The effect of automatic concern mapping strategies on conceptual cohesion measurement
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFBA |
Texto Completo: | http://repositorio.ufba.br/ri/handle/ri/32475 |
Resumo: | Context: Cohesion has been recognized as an important quality attribute of software design across decades. It can be defined as the degree to which a module is focused on a single concern of software. A concern is any concept, feature, requirement or property of the problem or solution domain. Conceptual cohesion is an alternative way of cohesion measurement based on what concerns each module addresses. Therefore, adopting a strategy to map concerns to source code elements is challenging but necessary. Objective: We aim at providing empirical evidence about whether automatic concern mapping strategies are already ready to be used effectively for conceptual cohesion measurement. Method: We carried out an empirical study to assess the ability of conceptual cohesion measurement using different automatic concern mapping strategies in selecting the least cohesive modules. Results: Conceptual cohesion measurements over the two analyzed mapping strategies performed weakly in the ability of selecting the least cohesive modules. We then provide a discussion to explain the reasons. Conclusion: Concern mapping strategies should be carefully chosen for conceptual cohesion measure- ment, specially if automatic mapping is under consideration. Manual mapping is still the most reliable way for computing conceptual cohesion. We pointed out limitations in automatic mapping strategies that go beyond conceptual cohesion measurement purposes and which should be considered in future research or applications in industry. |
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Silva, Bruno Carreiro daSant'Anna, Cláudio NogueiraRocha, NeylorChavez, Christina Von Flach Garcia2020-12-10T19:13:51Z2020-12-10T19:13:51Z2016-01Silva, Bruno [et al.]. The effect of automatic concern mapping strategies on conceptual cohesion measurement. Information and Software Technology, Canadá, vol. 75, p. 56–70, jul., 2016, doi:10.1016/j.infsof.2016.03.006. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0950584916300520#!. Acesso em: jan. 2016.0950-5849http://repositorio.ufba.br/ri/handle/ri/32475v. 75Context: Cohesion has been recognized as an important quality attribute of software design across decades. It can be defined as the degree to which a module is focused on a single concern of software. A concern is any concept, feature, requirement or property of the problem or solution domain. Conceptual cohesion is an alternative way of cohesion measurement based on what concerns each module addresses. Therefore, adopting a strategy to map concerns to source code elements is challenging but necessary. Objective: We aim at providing empirical evidence about whether automatic concern mapping strategies are already ready to be used effectively for conceptual cohesion measurement. Method: We carried out an empirical study to assess the ability of conceptual cohesion measurement using different automatic concern mapping strategies in selecting the least cohesive modules. Results: Conceptual cohesion measurements over the two analyzed mapping strategies performed weakly in the ability of selecting the least cohesive modules. We then provide a discussion to explain the reasons. Conclusion: Concern mapping strategies should be carefully chosen for conceptual cohesion measure- ment, specially if automatic mapping is under consideration. Manual mapping is still the most reliable way for computing conceptual cohesion. We pointed out limitations in automatic mapping strategies that go beyond conceptual cohesion measurement purposes and which should be considered in future research or applications in industry.Submitted by Christina Chavez (flach@ufba.br) on 2020-12-07T17:28:43Z No. of bitstreams: 1 preprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf: 808163 bytes, checksum: 7477421c55e70e20a9c414e3d87dcd05 (MD5)Approved for entry into archive by Solange Rocha (soluny@gmail.com) on 2020-12-10T19:13:49Z (GMT) No. of bitstreams: 1 preprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf: 808163 bytes, checksum: 7477421c55e70e20a9c414e3d87dcd05 (MD5)Made available in DSpace on 2020-12-10T19:13:51Z (GMT). No. of bitstreams: 1 preprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf: 808163 bytes, checksum: 7477421c55e70e20a9c414e3d87dcd05 (MD5) Previous issue date: 2016-01Alberta, CanadáElsevierBrasilhttp://www.sciencedirect.com/science/article/pii/S0950584916300520reponame:Repositório Institucional da UFBAinstname:Universidade Federal da Bahia (UFBA)instacron:UFBAModule cohesionCohesion metricsConcern mappingComparative empirical studyThe effect of automatic concern mapping strategies on conceptual cohesion measurementinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessengORIGINALpreprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdfpreprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdfapplication/pdf808163https://repositorio.ufba.br/bitstream/ri/32475/1/preprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf7477421c55e70e20a9c414e3d87dcd05MD51LICENSElicense.txtlicense.txttext/plain1442https://repositorio.ufba.br/bitstream/ri/32475/2/license.txte3e6f4a9287585a60c07547815529482MD52TEXTpreprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf.txtpreprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf.txtExtracted texttext/plain98115https://repositorio.ufba.br/bitstream/ri/32475/3/preprint_IST_2016_The_Effect_of_Automatic_Concern_Mapping_Strategies.pdf.txt8b9f9020dbec26c6b6cb3d0b113bf1dbMD53ri/324752022-03-10 14:22:04.501oai:repositorio.ufba.br:ri/32475VGVybW8gZGUgTGljZW4/YSwgbj9vIGV4Y2x1c2l2bywgcGFyYSBvIGRlcD9zaXRvIG5vIFJlcG9zaXQ/cmlvIEluc3RpdHVjaW9uYWwgZGEgVUZCQS4KCiBQZWxvIHByb2Nlc3NvIGRlIHN1Ym1pc3M/Pz8/byBkZSBkb2N1bWVudG9zLCBvIGF1dG9yIG91IHNldSByZXByZXNlbnRhbnRlIGxlZ2FsLCBhbyBhY2VpdGFyIGVzc2UgdGVybW8gZGUgbGljZW4/Pz8/YSwgY29uY2VkZSBhbyBSZXBvc2l0Pz8/P3JpbyBJbnN0aXR1Y2lvbmFsIGRhIFVuaXZlcnNpZGFkZSBGZWRlcmFsIGRhIEJhaGlhIG8gZGlyZWl0byBkZSBtYW50ZXIgdW1hIGM/Pz8/cGlhIGVtIHNldSByZXBvc2l0Pz8/P3JpbyBjb20gYSBmaW5hbGlkYWRlLCBwcmltZWlyYSwgZGUgcHJlc2VydmE/Pz8/Pz8/P28uIAoKRXNzZXMgdGVybW9zLCBuPz8/P28gZXhjbHVzaXZvcywgbWFudD8/Pz9tIG9zIGRpcmVpdG9zIGRlIGF1dG9yL2NvcHlyaWdodCwgbWFzIGVudGVuZGUgbyBkb2N1bWVudG8gY29tbyBwYXJ0ZSBkbyBhY2Vydm8gaW50ZWxlY3R1YWwgZGVzc2EgVW5pdmVyc2lkYWRlLgoKIFBhcmEgb3MgZG9jdW1lbnRvcyBwdWJsaWNhZG9zIGNvbSByZXBhc3NlIGRlIGRpcmVpdG9zIGRlIGRpc3RyaWJ1aT8/Pz8/Pz8/bywgZXNzZSB0ZXJtbyBkZSBsaWNlbj8/Pz9hIGVudGVuZGUgcXVlOgoKIE1hbnRlbmRvIG9zIGRpcmVpdG9zIGF1dG9yYWlzLCByZXBhc3NhZG9zIGEgdGVyY2Vpcm9zLCBlbSBjYXNvIGRlIHB1YmxpY2E/Pz8/Pz8/P2VzLCBvIHJlcG9zaXQ/Pz8/cmlvIHBvZGUgcmVzdHJpbmdpciBvIGFjZXNzbyBhbyB0ZXh0byBpbnRlZ3JhbCwgbWFzIGxpYmVyYSBhcyBpbmZvcm1hPz8/Pz8/Pz9lcyBzb2JyZSBvIGRvY3VtZW50byAoTWV0YWRhZG9zIGRlc2NyaXRpdm9zKS4KCiBEZXN0YSBmb3JtYSwgYXRlbmRlbmRvIGFvcyBhbnNlaW9zIGRlc3NhIHVuaXZlcnNpZGFkZSBlbSBtYW50ZXIgc3VhIHByb2R1Pz8/Pz8/Pz9vIGNpZW50Pz8/P2ZpY2EgY29tIGFzIHJlc3RyaT8/Pz8/Pz8/ZXMgaW1wb3N0YXMgcGVsb3MgZWRpdG9yZXMgZGUgcGVyaT8/Pz9kaWNvcy4KCiBQYXJhIGFzIHB1YmxpY2E/Pz8/Pz8/P2VzIHNlbSBpbmljaWF0aXZhcyBxdWUgc2VndWVtIGEgcG9sPz8/P3RpY2EgZGUgQWNlc3NvIEFiZXJ0bywgb3MgZGVwPz8/P3NpdG9zIGNvbXB1bHM/Pz8/cmlvcyBuZXNzZSByZXBvc2l0Pz8/P3JpbyBtYW50Pz8/P20gb3MgZGlyZWl0b3MgYXV0b3JhaXMsIG1hcyBtYW50Pz8/P20gYWNlc3NvIGlycmVzdHJpdG8gYW9zIG1ldGFkYWRvcyBlIHRleHRvIGNvbXBsZXRvLiBBc3NpbSwgYSBhY2VpdGE/Pz8/Pz8/P28gZGVzc2UgdGVybW8gbj8/Pz9vIG5lY2Vzc2l0YSBkZSBjb25zZW50aW1lbnRvIHBvciBwYXJ0ZSBkZSBhdXRvcmVzL2RldGVudG9yZXMgZG9zIGRpcmVpdG9zLCBwb3IgZXN0YXJlbSBlbSBpbmljaWF0aXZhcyBkZSBhY2Vzc28gYWJlcnRvLgo=Repositório InstitucionalPUBhttp://192.188.11.11:8080/oai/requestopendoar:19322022-03-10T17:22:04Repositório Institucional da UFBA - Universidade Federal da Bahia (UFBA)false |
dc.title.pt_BR.fl_str_mv |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
title |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
spellingShingle |
The effect of automatic concern mapping strategies on conceptual cohesion measurement Silva, Bruno Carreiro da Module cohesion Cohesion metrics Concern mapping Comparative empirical study |
title_short |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
title_full |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
title_fullStr |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
title_full_unstemmed |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
title_sort |
The effect of automatic concern mapping strategies on conceptual cohesion measurement |
author |
Silva, Bruno Carreiro da |
author_facet |
Silva, Bruno Carreiro da Sant'Anna, Cláudio Nogueira Rocha, Neylor Chavez, Christina Von Flach Garcia |
author_role |
author |
author2 |
Sant'Anna, Cláudio Nogueira Rocha, Neylor Chavez, Christina Von Flach Garcia |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Silva, Bruno Carreiro da Sant'Anna, Cláudio Nogueira Rocha, Neylor Chavez, Christina Von Flach Garcia |
dc.subject.por.fl_str_mv |
Module cohesion Cohesion metrics Concern mapping Comparative empirical study |
topic |
Module cohesion Cohesion metrics Concern mapping Comparative empirical study |
description |
Context: Cohesion has been recognized as an important quality attribute of software design across decades. It can be defined as the degree to which a module is focused on a single concern of software. A concern is any concept, feature, requirement or property of the problem or solution domain. Conceptual cohesion is an alternative way of cohesion measurement based on what concerns each module addresses. Therefore, adopting a strategy to map concerns to source code elements is challenging but necessary. Objective: We aim at providing empirical evidence about whether automatic concern mapping strategies are already ready to be used effectively for conceptual cohesion measurement. Method: We carried out an empirical study to assess the ability of conceptual cohesion measurement using different automatic concern mapping strategies in selecting the least cohesive modules. Results: Conceptual cohesion measurements over the two analyzed mapping strategies performed weakly in the ability of selecting the least cohesive modules. We then provide a discussion to explain the reasons. Conclusion: Concern mapping strategies should be carefully chosen for conceptual cohesion measure- ment, specially if automatic mapping is under consideration. Manual mapping is still the most reliable way for computing conceptual cohesion. We pointed out limitations in automatic mapping strategies that go beyond conceptual cohesion measurement purposes and which should be considered in future research or applications in industry. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016-01 |
dc.date.accessioned.fl_str_mv |
2020-12-10T19:13:51Z |
dc.date.available.fl_str_mv |
2020-12-10T19:13:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
Silva, Bruno [et al.]. The effect of automatic concern mapping strategies on conceptual cohesion measurement. Information and Software Technology, Canadá, vol. 75, p. 56–70, jul., 2016, doi:10.1016/j.infsof.2016.03.006. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0950584916300520#!. Acesso em: jan. 2016. |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufba.br/ri/handle/ri/32475 |
dc.identifier.issn.none.fl_str_mv |
0950-5849 |
dc.identifier.number.pt_BR.fl_str_mv |
v. 75 |
identifier_str_mv |
Silva, Bruno [et al.]. The effect of automatic concern mapping strategies on conceptual cohesion measurement. Information and Software Technology, Canadá, vol. 75, p. 56–70, jul., 2016, doi:10.1016/j.infsof.2016.03.006. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0950584916300520#!. Acesso em: jan. 2016. 0950-5849 v. 75 |
url |
http://repositorio.ufba.br/ri/handle/ri/32475 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
Elsevier |
dc.publisher.country.fl_str_mv |
Brasil |
publisher.none.fl_str_mv |
Elsevier |
dc.source.pt_BR.fl_str_mv |
http://www.sciencedirect.com/science/article/pii/S0950584916300520 |
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reponame:Repositório Institucional da UFBA instname:Universidade Federal da Bahia (UFBA) instacron:UFBA |
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