The dance of classes: a stochastic model for software structure evolution

Rafael Prates Ferreira Trindade; Talita  Santana Orfanó; Kecia Aline Marques Ferreira; Elizabeth  Fialho Wanner

doi:10.1109/WETSoM.2017..5

The dance of classes: a stochastic model for software structure evolution

Rafael Prates Ferreira Trindade, Talita Santana Orfanó, Kecia Aline Marques Ferreira, Elizabeth Fialho Wanner

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

In this study, we investigate software structure evolution and growth. We represent software structure by means of a generic macro-topology called Little House, which models the dependencies among classes of object-oriented software systems. We, then, define a stochastic model to predict the way software architectures evolve. The model estimates how the classes of object-oriented programs get connected one to another along the evolution of the systems. To define the model, we analyzed data from 81 versions of six Java based projects. We analyzed each pair of sequential versions, for each project, in order to depict a pattern of software structure evolution based on Little House. To evaluate the model, we performed two experiments: one with the data used to derive the model, and another with data of 35 releases, in total, of four open-source Java project. In both experiments, we found a very low rate of error for the application of the proposed model. The evaluation of the model suggests it is able to predict how a software structure will evolve.

Original language	English
Title of host publication	WETSoM '17: Proceedings of the 8th Workshop on Emerging Trends in Software Metrics
Place of Publication	Piscataway, NJ (US)
Publisher	IEEE
Pages	22-28
Number of pages	7
ISBN (Print)	978-1-5386-2807-2
DOIs	https://doi.org/10.1109/WETSoM.2017..5
Publication status	Published - 20 May 2017
Event	8th Workshop on Emerging Trends in Software Metrics: ICSE International Conference on Software Engineering - Argentina, Buenos Aires, Argentina Duration: 20 May 2017 → 28 May 2017

Workshop

Workshop	8th Workshop on Emerging Trends in Software Metrics
Abbreviated title	WETSoM 2017
Country/Territory	Argentina
City	Buenos Aires
Period	20/05/17 → 28/05/17

Bibliographical note

-© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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10.1109/WETSoM.2017..5

Stochastic model for software structure evolution
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Accepted author manuscript, 528 KB

Cite this

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title = "The dance of classes: a stochastic model for software structure evolution",

abstract = "In this study, we investigate software structure evolution and growth. We represent software structure by means of a generic macro-topology called Little House, which models the dependencies among classes of object-oriented software systems. We, then, define a stochastic model to predict the way software architectures evolve. The model estimates how the classes of object-oriented programs get connected one to another along the evolution of the systems. To define the model, we analyzed data from 81 versions of six Java based projects. We analyzed each pair of sequential versions, for each project, in order to depict a pattern of software structure evolution based on Little House. To evaluate the model, we performed two experiments: one with the data used to derive the model, and another with data of 35 releases, in total, of four open-source Java project. In both experiments, we found a very low rate of error for the application of the proposed model. The evaluation of the model suggests it is able to predict how a software structure will evolve.",

author = "{Prates Ferreira Trindade}, Rafael and {Santana Orfan{\'o}}, Talita and {Marques Ferreira}, {Kecia Aline} and {Fialho Wanner}, Elizabeth",

note = "-{\textcopyright} 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; 8th Workshop on Emerging Trends in Software Metrics : ICSE International Conference on Software Engineering, WETSoM 2017 ; Conference date: 20-05-2017 Through 28-05-2017",

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Prates Ferreira Trindade, R, Santana Orfanó, T, Marques Ferreira, KA & Fialho Wanner, E 2017, The dance of classes: a stochastic model for software structure evolution. in WETSoM '17: Proceedings of the 8th Workshop on Emerging Trends in Software Metrics . IEEE, Piscataway, NJ (US), pp. 22-28, 8th Workshop on Emerging Trends in Software Metrics, Buenos Aires, Argentina, 20/05/17. https://doi.org/10.1109/WETSoM.2017..5

The dance of classes: a stochastic model for software structure evolution. / Prates Ferreira Trindade, Rafael; Santana Orfanó, Talita ; Marques Ferreira, Kecia Aline et al.
WETSoM '17: Proceedings of the 8th Workshop on Emerging Trends in Software Metrics . Piscataway, NJ (US): IEEE, 2017. p. 22-28.

Research output: Chapter in Book/Published conference output › Conference publication

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AU - Marques Ferreira, Kecia Aline

AU - Fialho Wanner, Elizabeth

N1 - -© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2017/5/20

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N2 - In this study, we investigate software structure evolution and growth. We represent software structure by means of a generic macro-topology called Little House, which models the dependencies among classes of object-oriented software systems. We, then, define a stochastic model to predict the way software architectures evolve. The model estimates how the classes of object-oriented programs get connected one to another along the evolution of the systems. To define the model, we analyzed data from 81 versions of six Java based projects. We analyzed each pair of sequential versions, for each project, in order to depict a pattern of software structure evolution based on Little House. To evaluate the model, we performed two experiments: one with the data used to derive the model, and another with data of 35 releases, in total, of four open-source Java project. In both experiments, we found a very low rate of error for the application of the proposed model. The evaluation of the model suggests it is able to predict how a software structure will evolve.

AB - In this study, we investigate software structure evolution and growth. We represent software structure by means of a generic macro-topology called Little House, which models the dependencies among classes of object-oriented software systems. We, then, define a stochastic model to predict the way software architectures evolve. The model estimates how the classes of object-oriented programs get connected one to another along the evolution of the systems. To define the model, we analyzed data from 81 versions of six Java based projects. We analyzed each pair of sequential versions, for each project, in order to depict a pattern of software structure evolution based on Little House. To evaluate the model, we performed two experiments: one with the data used to derive the model, and another with data of 35 releases, in total, of four open-source Java project. In both experiments, we found a very low rate of error for the application of the proposed model. The evaluation of the model suggests it is able to predict how a software structure will evolve.

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ER -

The dance of classes: a stochastic model for software structure evolution

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Workshop

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