Mostrar el registro sencillo del ítem

Human Aspects in Software Development: A Systematic Mapping Study

dc.contributor.authorRestrepo-Tamayo L.M
dc.contributor.authorGasca-Hurtado G.P.
dc.date.accessioned2023-10-24T19:25:11Z
dc.date.available2023-10-24T19:25:11Z
dc.date.created2022
dc.identifier.isbn9783031202179
dc.identifier.issn3029743
dc.identifier.urihttp://hdl.handle.net/11407/8048
dc.description.abstractSoftware development is a process that requires a high level of human talent management to ensure its success. This makes it a topic of interest to the software industry and research. Considering this interest, it is evident the need to know the aspects that have been studied, how they have been measured, and what data analysis methods have been used. This paper presents an analysis of the human aspects associated with the software development process, identifying procedures and methods used to analyze data and its measurement. A systematic mapping with a sample of 99 studies identified by their relationship with the proposed topic was used as the research method. The main findings show that one of the most studied is personality. This aspect is related to the performance of software development teams and is a key variable for its conformation. Concerning the most used data source, we find the survey based on self-reporting. Finally, descriptive statistics is the most frequent method of analysis, which is performed prior to other methods such as correlation or regression analysis. The results suggest a wide spectrum of human aspects to be studied in Software Engineering, and interesting potential for analysis by identifying interesting methods other than self-reporting. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.eng
dc.language.isoeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85142624351&doi=10.1007%2f978-3-031-20218-6_1&partnerID=40&md5=45c018fd26b12321fb78acff009c8a43
dc.sourceLect. Notes Comput. Sci.
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)eng
dc.subjectHuman aspectseng
dc.subjectMetricseng
dc.subjectSoftware developmenteng
dc.subjectSystematic mapping studyeng
dc.titleHuman Aspects in Software Development: A Systematic Mapping Studyeng
dc.typeConference Paper
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemasspa
dc.type.spaDocumento de conferencia
dc.identifier.doi10.1007/978-3-031-20218-6_1
dc.relation.citationvolume13632 LNCS
dc.relation.citationstartpage1
dc.relation.citationendpage22
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationRestrepo-Tamayo, L.M., Universidad de Medellín, Carrera 87 No. 30-65, Medellín, 50026, Colombia
dc.affiliationGasca-Hurtado, G.P., Universidad de Medellín, Carrera 87 No. 30-65, Medellín, 50026, Colombia
dc.relation.referencesStaron, M., Meding, W., (2018) Software Development Measurement Programs: Development, Management and Evolution, , https://doi.org/10.1007/978-3-319-91836-5, Springer, Cham
dc.relation.referencesHazzan, O., Hadar, I., Why and how can human-related measures support software development processes? (2008) J. Syst. Softw., 81, pp. 1248-1252. , https://doi.org/10.1016/j.jss.2008.01.037
dc.relation.referencesAcuña, S.T., Gómez, M., Juristo, N., How do personality, team processes and task characteristics relate to job satisfaction and software quality? (2009) Inf. Softw. Technol., 51, pp. 627-639. , https://doi.org/10.1016/j.infsof.2008.08.006
dc.relation.referencesSadowski, C., Zimmermann, T., (2019) Rethinking Productivity in Software Engineering, , https://doi.org/10.1007/978-1-4842-4221-6, Apress, Berkeley, CA
dc.relation.referencesMachuca-Villegas, L., Gasca-Hurtado, G.P., Towards a social and human factor classification related to productivity in software development teams (2020) Mejia, J., Muñoz, M., Rocha, Á., A. Calvo-Manzano, J. (Eds.) CIMPS 2019. AISC, Vol. 1071, pp. 36-50. , https://doi.org/10.1007/978-3-030-33547-2_4, Springer, Cham
dc.relation.referencesCapretz, L.F., Ahmed, F., da Silva, F.Q.B., Soft sides of software (2017) Inf. Softw. Technol., 92, pp. 92-94. , https://doi.org/10.1016/j.infsof.2017.07.011
dc.relation.referencesCha, S., Taylor, R.N., Kang, K., (2019) Handbook of Software Engineering, , https://doi.org/10.1007/978-3-030-00262-6, Springer, Cham
dc.relation.referencesSchmidt, R.F., Software engineering fundamentals (2013) Software Engineering, pp. 1-6
dc.relation.referencesLicorish, S.A., Macdonell, S.G., Exploring software developers’ work practices: Task differences, participation, engagement, and speed of task resolution (2017) Inf. Manag., 54, pp. 364-382. , https://doi.org/10.1016/j.im.2016.09.005
dc.relation.referencesSudhakar, G.P., Farooq, A., Patnaik, S., Soft factors affecting the performance of software development teams (2011) Team Perform. Manag., 17, pp. 187-205. , https://doi.org/10.1108/13527591111143718
dc.relation.referencesTrendowicz, A., Münch, J., Factors influencing software development productivity-state-of-the-art and industrial experiences (2009) Advances in Computers, pp. 185-241
dc.relation.referencesCanedo, E.D., Santos, G.A., Factors affecting software development productivity: An empirical study (2019) ACM International Conference Proceeding Series, pp. 307-316. , Association for Computing Machinery
dc.relation.referencesDevadas, U.M., Dharmapala, Y.Y., Soft skills evaluation in the information technology and business process management industry in Sri Lanka: Skills, methods and problems (2021) Int. J. Econ. Bus. Hum. Behav., 2 (3). , https://doi.org/10.5281/zenodo.5280309
dc.relation.referencesAhmed, F., Capretz, L.F., Campbell, P., Evaluating the demand for soft skills in software development (2012) IT Prof, 14, pp. 44-49. , https://doi.org/10.1109/MITP.2012.7
dc.relation.referencesMachuca-Villegas, L., Gasca-Hurtado, G.P., Restrepo-Tamayo, L.M., Morillo Puente, S., Social and human factor classification of influence in productivity in software development teams (2020) Eurospi Systems, Software and Services Process Improvement, pp. 717-729
dc.relation.referencesMachuca-Villegas, L., Gasca-Hurtado, G.P., Morillo Puente, S., Restrepo-Tamayo, L.M., An instrument for measuring perception about social and human factors that influence software development productivity (2021) J. Univers. Comput. Sci., 27, pp. 111-134. , https://doi.org/10.3897/jucs.65102
dc.relation.referencesAmrit, C., Daneva, M., Damian, D., Human factors in software development: On its underlying theories and the value of learning from related disciplines. A guest editorial introduction to the special issue (2014) Inf. Softw. Technol., 56, pp. 1537-1542. , https://doi.org/10.1016/j.infsof.2014.07.006
dc.relation.referencesPetersen, K., Feldt, R., Mujtaba, S., Mattsson, M., Systematic mapping studies in software engineering (2008) 12Th International Conference on Evaluation and Assessment in Software Engineering, EASE 2008
dc.relation.referencesBrereton, P., Kitchenham, B.A., Budgen, D., Turner, M., Khalil, M., Lessons from applying the systematic literature review process within the software engineering domain (2007) J. Syst. Softw., 80, pp. 571-583. , https://doi.org/10.1016/j.jss.2006.07.009
dc.relation.referencesPetticrew, M., Roberts, H., (2008) Systematic Reviews in the Social Sciences: A Practical Guide
dc.relation.referencesVarona, D., Capretz, L.F., A comparison of junior and senior software engineering stu-dents’ personalities (2014) CHASE Cooperative and Human Aspects of Software Engineering, pp. 131-132
dc.relation.referencesMeyer, G.J., Psychological testing and psychological assessment (2001) Am. Psychol., 56, pp. 128-165. , https://doi.org/10.1037//OOO3-O66X.56.2.128
dc.relation.referencesGawronski, B., de Houwer, J., Implicit measures for social and personality psychology (2014) Handbook of Research Methods in Social and Personality Psychology, pp. 282-310
dc.relation.referencesTenenberg, J., An institutional analysis of software teams (2008) Int. J. Hum. Comput. Stud., 66, pp. 484-494. , https://doi.org/10.1016/j.ijhcs.2007.08.002
dc.relation.referencesCruz, S., Fabio, Q.B., Fernando, L., Forty years of research on personality in software engineering: A mapping study (2015) Comput. Human Behav., 46, pp. 94-113. , https://doi.org/10.1016/j.chb.2014.12.008
dc.relation.referencesFerreira, N.N.V., Langerman, J.J., The correlation between personality type and individual performance on an ICT project (2014) ICCSE International Conference on Computer Science & Education, pp. 425-430
dc.relation.referencesWiesche, M., Krcmar, H., The relationship of personality models and development tasks in software engineering (2014) SIGMIS-CPR Conference on Computers and People Research, pp. 149-161
dc.relation.referencesSoomro, A.B., Salleh, N., Mendes, E., Grundy, J., Burch, G., Nordin, A., The effect of software engineers’ personality traits on team climate and performance: a systematic literature review (2016) Inf. Softw. Technol., 73, pp. 52-65. , https://doi.org/10.1016/j.infsof.2016.01.006
dc.relation.referencesBano, A., Salleh, N., Mendes, E., Grundy, J., Burch, G., Nordin, A., The effect of software engineers’ personality traits on team climate and performance: a systematic literature review (2016) Inf. Softw. Technol., 73, pp. 52-65. , https://doi.org/10.1016/j.infsof.2016.01.006
dc.relation.referencesFreitas, F., Mendes, E., Salleh, N., The relationship between personality and decision-making: A systematic literature review (2019) Inf. Softw. Technol., 111, pp. 50-71. , https://doi.org/10.1016/j.infsof.2019.03.010
dc.relation.referencesJia, J., Zhang, P., Zhang, R., A comparative study of three personality assessment models in software engineering field (2015) ICSESS International Conference on Software Engineering and Service Science, pp. 7-10. , IEEE
dc.relation.referencesHannay, J.E., Arisholm, E., Engvik, H., Sjøberg, D.I.K., Effects of personality on pair programming (2010) IEEE Trans. Softw. Eng., 36, pp. 61-80
dc.relation.referencesHuang, F., Liu, B., Song, Y., Keyal, S., Science of computer programming the links between human error diversity and software diversity: Implications for fault diversity seeking (2014) Sci. Comput. Program., 89, pp. 350-373. , https://doi.org/10.1016/j.scico.2014.03.004
dc.relation.referencesGulati, J., A study of relationship between performance, temperament and personality of a software programmer (2016) SIGSOFT Softw. Eng. Notes, 41, pp. 1-5. , https://doi.org/10.1145/2853073.2853089
dc.relation.referencesKarimi, Z., Baraani-Dastjerdi, A., Ghasem-Aghaee, N., Wagner, S., Links between the personalities, styles and performance in computer programming (2016) J. Syst. Softw., 111, pp. 228-241. , https://doi.org/10.1016/j.jss.2015.09.011
dc.relation.referencesCaulo, M., Francese, R., Scanniello, G., Tortora, G., Relationships between personality traits and productivity in a multi-platform development context (2021) The International Conference on Evaluation and Assessment in Software Engineering (EASE), pp. 70-79
dc.relation.referencesMendes, F., Mendes, E., Salleh, N., Oivo, M., Insights on the relationship between decision-making style and personality in software engineering (2021) Inf. Softw. Technol., 136. , https://doi.org/10.1016/j.infsof.2021.106586
dc.relation.referencesLicorish, S.A., Macdonell, S.G., Communication and personality profiles of global software developers (2015) Inf. Softw. Technol., 64, pp. 113-131. , https://doi.org/10.1016/j.infsof.2015.02.004
dc.relation.referencesGómez, M.N., Acuña, S.T., A replicated quasi-experimental study on the influence of personality and team climate in software development (2013) Empir. Softw. Eng., 19 (2), pp. 343-377. , https://doi.org/10.1007/s10664-013-9265-9
dc.relation.referencesVishnubhotla, S.D., Mendes, E., Lundberg, L., Investigating the relationship between personalities and agile team climate of software professionals in a telecom company (2020) Inf. Softw. Technol., 126. , https://doi.org/10.1016/j.infsof.2020.106335
dc.relation.referencesMartinez, L., Guillermo, L., Rodríguez-Díaz, A., Castro, J., Experiences in software engineering courses using psychometrics with RAMSET (2010) Iticse Innovation and Technology in Computer Science Education, pp. 244-248
dc.relation.referencesSilva, F.Q.B., Team building criteria in software projects: A mix-method replicated study (2013) Inf. Softw. Technol., 55, pp. 1316-1340. , https://doi.org/10.1016/j.infsof.2012.11.006
dc.relation.referencesKosti, M., Feldt, R., Angelis, L., Personality, emotional intelligence and work preferences in software engineering: An empirical study (2014) Inf. Softw. Technol., 56, pp. 973-990. , https://doi.org/10.1016/j.infsof.2014.03.004
dc.relation.referencesPapatheocharous, E., Belk, M., Nyfjord, J., Germanakos, P., Samaras, G., Personalised continuous software engineering (2014) Rcose Rapid Continuous Software Engineering, pp. 57-62
dc.relation.referencesCapretz, F., Varona, D., Raza, A., Influence of personality types in software tasks choices (2015) Comput. Human Behav., 52, pp. 373-378. , https://doi.org/10.1016/j.chb.2015.05.050
dc.relation.referencesKosti, M.V., Feldt, R., Angelis, L., Archetypal personalities of software engineers and their work preferences: A new perspective for empirical studies (2015) Empir. Softw. Eng., 21 (4), pp. 1509-1532. , https://doi.org/10.1007/s10664-015-9395-3
dc.relation.referencesYilmaz, M., Connor, R.V.O., Colomo-Palacios, R., Clarke, P., An examination of personality traits and how they impact on software development teams (2017) Inf. Softw. Technol., 86, pp. 101-122. , https://doi.org/10.1016/j.infsof.2017.01.005
dc.relation.referencesMuñoz, M., Peña, A., Mejia, J., Rangel, N., Torres, C., Hernández, L., Building high effec-tives teams using a virtual environment (2018) Eurospi Systems, Software and Services Process Improvement, pp. 554-568
dc.relation.referencesAkarsu, Z., Orgun, P., Dinc, H., Gunyel, B., Yilmaz, M., Assessing personality traits in a large scale software development company: Exploratory industrial case study (2019) Eurospi 2019. CCIS, 1060, pp. 192-206. , https://doi.org/10.1007/978-3-030-28005-5_15, Walker, A., O’Connor, R.V., Messnarz, R. (eds.), Springer, Cham
dc.relation.referencesFeldt, R., Angelis, L., Torkar, R., Samuelsson, M., Links between the personalities, views and attitudes of software engineers (2010) Inf. Softw. Technol., 52, pp. 611-624. , https://doi.org/10.1016/j.infsof.2010.01.001
dc.relation.referencesCalefato, F., Lanubile, F., Vasilescu, B., A large-scale, in-depth analysis of developers’ personalities in the Apache ecosystem (2019) Inf. Softw. Technol., 114, pp. 1-20. , https://doi.org/10.1016/j.infsof.2019.05.012
dc.relation.referencesLicorish, S.A., Macdonell, S.G., Personality profiles of global software developers (2014) EASE Evaluation and Assessment in Software Engineering, pp. 1-10
dc.relation.referencesCapiola, A., Trust in software: Attributes of computer code and the human factors that influence utilization metrics (2019) HCII 2019. CCIS, 1032, pp. 190-196. , https://doi.org/10.1007/978-3-030-23522-2_24, Stephanidis, C. (ed.), Springer, Cham
dc.relation.referencesDieste, O., Empirical evaluation of the effects of experience on code quality and programmer productivity: An exploratory study (2017) Empir. Softw. Eng., 22 (5), pp. 2457-2542. , https://doi.org/10.1007/s10664-016-9471-3
dc.relation.referencesJuneja, K., Design of programmer’s skill evaluation metrics for effective team selection (2020) Wireless Pers. Commun., 114 (4), pp. 3049-3080. , https://doi.org/10.1007/s11277-020-07517-6
dc.relation.referencesda Silva, L.M., Autonomy in software engineering: A preliminary study on the influence of education level and professional experience (2017) ACM/IEEE International Symposium on Empirical Software Engineering and Measurement Autonomy, pp. 229-234. , 2017
dc.relation.referencesMarsicano, G., Silva, F.Q.B., Seaman, C.B., Adaid-Castro, B.G., The Teamwork Process Antecedents (TPA) questionnaire: Developing and validating a comprehensive measure for assessing antecedents of teamwork process quality (2020) Empir. Softw. Eng., 25, pp. 3928-3976
dc.relation.referencesFagerholm, F., Ikonen, M., Kettunen, P., Münch, J., Roto, V., Abrahamsson, P., Performance alignment work: How software developers experience the continuous adaptation of team performance in Lean and Agile environments (2015) Inf. Softw. Technol., 64, pp. 132-147. , https://doi.org/10.1016/j.infsof.2015.01.010
dc.relation.referencesvan Kelle, E., Visser, J., Plaat, A., van der Wijst, P., An empirical study into social success factors for agile software development (2015) CHASE Cooperative and Human Aspects of Software Engineering, pp. 77-80
dc.relation.referencesSchneider, K., Liskin, O., Paulsen, H., Kauffeld, S., Media, mood, and meetings: Related to project success? (2015) ACM Trans. Comput. Educ., 15, pp. 1-33
dc.relation.referencesde Sá Leitão Júnior, N.G., de Farias Junior, I.H., Marczak, S., Santos, R., Furtado, F., de Moura, H.P., (2017) Evaluation of a Preliminary Assessment Method for Identifying the Maturity of Communication in Distributed Software Development
dc.relation.referencesBettenburg, N., Hassan, A.E., Studying the impact of social interactions on software quality (2013) Empir. Softw. Eng., 18, pp. 375-431. , https://doi.org/10.1007/s10664-012-9205-0
dc.relation.referencesRyan, S., Connor, R.V.O., Acquiring and sharing tacit knowledge in software development teams: An empirical study (2013) Inf. Softw. Technol., 55, pp. 1614-1624. , https://doi.org/10.1016/j.infsof.2013.02.013
dc.relation.referencesAlahyari, H., The role of social interactions in value creation in agile software development processes (2015) SSE Social Software Engineering, pp. 17-20
dc.relation.referencesXiang, C., Yang, Z., Zhang, L., Improving IS development teams’ performance during requirement analysis in project—the perspectives from shared mental model and emotional intelligence (2016) Int. J. Proj. Manag., 34, pp. 1266-1279. , https://doi.org/10.1016/j.ijproman.2016.06.009
dc.relation.referencesFrança, C., Sharp, H., Silva, F.Q.B., Motivated software engineers are engaged and focused, while satisfied ones are happy (2014) ESEM Empirical Software Engineering and Measurement, pp. 1-8
dc.relation.referencesKuusinen, K., Petrie, H., Fagerholm, F., Mikkonen, T., Flow, intrinsic motivation, and developer experience in software engineering (2016) International Conference on Agile Software Development, pp. 104-117
dc.relation.referencesAndré, M., Baldoquín, M.G., Acuña, S.T., Formal model for assigning human resources to teams in software projects (2011) Inf. Softw. Technol., 53, pp. 259-275. , https://doi.org/10.1016/j.infsof.2010.11.011
dc.relation.referencesFrança, C., Silva, F.Q.B., Sharp, H., Motivation and satisfaction of software engineers (2020) IEEE Trans. Softw. Eng., 46, pp. 118-140
dc.relation.referencesFreire, A., Perkusich, M., Saraiva, R., Almeida, H., Perkusich, A., A Bayesian networks-based approach to assess and improve the teamwork quality of agile teams (2018) Inf. Softw. Technol., 100, pp. 119-132. , https://doi.org/10.1016/j.infsof.2018.04.004
dc.relation.referencesGünsel, A., Açikgšz, A., Tükel, A., Öğüt, E., The role of flexibility on software development performance: an empirical study on software development teams (2012) Procedia-Soc. Behav. Sci., 58, pp. 853-860. , https://doi.org/10.1016/j.sbspro.2012.09.1063
dc.relation.referencesSantos, R.E.S., Correia-Neto, J.S., Silva, F.Q.B., Souza, R.E.C., Would you like to motivate software testers? Ask them how (2017) ACM/IEEE International Symposium on Empirical Software Engineering and Measurement Would, pp. 95-104
dc.relation.referencesMa, Z., A data-driven risk measurement model of software developer turnover (2019) Soft. Comput., 24 (2), pp. 825-842. , https://doi.org/10.1007/s00500-019-04540-z
dc.relation.referencesSharp, H., Baddoo, N., Beecham, S., Hall, T., Robinson, H., Models of motivation in software engineering (2009) Inf. Softw. Technol., 51, pp. 219-233. , https://doi.org/10.1016/j.infsof.2008.05.009
dc.relation.referencesSilva, F.Q.B., Franca, A.C.C., Towards understanding the underlying structure of motivational factors for software engineers to guide the definition of motivational programs (2012) J. Syst. Softw., 85, pp. 216-226. , https://doi.org/10.1016/j.jss.2010.12.017
dc.relation.referencesBordel, B., Alcarria, R., Assessment of human motivation through analysis of physiological and emotional signals in Industry 4.0 scenarios (2017) J. Ambient. Intell. Humaniz. Comput., pp. 1-21. , https://doi.org/10.1007/s12652-017-0664-4
dc.relation.referencesLenberg, P., Feldt, R., Psychological safety and norm clarity in software engineering teams (2018) CHASE Cooperative and Human Aspects of Software Engineering, pp. 79-86
dc.relation.referencesFelderer, M., Travassos, G., (2020) Contemporary Empirical Methods in Software Engineering, , https://doi.org/10.1007/978-3-030-32489-6, Springer, Cham
dc.relation.referencesFritz, T., Murphy, G.C., Murphy-Hill, E., Ou, J., Hill, E., Degree-of-knowledge: Modeling a developer’s knowledge of code (2014) ACM Trans. Softw. Eng. Methodol., 23 (2), pp. 1-42
dc.relation.referencesCárdenas-Castro, C., Gil Julio, J.C., Rodríguez, P., Soft skills training: Performance psychology applied to software development (2019) IEEE/ACM 12Th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE), pp. 115-116
dc.relation.referencesBasirati, M.R., Otasevic, M., Rajavi, K., Böhm, M., Krcmar, H., Understanding the relationship of conflict and success in software development projects (2020) Inf. Softw. Technol., 126. , https://doi.org/10.1016/j.infsof.2020.106331
dc.relation.referencesBesker, T., Ghanbari, H., Martini, A., Bosch, J., The influence of Technical Debt on software developer morale (2020) J. Syst. Softw., 167. , https://doi.org/10.1016/j.jss.2020.110586
dc.relation.referencesOlsson, J., Risfelt, E., Besker, T., Martini, A., Torkar, R., Measuring affective states from technical debt: A psychoempirical software engineering experiment (2021) Empir. Softw. Eng., 26
dc.relation.referencesShastri, Y., Hoda, R., Amor, R., The role of the project manager in agile software development projects (2021) J. Syst. Softw., 173. , https://doi.org/10.1016/j.jss.2020.110871
dc.relation.referencesEasterbrook, S., Singer, J., Storey, M.A., Damian, D., Selecting empirical methods for software engineering research (2008) Guide to Advanced Empirical Software Engineering, pp. 285-311
dc.relation.referencesKitchenham, B.A., Preliminary guidelines for empirical research in software engineering (2002) IEEE Trans. Softw. Eng., 28, pp. 721-734
dc.relation.referencesGirardi, D., Novielli, N., Fucci, D., Lanubile, F., Recognizing developers’ emotions while programming (2020) ICSE International Conference on Software Engineering, pp. 666-677
dc.relation.referencesde Magalhães, C.V., Toward understanding work characteristics in software engineering (2016) SIGSOFT Softw. Eng. Notes, 41, pp. 1-6. , https://doi.org/10.1145/3011286.3011
dc.relation.referencesSantos, R.E.S., Work design and job rotation in software engineering: Results from an industrial study (2019) CHASE Cooperative and Human Aspects of Software Engineering, pp. 139-146
dc.relation.referencesGraziotin, D., Fagerholm, F., Wang, X., Abrahamsson, P., On the unhappiness of software developers (2017) EASE Evaluation and Assessment in Software Engineering
dc.relation.referencesGraziotin, D., Fagerholm, F., Wang, X., Abrahamsson, P., What happens when software developers are (un)happy (2018) J. Syst. Softw., 140, pp. 32-47. , https://doi.org/10.1016/j.jss.2018.02.041
dc.relation.referencesRusso, D., Hanel, P.H.P., Altnickel, S., van Berkel, N., Predictors of well-being and productivity among software professionals during the COVID-19 pandemic – a longitudinal study. Empir. Softw (2021) Eng, 26 (4), pp. 1-63. , https://doi.org/10.1007/s10664-021-09945-9
dc.relation.referencesGonzález Llaneza, F.M., (2007) Instrumentos De evaluación psicológica, , La Habana
dc.relation.referencesAndersson, D., Rankin, A., Diptee, D., Approaches to team performance assessment: A comparison of self-assessment reports and behavioral observer scales (2017) Cogn. Technol. Work, 19 (2-3), pp. 517-528. , https://doi.org/10.1007/s10111-017-0428-0
dc.relation.referencesPassos, C., Cruzes, D.S., Applying theory of reasoned action in the context of software development practices insights into team intention and behavior (2013) EASE Evaluation and Assessment in Software Engineering, pp. 2-11
dc.relation.referencesChristov, S.C., Hoffman, M.E., Experiential learning of software project management and software development via course collaboration (2019) SIGCSE 2019-Proceedings of ACM Technical Symposium on Computer Science Education, pp. 2013-2019
dc.relation.referencesFritz, T., Begel, A., Müller, S.C., Yigit-Elliott, S., Züger, M., Using psycho-physiological measures to assess task difficulty in software development categories and subject descriptors (2014) ICSCA International Conference on Software and Computer Applications, pp. 402-413
dc.relation.referencesde Oliveira Neto, F.G., Torkar, R., Feldt, R., Gren, L., Furia, C.A., Huang, Z., Evolution of statistical analysis in empirical software engineering research: Current state and steps forward (2019) J. Syst. Softw., 156, pp. 246-267. , https://doi.org/10.1016/j.jss.2019.07.002
dc.relation.referencesWackerly, D.D., Mendenhall, W., Scheaffer, R.L., (2010) Estadística Matemática Con Aplicaciones
dc.relation.referencesDevore, J.L., Probability and statistics for engineering and the sciences (2008) Cengage Learning ALL, , Canadá
dc.relation.referencesColomo-Palacios, R., Casado-Lumbreras, C., Soto-Acosta, P., García-Peñalvo, F.J., Tovar-Caro, E., Competence gaps in software personnel: A multi-organizational study (2013) Comput. Human Behav., 29, pp. 456-461. , https://doi.org/10.1016/j.chb.2012.04.021
dc.relation.referencesMarczak, S., Gomes, V., On the development of a theoretical model of the impact of trust in the performance of distributed software projects (2013) 2013 6Th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE), pp. 97-100. , https://doi.org/10.1109/CHASE.2013.6614740
dc.relation.referencesBernárdez, B., Cortés, A.R., A controlled experiment to evaluate the effects of mindfulness in software engineering (2014) Categories and Subject Descriptors. In: ESEM Empirical Software Engineering and Measurement
dc.relation.referencesSutanto, J., Zurich, E.T.H., Investigating task coordination in globally dispersed teams (2015) ACM Trans. Manag. Inf. Syst., 6 (2), pp. 1-31
dc.relation.referencesLenberg, P., Wallgren Tengberg, L.G., Feldt, R., An initial analysis of software engineers’ attitudes towards organizational change (2016) Empir. Softw. Eng., 22 (4), pp. 2179-2205. , https://doi.org/10.1007/s10664-016-9482-0
dc.relation.referencesKropp, M., Meier, A., Anslow, C., Biddle, R., Satisfaction and its correlates in agile software development (2020) J. Syst. Softw., 164. , https://doi.org/10.1016/j.jss.2020.110544
dc.relation.referencesFaraway, J., (2014) Linear Models with R, , Taylor & Francis
dc.relation.referencesGren, L., Standards of validity and the validity of standards in behavioral software engineering research: The perspective of psychological test theory (2018) International Symposium on Empirical Software Engineering and Measurement
dc.relation.referencesLloret-Segura, S., Ferreres-Traver, A., Hernández-Baeza, A., Tomás-Marco, I., El análisis factorial exploratorio de los ítems: Una guía práctica, revisada y actualizada (2014) An. Psicol., 30, pp. 1151-1169. , https://doi.org/10.6018/analesps.30.3.199361
dc.relation.referencesRusso, D., Stol, K.-J., PLS-SEM for software engineering research. ACM Comput (2021) Surv, 54, pp. 1-38. , https://doi.org/10.1145/3447580
dc.relation.referencesBuse, R.P.L., Zimmermann, T., (2010) Analytics for Software Development. Proc. FSE/SDP Work. Futur. Softw. Eng. Res. Foser 2010, pp. 77-80. , https://doi.org/10.1145/1882362.1882379
dc.relation.referencesAdams, W., Conducting semi-structured interviews (2015) Handbook of Practical Program Evaluation, pp. 492-505. , Jossey-Bass
dc.relation.referencesSilva, F.Q.B., The innovative behaviour of software engineers: Findings from a pilot case study (2016) ESEM Empirical Software Engineering and Measurement
dc.relation.referencesSantos, R.E.S., da Silva, F.Q.B., de Magalhães, C.V.C., Monteiro, C.V.F., Building a theory of job rotation in software engineering from an instrumental case study (2016) 2016 IEEE/ACM 38Th IEEE International Conference on Software Engineering Building, pp. 971-981
dc.relation.referencesMinetto, B., Synthesizing researches on knowledge management and agile software development using the meta-ethnography method (2021) J. Syst. Softw., 178. , https://doi.org/10.1016/j.jss.2021.110973
dc.relation.referencesRalph, P., Kelly, P., The dimensions of software engineering success (2014) ICSE International Conference on Software Engineering, pp. 24-35
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín
dc.contributor.event28th International Conference on Collaboration Technologies and Social Computing, CollabTech 2022


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem