code snapshots before and after a code change. In this paper, we propose a graph representation called Operation History Graph (OHG), which presents code change information with such traceability links that are inferred from the history of edit operations. An OHG instance is generated by parsing any source code snapshot restored by edit histories and combining resultant abstract syntax trees (ASTs) into a single graph structure. To improve the performance of building graph instances, we avoided simply maintaining every program element. Any program element presenting the inner-structure of methods and non-changed elements are omitted. In addition, we adopted a lightweight static analysis for type name resolving to reduce required memory resource in the analysis while the accuracy of name resolving is preserved. Moreover, we assign a specific ID to each node and edge in the graph instance so that a part of the graph data can be separately stored and loaded on demand. These decisions make it feasible to build, manipulate, and store the graph with limited computer resources. To demonstrate the usefulness of the proposed operation history graph and verify whether detected traceability links are sufficient to reveal actual changes of program elements, we implemented tools to generate and manipulate OHG instances. The evaluation on graph generation performance shows that our tool can reduce the required computer resource as compared to another tool authors previously proposed. Moreover, the evaluation on traceability shows that OHG provides traceability links with sufficient accuracy as compared to the baseline approach using GumTree.
- Publication
- IEICE TRANSACTIONS on Information Vol.E104-D No.3 pp.404-418
- Publication Date
- 2021/03/01
- Publicized
- 2020/12/15
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2020EDP7129
- Type of Manuscript
- PAPER
- Category
- Software System
Authors
Takayuki OMORI
Ritsumeikan University
Katsuhisa MARUYAMA
Ritsumeikan University
Atsushi OHNISHI
Ritsumeikan University
Keyword
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Takayuki OMORI, Katsuhisa MARUYAMA, Atsushi OHNISHI, "Lightweight Operation History Graph for Traceability on Program Elements" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 3, pp. 404-418, March 2021, doi: 10.1587/transinf.2020EDP7129.
Abstract: History data of edit operations are more beneficial than those stored in version control systems since they provide detailed information on how source code was changed. Meanwhile, a large number of recorded edit operations discourage developers and researchers from roughly understanding the changes. To assist with this task, it is desirable that they easily obtain traceability links for changed program elements over two source code snapshots before and after a code change. In this paper, we propose a graph representation called Operation History Graph (OHG), which presents code change information with such traceability links that are inferred from the history of edit operations. An OHG instance is generated by parsing any source code snapshot restored by edit histories and combining resultant abstract syntax trees (ASTs) into a single graph structure. To improve the performance of building graph instances, we avoided simply maintaining every program element. Any program element presenting the inner-structure of methods and non-changed elements are omitted. In addition, we adopted a lightweight static analysis for type name resolving to reduce required memory resource in the analysis while the accuracy of name resolving is preserved. Moreover, we assign a specific ID to each node and edge in the graph instance so that a part of the graph data can be separately stored and loaded on demand. These decisions make it feasible to build, manipulate, and store the graph with limited computer resources. To demonstrate the usefulness of the proposed operation history graph and verify whether detected traceability links are sufficient to reveal actual changes of program elements, we implemented tools to generate and manipulate OHG instances. The evaluation on graph generation performance shows that our tool can reduce the required computer resource as compared to another tool authors previously proposed. Moreover, the evaluation on traceability shows that OHG provides traceability links with sufficient accuracy as compared to the baseline approach using GumTree.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020EDP7129/_p
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@ARTICLE{e104-d_3_404,
author={Takayuki OMORI, Katsuhisa MARUYAMA, Atsushi OHNISHI, },
journal={IEICE TRANSACTIONS on Information},
title={Lightweight Operation History Graph for Traceability on Program Elements},
year={2021},
volume={E104-D},
number={3},
pages={404-418},
abstract={History data of edit operations are more beneficial than those stored in version control systems since they provide detailed information on how source code was changed. Meanwhile, a large number of recorded edit operations discourage developers and researchers from roughly understanding the changes. To assist with this task, it is desirable that they easily obtain traceability links for changed program elements over two source code snapshots before and after a code change. In this paper, we propose a graph representation called Operation History Graph (OHG), which presents code change information with such traceability links that are inferred from the history of edit operations. An OHG instance is generated by parsing any source code snapshot restored by edit histories and combining resultant abstract syntax trees (ASTs) into a single graph structure. To improve the performance of building graph instances, we avoided simply maintaining every program element. Any program element presenting the inner-structure of methods and non-changed elements are omitted. In addition, we adopted a lightweight static analysis for type name resolving to reduce required memory resource in the analysis while the accuracy of name resolving is preserved. Moreover, we assign a specific ID to each node and edge in the graph instance so that a part of the graph data can be separately stored and loaded on demand. These decisions make it feasible to build, manipulate, and store the graph with limited computer resources. To demonstrate the usefulness of the proposed operation history graph and verify whether detected traceability links are sufficient to reveal actual changes of program elements, we implemented tools to generate and manipulate OHG instances. The evaluation on graph generation performance shows that our tool can reduce the required computer resource as compared to another tool authors previously proposed. Moreover, the evaluation on traceability shows that OHG provides traceability links with sufficient accuracy as compared to the baseline approach using GumTree.},
keywords={},
doi={10.1587/transinf.2020EDP7129},
ISSN={1745-1361},
month={March},}
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TY - JOUR
TI - Lightweight Operation History Graph for Traceability on Program Elements
T2 - IEICE TRANSACTIONS on Information
SP - 404
EP - 418
AU - Takayuki OMORI
AU - Katsuhisa MARUYAMA
AU - Atsushi OHNISHI
PY - 2021
DO - 10.1587/transinf.2020EDP7129
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2021
AB - History data of edit operations are more beneficial than those stored in version control systems since they provide detailed information on how source code was changed. Meanwhile, a large number of recorded edit operations discourage developers and researchers from roughly understanding the changes. To assist with this task, it is desirable that they easily obtain traceability links for changed program elements over two source code snapshots before and after a code change. In this paper, we propose a graph representation called Operation History Graph (OHG), which presents code change information with such traceability links that are inferred from the history of edit operations. An OHG instance is generated by parsing any source code snapshot restored by edit histories and combining resultant abstract syntax trees (ASTs) into a single graph structure. To improve the performance of building graph instances, we avoided simply maintaining every program element. Any program element presenting the inner-structure of methods and non-changed elements are omitted. In addition, we adopted a lightweight static analysis for type name resolving to reduce required memory resource in the analysis while the accuracy of name resolving is preserved. Moreover, we assign a specific ID to each node and edge in the graph instance so that a part of the graph data can be separately stored and loaded on demand. These decisions make it feasible to build, manipulate, and store the graph with limited computer resources. To demonstrate the usefulness of the proposed operation history graph and verify whether detected traceability links are sufficient to reveal actual changes of program elements, we implemented tools to generate and manipulate OHG instances. The evaluation on graph generation performance shows that our tool can reduce the required computer resource as compared to another tool authors previously proposed. Moreover, the evaluation on traceability shows that OHG provides traceability links with sufficient accuracy as compared to the baseline approach using GumTree.
ER -
English
