Community smells in software development communities: systematic literature review
Main Article Content
Objective: This study presents initial findings from a Systematic Literature Review (SLR) aimed at identifying potential anti-patterns known as community smells. If not effectively addressed, these smells can lead to underlying social issues within software development teams. Methodology: To conduct this study, a Systematic Literature Review was performed, providing a detailed and structured analysis of existing research on community smells in software development teams. The article focuses on three main aspects: (i) demographic aspects of the topic, (ii) types of research, and (iii) the definition, causes, and effects of community smells according to different authors. The Systematic Literature Review followed the protocol proposed by Kitchenham, which allowed for the identification, analysis, evaluation, and in-depth investigation of the available literature. Results: A total of 49 primary studies were selected, analyzed, and evaluated, leading to the identification of 35 community smells. Among the most prominent or visible are organizational silo, black cloud, lone wolf, and bottleneck, each of these smells was examined alongside its causes and negative effects on software development collaboration. Conclusions: Through the Systematic Literature Review, the current state of research on community smells was identified, along with the main anti-patterns that contribute to their emergence. The findings suggest that these effects can hinder interaction and teamwork, leading to failures in communication and collaboration, delays in software development, incomplete or defective software artifact and the emergence of psychosocial risks.
- Anti-patterns
- Communication
- Cooperation
- Coordination
- Software communities
- Social debt
- Community smells
Gómez Fuentes M del C, Cervantes Ojeda J, González Pérez P. Fundamentos de Ingeniería de Software 1st ed. UAM UC, editor. Ciudad de México: Universidad Autónoma Metropolítana; 2019, 1–277 p. Available from: https://shorturl.at/gjGIL
Yilmaz M, O’Connor R V., Clarke P. Effective Social Productivity Measurements during Software Development - An Empirical Study. International Journal of Software Engineering and Knowledge Engineering. 2016 Apr 1;26(3):457–90. https://doi.org/10.1142/S0218194016500194 DOI: https://doi.org/10.1142/S0218194016500194
Galster M, Tamburri DA, Kazman R. Towards Understanding the Social and Organizational Dimensions of Software Architecting. ACM SIGSOFT Software Engineering Notes. 2017;42(3):24–5. https://doi.org/10.1145/3127360.3127374 DOI: https://doi.org/10.1145/3127360.3127374
Sievi-Korte O, Fagerholm F, Systä K, Mikkonen T. Dimensions of Consistency in GSD: Social Factors, Structures and Interactions. Proceedings Lecture Notes in Computer Science. 2020;12562:315–30. https://doi.org/10.1007/978-3-030-64148-1_20
Brieva ES, Pardo C, Villarreal V. Deuda Social y Riesgos psicosociales en entornos de desarrollo de software ágil: Análisis preliminar de una Revisión Sistemática de la Literatura. In: 2024 IEEE VII Congreso Internacional en Inteligencia Ambiental, Ingeniería de Software y Salud Electrónica y Móvil (AmITIC). 2024. p. 1–8. https://doi.org/10.1109/AmITIC62658.2024.10747594 DOI: https://doi.org/10.1109/AmITIC62658.2024.10747594
Vizcaíno A, García F, Piattini M. Visión General del Desarrollo Global de Software. International Journal of Information Systems and Software Engineering for Big Companies (IJISEBC) 2014;1(1):8–22. www.ijisebc.com
Jiménez M, Piattini M, Vizcaíno A. Challenges and improvements in distributed software development: A systematic review. Advances in Software Engineering. 2009; 1–14. https://doi.org/10.1155/2009/710971 DOI: https://doi.org/10.1155/2009/710971
Vizcaíno A, Valencia D, Soto JP, García-Mundo L, Piattini M. ¿Qué desafíos presenta el desarrollo global del software? Aprende jugando. In: XXI Jornadas de Ingeniería del Software y Bases de Datos. México; 2016. p. 605–8. https://investigadores.unison.mx/ws/portalfiles/portal/8020882/CEDI_2016_paper_47.pdf
García GD, Pardo Calvache CJ, Rodríguez FJA. Society 5.0 and Soft Skills in Agile Global Software Development. Revista Iberoamericana de Tecnologías del Aprendizaje. 2022 May 1;17(2):197–207. https://doi.org/10.1109/RITA.2022.3166966 DOI: https://doi.org/10.1109/RITA.2022.3166966
Mens T. An ecosystemic and socio-technical view on software maintenance and evolution. In: Proceedings - 2016 IEEE International Conference on Software Maintenance and Evolution, ICSME 2016. Institute of Electrical and Electronics Engineers Inc.; 2017. p. 1–8. https://doi.org/10.1109/ICSME.2016.19 DOI: https://doi.org/10.1109/ICSME.2016.19
Gote C, Perri V, Zingg C, Casiraghi G, Arzig C, von Gernler A, et al. Locating community smells in software development processes using higher-order network centralities. Soc Netw Anal Min. 2023 Oct 1;13(1):1–28. https://doi.org/10.1007/s13278-023-01120-w
Olsson J, Risfelt E, Besker T, Martini A, Torkar R. Measuring affective states from technical debt: A psychoempirical software engineering experiment. Empir Softw Eng. 2021 Sep 1;26(5). https://doi.org/10.1007/s10664-021-09998-w DOI: https://doi.org/10.1007/s10664-021-09998-w
Tamburri DA, Milano D, Kazman R. The Architect’s Role in Community Shepherding. https://doi.org/10.1109/MS.2016.144 DOI: https://doi.org/10.1109/MS.2016.144
Tamburri DA, Palomba F, Kazman R. Exploring Community Smells in Open-Source: An automated approach. IEEE Transactions on Software Engineering. 2017;14(8):630–52. https://doi.org/10.1109/TSE.2019.2901490
Palomba F, Tamburri DA. Predicting the emergence of community smells using socio-technical metrics: A machine-learning approach. Journal of Systems and Software. 2021;171. https://doi.org/10.1016/j.jss.2020.110847
Huang Z, Shao Z, Fan G, Gao J, Zhou Z, Yang K, et al. Predicting Community Smells’ Occurrence on individual developers by sentiments. In: ICPC, editor. 2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC). Madrid : IEEE; 2021. p. 230–41. https://doi.org/10.1109/ICPC52881.2021.00030
Caballero-Espinosa E, Carver JC, Stowers K. Community smells—The sources of social debt: A systematic literature review. Inf Softw Technol. 2023;153. https://doi.org/10.1016/j.infsof.2022.107078 DOI: https://doi.org/10.1016/j.infsof.2022.107078
Catolino G, Palomba F, Tamburri DA, Serebrenik A. Understanding Community Smells Variability: A Statistical Approach. Proceedings - International Conference on Software Engineering. 2021; 77–86. https://doi.org/10.1109/ICSE-SEIS52602.2021.00017
Almarimi N, Ouni A, Chouchen M, Mkaouer MW. Improving the detection of community smells through socio‐technical and sentiment analysis. Journal of Software: Evolution and Process. 2022;35 https://doi.org/10.1002/smr.2505 DOI: https://doi.org/10.1002/smr.2505
Saeeda H, Ovais Ahmad M, Gustavsson T. Navigating social debt and its link with technical debt in large-scale agile software development projects. Software Quality Journal. 2024;32:1581–1613 https://doi.org/10.1007/s11219-024-09688-y DOI: https://doi.org/10.1007/s11219-024-09688-y
Saeeda H, Ovais Ahamd M, Gustavsson T. A Multivocal Literature Review on Non-Technical Debt in Software Development: An Insight into Process, Social, People, Organizational, and Culture Debt. e-Informatica Software Engineering Journal. 2024;18(1):240101. https://doi.org/10.37190/e-Inf240101 DOI: https://doi.org/10.37190/e-Inf240101
Palomba F, Serebrenik A, Zaidman A. Social Debt Analytics for improving the management of Software evolution tasks. In: CEUR Workshop Proceedings, editor. Belgian Netherlands Software evolution Symposium. Belgium; 2023;19–21. https://shorturl.at/ahoX7
Moreno Jiménez, Bernardo. “Factores y riesgos laborales psicosociales: conceptualización, historia y cambios actuales.” Medicina y Seguridad del trabajo. 2011; 57: 4-19. DOI: https://doi.org/10.4321/S0465-546X2011000500002
Organización Internacional del Trabajo. La organización del trabajo y los riesgos psicosociales: una mirada de género. Organización Internacional del Trabajo. San José; 2013 https://scielo.isciii.es/scielo.php?pid=S0465-546X2011000500002&script=sci_arttext&tlng=en
Tamburri DA, Kruchten P, Lago P, Vliet H van. Social debt in software engineering: insights from industry. Journal of Internet Services and Applications. 2015;6(1). https://doi.org/10.1186/s13174-015-0024-6
De Stefano M, Iannone E, Pecorelli F, Tamburri DA. Impacts of software community patterns on process and product: An empirical study. Sci Comput Program. 2022; 214:102731. https://doi.org/10.1016/j.scico.2021.102731
Lambiase S, Catolino G, Tamburri DA, Serebrenik A, Palomba F, Ferrucci F. Good fences make good neighbours? on the impact of cultural and geographical dispersion on community smells. In: Proceedings of the 2022 ACM/IEEE 44th International Conference on Software Engineering: Software Engineering in Society. New York, NY, USA: Association for Computing Machinery; 2022. p. 67–78. https://doi.org/10.1145/3510458.3513015
Tamburri DA. Software Architecture Social Debt: Managing the Incommunicability Factor. IEEE Trans Comput Soc Syst. 2019;6(1):20–37. https://doi.org/10.1109/TCSS.2018.2886433
Dreesen T, Hennel P, Rosenkranz C, Kude T. The second vice is lying, the first is running into debt. Antecedents and mitigating practices of social debt: An exploratory study in distributed software development teams. Proceedings of the Annual Hawaii International Conference on System Sciences. 2021; 6826–35. https://doi.org/10.24251/HICSS.2021.818
Mumtaz H, Paradis C, Palomba F, Tamburri DA, Kazman R, Blincoe K. A Preliminary Study on the Assignment of GitHub Issues to Issue Commenters and the Relationship with Social Smells. Vol. 1, Proceedings - 15th International Conference on Cooperative and Human Aspects of Software Engineering, CHASE 2022. Association for Computing Machinery. 2022; 61–65 https://doi.org/10.1145/3528579.3529181
Lambiase S, Catolino G, Tamburri DA, Serebrenik A, Palomba F, Ferrucci F. Good fences make good neighbours? 2022;67–78. https://doi.org/10.1109/ICSE-SEIS55304.2022.9793992
Pontificia Universidad Javeriana, Ministerio de la Protección Social. Batería de instrumentos para la evaluación de factores de riesgo psicosocial. 2010 https://shorturl.at/kuE49
R. S. Sangwan, K. W. Jablokow and J. F. DeFranco, “Asynchronous Collaboration: Bridging the Cognitive Distance in Global Software Development Projects,” in IEEE Transactions on Professional Communication. 2020; 63(4):361-371 https://doi.org/10.1109/TPC.2020.3029674 DOI: https://doi.org/10.1109/TPC.2020.3029674
Almarimi N, Ouni A, Mkaouer MW. Learning to detect community smells in open source software projects. Knowl Based Syst. 2020 Sep 27;204. https://doi.org/10.1016/j.knosys.2020.106201
Palomba F, Tamburri DA. Predicting the emergence of community smells using socio-technical metrics: A machine-learning approach. Journal of Systems and Software. 2021;171. https://doi.org/10.1016/j.jss.2020.110847
Catolino G, Palomba F, Tamburri DA, Serebrenik A, Ferrucci F. Refactoring Community Smells in the Wild: The Practitioner’s Field Manual. In: Proceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering: Software Engineering in Society, ICSE-SEIS 2020. 2020; 25–34. https://doi.org/10.1145/3377815.3381380
Palomba F, Tamburri DA. Predicting the emergence of community smells using socio-technical metrics: A machine-learning approach. Journal of Systems and Software. 2021;171:110847. https://doi.org/10.1016/j.jss.2020.110847
Raza B, Ahmad R, Nasir MH, Fauzi SS, Raza MA. Assessing the impact of socio-technical congruence in software development: a systematic literature review. KJS 2021;49(1). https://journalskuwait.org/kjs/index.php/KJS/article/view/9240 DOI: https://doi.org/10.48129/kjs.v49i1.9240
Tahsin N, Rauf A, Manzoor A, Anwer MU. Community smells—The sources of social debt: A systematic literature review. Systematic Literature Review and Meta-analysis Research. 2023;3(4). Available from: https://doi.org/10.54480/slrm.v3i4.51 DOI: https://doi.org/10.54480/slr-m.v3i4.51
Raza B, Ahmad R, Nasir MHNBM, Fauzi SSM. Socio-Technical Congruence as an Emerging Concept in Software Development: A Scientometric Analysis and Critical Literature Review. IEEE Access. 2021;9:129051–77. https://doi.org/10.1109/ACCESS.2021.3113637 DOI: https://doi.org/10.1109/ACCESS.2021.3113637
Kitchenham B, Charters S. Guidelines for performing Systematic Literature Reviews in Software Engineering Version 2.3. Vol. 45, Durham University. 2007 https://acortar.link/dzpbgk
Van Solingen R, Basili V, Caldiera G, Rombach HD. Goal Question Metric (GQM) Approach. Encyclopedia of Software Engineering. 2002. https://doi.org/10.1002/0471028959.sof142 DOI: https://doi.org/10.1002/0471028959.sof142
Wieringa R, Maiden N, Mead N, Rolland C. Requirements engineering paper classification and evaluation criteria: A proposal and a discussion. Requir Eng. 2006;11(1):102–7. https://doi.org/10.1007/s00766-005-0021-6
Kitchenham BA, Charters S. Guidelines for performing Systematic Literature Reviews in Software Engineering (Software Engineering Group, Department of Computer Science, Keele …. Technical Report EBSE 2007- 001 Keele University and Durham University Joint Report. 2007;(January).
Wieringa R, Maiden N, Mead N, Rolland C. Requirements engineering paper classification and evaluation criteria: A proposal and a discussion. Requir Eng. 2006 11(1):102–7. https://doi.org/10.1007/s00766-005-0021-6
Tamburri DA, Kruchten P, Lago P, Van Vliet H. What is social debt in software engineering? In: 2013 6th International Workshop on Cooperative and Human Aspects of Software Engineering, CHASE 2013 - Proceedings. 2013; 93–6. https://doi.org/10.1109/CHASE.2013.6614739 DOI: https://doi.org/10.1109/CHASE.2013.6614739
Tamburri DA, Nitto E Di. When Software Architecting Leads to Social Debt.2005. http://tinyurl.com/ljqgay9
Besker T, Ghanbari H, Martini A, Bosch J. The influence of Technical Debt on software developer morale. Journal of Systems and Software. 2020;167. https://doi.org/10.1016/j.jss.2020.110586 DOI: https://doi.org/10.1016/j.jss.2020.110586
Besker T, Martini A, Bosch J. The use of incentives to promote technical debt management. Inf Softw Technol. 2022;142: 106740 https://doi.org/10.1016/j.infsof.2021.106740 DOI: https://doi.org/10.1016/j.infsof.2021.106740
Martini A, Besker T, Bosch J. Technical Debt tracking: Current state of practice: A survey and multiple case study in 15 large organizations. Sci Comput Program. 2018;163:42–61. https://doi.org/10.1016/j.scico.2018.03.007 DOI: https://doi.org/10.1016/j.scico.2018.03.007
Almarimi N, Ouni A, Mkaouer MW. Learning to detect community smells in open source software projects. Knowl Based Syst. 2020 ;204. https://doi.org/10.1016/j.knosys.2020.106201 DOI: https://doi.org/10.1016/j.knosys.2020.106201
Palomba F, Tamburri DA. Predicting the emergence of community smells using socio-technical metrics: A machine-learning approach. Journal of Systems and Software. 2021;171:110847 https://doi.org/10.1016/j.jss.2020.110847 DOI: https://doi.org/10.1016/j.jss.2020.110847
De Stefano M, Iannone E, Pecorelli F, Tamburri DA. Impacts of software community patterns on process and product: An empirical study. Sci Comput Program. 2022; 214: 102731 https://doi.org/10.1016/j.scico.2021.102731 DOI: https://doi.org/10.1016/j.scico.2021.102731
Gemma Catolino, Fabio Palomba, Damian A. Tamburri, Alexander Serebrenik, Filomena Ferrucci. Refactoring Community Smells in the Wild: The Practitioner’s Field Manual. ICSE. 2020;25–34. https://doi.org/10.1145/3377815.3381380 DOI: https://doi.org/10.1145/3377815.3381380
Almarimi N, Ouni A, Chouchen M, Saidani I, Mkaouer MW. On the detection of community smells using genetic programming-based ensemble classifier chain. In: Proceedings - 2020 ACM/IEEE 15th International Conference on Global Software Engineering, ICGSE 2020. Association for Computing Machinery, Inc. 2020; 43–54. https://doi.org/10.1145/3372787.3390439 DOI: https://doi.org/10.1145/3372787.3390439
Catolino G, Palomba F, Tamburri DA, Serebrenik A, Ferrucci F. Gender diversity and women in software teams: How do they affect community smells? 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS). IEEE, 2019. https://doi.org/10.1109/ICSE-SEIS.2019.00010 DOI: https://doi.org/10.1109/ICSE-SEIS.2019.00010
De Stefano M, Pecorelli F, Tamburri DA, Palomba F, De Lucia A. Splicing Community Patterns and Smells: A Preliminary Study. 42nd International Conference on Software Engineering Workshops. 2020: 703–10. https://doi.org/10.1145/3387940.3392204 DOI: https://doi.org/10.1145/3387940.3392204
Canedo ED, Mendes F, Cerqueira A, Okimoto M, Pinto G, Bonifacio R. Breaking one barrier at a time: How women developers cope in a men-dominated industry. In: ACM International Conference Proceeding Series. Association for Computing Machinery. 2021;378–87. https://doi.org/10.1145/3474624.3474638 DOI: https://doi.org/10.1145/3474624.3474638
Catolino G, Palomba F, Tamburri DA, Serebrenik A. Understanding Community Smells Variability: A Statistical Approach. In: Proceedings - International Conference on Software Engineering. IEEE Computer Society. 2021;77–86. https://doi.org/10.1109/ICSE-SEIS52602.2021.00017 DOI: https://doi.org/10.1109/ICSE-SEIS52602.2021.00017
Tamburri DA, Palomba F, Kazman R. Exploring Community Smells in Open-Source: An Automated Approach. EEE Transactions on software Engineering. 2019; 47(3): 630-652. https://doi.org/10.1109/TSE.2019.2901490 DOI: https://doi.org/10.1109/TSE.2019.2901490
Tamburri DA. Software Architecture Social Debt: Managing the Incommunicability Factor. IEEE Trans Comput Soc Syst. 2019;6(1):20–37. https://doi.org/10.1109/TCSS.2018.2886433 DOI: https://doi.org/10.1109/TCSS.2018.2886433
Palomba F, Tamburri DA, Serebrenik A, Zaidman A, Fontana FA, Oliveto R. How do community smells influence code smells? In: Proceedings - International Conference on Software Engineering. 2018; 240–1. https://doi.org/10.1145/3183440.3194950 DOI: https://doi.org/10.1145/3183440.3194950
Huang Z, Shao Z, Fan G, Gao J, Zhou Z, Yang K, et al. Predicting Community Smells’ Occurrence on Individual Developers by Sentiments. 2021;12. https://doi.org/10.1109/ICPC52881.2021.00030 DOI: https://doi.org/10.1109/ICPC52881.2021.00030
Catolino G, Palomba F, Tamburri DA, Serebrenik A, Ferrucci F. Gender Diversity and Community Smells: Insights from the Trenches. IEEE Softw. 2020;37(1):10–6. https://doi.org/10.1109/MS.2019.2944594 DOI: https://doi.org/10.1109/MS.2019.2944594
Palomba F, Andrew Tamburri D, Arcelli Fontana F, Oliveto R, Zaidman A, Serebrenik A. Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells? IEEE Transactions on Software Engineering. 2021;47(1):108–29. https://doi.org/10.1109/TSE.2018.2883603 DOI: https://doi.org/10.1109/TSE.2018.2883603
Eken B, Palma F, Ayşe B, Ayşe T. An empirical study on the effect of community smells on bug prediction. Software Quality Journal. 2021;29(1):159–94. https://doi.org/10.1007/s11219-020-09538-7 DOI: https://doi.org/10.1007/s11219-020-09538-7
Tamburri TU DA, datamburri -jads, Rick Kazman tuenl, Van den Heuvel Universiteit van Tilburg -JADS WJAMvdHeuvel WJ. Splicing Community and Software Architecture Smells in Agile Teams: An industrial Study. 2019. https://doi.org/10.24251/HICSS.2019.843 DOI: https://doi.org/10.24251/HICSS.2019.843
Tamburri DA, Kruchten P, Lago P, Vliet H van. Social debt in software engineering: insights from industry. Journal of Internet Services and Applications. 2015;6(1). https://doi.org/10.1186/s13174-015-0024-6 DOI: https://doi.org/10.1186/s13174-015-0024-6
Dreesen T, Hennel P, Rosenkranz C, Kude T. “The second vice is lying, the first is running into debt.” Antecedents and mitigating practices of social debt: An exploratory study in distributed software development teams. 2021;6826–35. https://doi.org/10.24251/HICSS.2021.818 DOI: https://doi.org/10.24251/HICSS.2021.818
Ahammed T, Asad M, Sakib K. Understanding the Relationship between Missing Link Community Smell and Fix-inducing Changes. 2021;469–75. https://doi.org/10.5220/0010500604690475
Sarmento C, Massoni T, Serebrenik A, Catolino G, Tamburri D, Palomba F. Gender Diversity and Community Smells: A Double-Replication Study on Brazilian Software Teams. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering, 2022; 273–83. https://doi.org/10.1109/SANER53432.2022.00043 DOI: https://doi.org/10.1109/SANER53432.2022.00043
Lambiase S, Catolino G, Tamburri DA, Serebrenik A, Palomba F, Ferrucci F. Good fences make good neighbours? In Association for Computing Machinery (ACM); 2022; 67–78. https://doi.org/10.1109/ICSE-SEIS55304.2022.9793992 DOI: https://doi.org/10.1109/ICSE-SEIS55304.2022.9793992
Mauerer W, Joblin M, Tamburri DA, Paradis C, Kazman R, Apel S. In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study. IEEE Transactions on Software Engineering. 2022;48(8):3159–84. https://doi.org/10.1109/TSE.2021.3082074 DOI: https://doi.org/10.1109/TSE.2021.3082074
Nadri R, Rodriguez-Perez G, Nagappan M. On the Relationship Between the Developer’s Perceptible Race and Ethnicity and the Evaluation of Contributions in OSS. IEEE Transactions on Software Engineering. 2022;48(8):2955–68. https://doi.org/10.1109/TSE.2021.3073773 DOI: https://doi.org/10.1109/TSE.2021.3073773
Prana GAA, Ford D, Rastogi A, Lo D, Purandare R, Nagappan N. Including Everyone, Everywhere: Understanding Opportunities and Challenges of Geographic Gender-Inclusion in OSS. IEEE Transactions on Software Engineering. 2021; https://doi.org/10.1109/TSE.2021.3092813 DOI: https://doi.org/10.1109/TSE.2021.3092813
Mumtaz H, Paradis C, Palomba F, Tamburri DA, Kazman R, Blincoe K. A preliminary study on the assignment of GitHub issues to issue commenters and the relationship with social smells. 15th International Conference on Cooperative and Human Aspects of Software Engineering. 2022; 61–5. https://doi.org/10.1145/3528579.3529181 DOI: https://doi.org/10.1145/3528579.3529181
Pigazzini I, Fontana FA, Walter B. A study on correlations between architectural smells and design patterns. Journal of Systems and Software. 2021;178:110984. https://doi.org/10.1016/j.jss.2021.110984 DOI: https://doi.org/10.1016/j.jss.2021.110984
Soliman M, Avgeriou P, Li Y. Architectural design decisions that incur technical debt — An industrial case study. Information-and-Software-Technology. 2021;139. https://doi.org/10.1016/j.infsof.2021.106669 DOI: https://doi.org/10.1016/j.infsof.2021.106669
Aksekili AY, Stettina CJ. Women in Agile: The Impact of Organizational Support for Women’s Advancement on Teamwork Quality and Performance in Agile Software Development Teams. Lecture Notes in Business Information Processing. 2021;408:3–23. https://doi.org/10.1007/978-3-030-67084-9_1 DOI: https://doi.org/10.1007/978-3-030-67084-9_1
Bjarnason E, Gislason Bern B, Svedberg L. Inter-team communication in large-scale co-located software engineering: a case study. Empir Softw Eng. 2022;27(2). https://doi.org/10.1007/s10664-021-10027-z DOI: https://doi.org/10.1007/s10664-021-10027-z
Martini A, Stray V, Moe NB. Technical-, Social- and Process Debt in Large-Scale Agile: An Exploratory Case-Study. In: Lecture Notes in Business Information Processing. Springer Verlag. 2019; 112–9. https://doi.org/10.1007/978-3-030-30126-2_14 DOI: https://doi.org/10.1007/978-3-030-30126-2_14
Tamburri DA, Palomba F, Serebrenik A, Zaidman A. Discovering community patterns in open-source: a systematic approach and its evaluation. Vol. 24, Empirical Software Engineering. Empirical Software Engineering; 2019;1369–1417 https://doi.org/10.1007/s10664-018-9659-9 DOI: https://doi.org/10.1007/s10664-018-9659-9
Sievi-Korte O, Fagerholm F, Systä K, Mikkonen T. Dimensions of Consistency in GSD: Social Factors, Structures and Interactions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020;12562:315–30. https://doi.org/10.1007/978-3-030-64148-1_20 DOI: https://doi.org/10.1007/978-3-030-64148-1_20
Stefano M De, Pecorelli F, Tamburri DA, Palomba F, Lucia A De. Refactoring Recommendations Based on the Optimization of Socio-Technical Congruence. In: 2020 IEEE International Conference on Software Maintenance and Evolution, ICSME. 2020;794–6. https://doi.org/10.1109/ICSME46990.2020.00094 DOI: https://doi.org/10.1109/ICSME46990.2020.00094
Ahammed T, Asad M, Sakib K. Understanding the Involvement of Developers in Missing Link Community Smell: An Exploratory Study on Apache Projects. International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE. 2020; 469–75. https://doi.org/10.5220/0010500604690475 DOI: https://doi.org/10.5220/0010500604690475
Lavallée M, Robillard PN. Are we working well with others? How the multi team systems impact software quality. E-Informatica Software Engineering Journal. 2018;12(1):117–31. https://doi.org/10.5277/e-inf180105
Martini A, Bosch J. Revealing social debt with the CAFFEA framework: An antidote to architectural debt. Proceedings - 2017 IEEE International Conference on Software Architecture Workshops. 2017;179–81. https://doi.org/10.1109/ICSAW.2017.42 DOI: https://doi.org/10.1109/ICSAW.2017.42
Serebrenik A. Emotional labor of software engineers. 2017;1-6. https://tinyurl.com/46n66wmx
Palomba F, Serebrenik A, Zaidman A. Social Debt Analytics for Improving the Management of Software Evolution Tasks. 16th Edition of the BElgian-NEtherlands Software EVOLution Symposium.2017; 18-21 https://tinyurl.com/mr3edacy
M. O. Ahmad. Psychological Safety, Leadership and Non-Technical Debt in Large-Scale Agile Software Development. In: Proceedings of the 18th Conference on Computer Science and Intelligence Systems. IEEE; 2023; 327–34. https://doi.org/10.15439/2023F8595 DOI: https://doi.org/10.15439/2023F8595
C. Gote. Locating community smells in software development processes using higher-order network centralities. Soc Netw Anal Min. 2023;13:1–28. https://doi.org/10.1007/s13278-023-01120-w DOI: https://doi.org/10.1007/s13278-023-01120-w
Wieringa R, Maiden N, Mead N, Rolland C. Requirements engineering paper classification and evaluation criteria: A proposal and a discussion. Requir Eng. 2006;11(1):102–7. https://doi.org/10.1007/s00766-005-0021-6 DOI: https://doi.org/10.1007/s00766-005-0021-6
Downloads

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors grant the journal and Universidad del Valle the economic rights over accepted manuscripts, but may make any reuse they deem appropriate for professional, educational, academic or scientific reasons, in accordance with the terms of the license granted by the journal to all its articles.
Articles will be published under the Creative Commons 4.0 BY-NC-SA licence (Attribution-NonCommercial-ShareAlike).