Job rotation in software engineering : theory and practice
Notice bibliographique
Résumé
Job rotation has been proposed as a managerial practice to be applied in the organizational environment to reduce job monotony, boredom, and exhaustion resulting from job simplification, specialization, and repetition. The scientific literature distinguishes between job-to-job and project-to-project rotations. Despite the potential benefits and its actual use by software companies, software engineering research did not accumulate an extensive body of scientific knowledge about benefits and limitations of job rotation in software engineering practice. In fact, there is a known knowledge gap regarding how practitioners can apply this practice in software industry. This research aims to identify and discuss evidence about project-to-project (P2P) job rotation in software companies, seeking to understand its benefits and limitations, in order to build a model that could guide research and practice towards the use of this managerial practice in software development environments. A mix-method research strategy was applied to collect, analyze, and synthesize empirical evidence in order to build and validate a consistent model that could be applied to guide industry practice. This research identified evidence from multiple sources and from different data types (qualitative and quantitative) about the use, benefits and limitations of rotation in software engineering practice. An amount of 25 factors (benefits and limitations) of such rotations in software engineering were identified and discussed. Different research methods yielded complementary evidence that could be used to inform practitioners about the effects of this managerial practice in software professionals’ work. Finally, a managerial model was build and its comprehensiveness was checked in order to be applied in software companies in the process of plan, execute and evaluate job rotations. Before this research, evidence related to job rotations in Software Engineering was restricted to studies that did not investigate this phenomenon as their primary goals. Now, relevant novel evidence and significant findings based on practice were added to the body of knowledge about this specific topic, supporting researchers into the development of future research about the theme, and guiding practitioners into the improvement industry practice.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».