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History-sensitive heuristics for recovery of features in code of evolving program families

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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History-sensitive heuristics for recovery of features in code of evolving program families. / Nunes, Camila; Garcia, Alessandro; Lucena, Carlos et al.
SPLC '12 Proceedings of the 16th International Software Product Line Conference. Vol. 1 New York: ACM, 2012. p. 136-145.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Nunes, C, Garcia, A, Lucena, C & Lee, J 2012, History-sensitive heuristics for recovery of features in code of evolving program families. in SPLC '12 Proceedings of the 16th International Software Product Line Conference. vol. 1, ACM, New York, pp. 136-145. https://doi.org/10.1145/2362536.2362556

APA

Nunes, C., Garcia, A., Lucena, C., & Lee, J. (2012). History-sensitive heuristics for recovery of features in code of evolving program families. In SPLC '12 Proceedings of the 16th International Software Product Line Conference (Vol. 1, pp. 136-145). ACM. https://doi.org/10.1145/2362536.2362556

Vancouver

Nunes C, Garcia A, Lucena C, Lee J. History-sensitive heuristics for recovery of features in code of evolving program families. In SPLC '12 Proceedings of the 16th International Software Product Line Conference. Vol. 1. New York: ACM. 2012. p. 136-145 doi: 10.1145/2362536.2362556

Author

Nunes, Camila ; Garcia, Alessandro ; Lucena, Carlos et al. / History-sensitive heuristics for recovery of features in code of evolving program families. SPLC '12 Proceedings of the 16th International Software Product Line Conference. Vol. 1 New York : ACM, 2012. pp. 136-145

Bibtex

@inproceedings{72628fdf741841af84ee7a28996f370f,
title = "History-sensitive heuristics for recovery of features in code of evolving program families",
abstract = "A program family might degenerate due to unplanned changes in its implementation, thus hindering the maintenance of family members. This degeneration is often induced by feature code that is changed individually in each member without considering other family members. Hence, as a program family evolves over time, it might no longer be possible to distinguish between common and variable features. One of the imminent activities to address this problem is the history-sensitive recovery of program family's features in the code. This recovery process encompasses the analysis of the evolution history of each family member in order to classify the implementation elements according to their variability nature. In this context, this paper proposes history-sensitive heuristics for the recovery of features in code of degenerate program families. Once the analysis of the family history is carried out, the feature elements are structured as Java project packages; they are intended to separate those elements in terms of their variability degree. The proposed heuristics are supported by a prototype tool called RecFeat. We evaluated the accuracy of the heuristics in the context of 33 versions of 2 industry program families. They presented encouraging results regarding recall measures that ranged from 85% to 100%; whereas the precision measures ranged from 71% to 99%.",
author = "Camila Nunes and Alessandro Garcia and Carlos Lucena and Jaejoon Lee",
year = "2012",
doi = "10.1145/2362536.2362556",
language = "English",
isbn = "978-1-4503-1094-9",
volume = "1",
pages = "136--145",
booktitle = "SPLC '12 Proceedings of the 16th International Software Product Line Conference",
publisher = "ACM",

}

RIS

TY - GEN

T1 - History-sensitive heuristics for recovery of features in code of evolving program families

AU - Nunes, Camila

AU - Garcia, Alessandro

AU - Lucena, Carlos

AU - Lee, Jaejoon

PY - 2012

Y1 - 2012

N2 - A program family might degenerate due to unplanned changes in its implementation, thus hindering the maintenance of family members. This degeneration is often induced by feature code that is changed individually in each member without considering other family members. Hence, as a program family evolves over time, it might no longer be possible to distinguish between common and variable features. One of the imminent activities to address this problem is the history-sensitive recovery of program family's features in the code. This recovery process encompasses the analysis of the evolution history of each family member in order to classify the implementation elements according to their variability nature. In this context, this paper proposes history-sensitive heuristics for the recovery of features in code of degenerate program families. Once the analysis of the family history is carried out, the feature elements are structured as Java project packages; they are intended to separate those elements in terms of their variability degree. The proposed heuristics are supported by a prototype tool called RecFeat. We evaluated the accuracy of the heuristics in the context of 33 versions of 2 industry program families. They presented encouraging results regarding recall measures that ranged from 85% to 100%; whereas the precision measures ranged from 71% to 99%.

AB - A program family might degenerate due to unplanned changes in its implementation, thus hindering the maintenance of family members. This degeneration is often induced by feature code that is changed individually in each member without considering other family members. Hence, as a program family evolves over time, it might no longer be possible to distinguish between common and variable features. One of the imminent activities to address this problem is the history-sensitive recovery of program family's features in the code. This recovery process encompasses the analysis of the evolution history of each family member in order to classify the implementation elements according to their variability nature. In this context, this paper proposes history-sensitive heuristics for the recovery of features in code of degenerate program families. Once the analysis of the family history is carried out, the feature elements are structured as Java project packages; they are intended to separate those elements in terms of their variability degree. The proposed heuristics are supported by a prototype tool called RecFeat. We evaluated the accuracy of the heuristics in the context of 33 versions of 2 industry program families. They presented encouraging results regarding recall measures that ranged from 85% to 100%; whereas the precision measures ranged from 71% to 99%.

U2 - 10.1145/2362536.2362556

DO - 10.1145/2362536.2362556

M3 - Conference contribution/Paper

SN - 978-1-4503-1094-9

VL - 1

SP - 136

EP - 145

BT - SPLC '12 Proceedings of the 16th International Software Product Line Conference

PB - ACM

CY - New York

ER -