Notice bibliographique
Résumé
Today, software system is designed by humans and works for humans.In the dynamic, continuous, complex and chaotic software development process, human is at the core.Through observing historical evolutions and empirical studies of software engineering methodologies, we can see that when more human factors are considered in the development process, the methodology can be more successful in the real world.Agile Software Development (ASD) is one of the software engineering methodologies with successful use of human factors.ASD is a relatively new software development paradigm that has gained popularity over the last decade.It is a group of methodologies based on iterative and incremental software development, where requirements and functions evolve through collaboration between self-organizing and cross-functional teams.Existing ASD methodologies, which have focused on some human factors, such as openness, collaboration, proactivity, self-organizing, and communication etc., are more people oriented than plandriven methodologies.However, they lack good quantitative methods to analyze the impacts of human factors on the process, which rely heavily on project managers and team members' intuition and feeling.Moreover, according to our empirical studies, this intuitive and subjective decision making process without data analytics affects the progress, quality and productivity of ASD.Through our four years of experiments on students' Scrum based ASD process, we have gained deep understanding into the human factors of agile methodology.We designed an agile project management tool (APM)the Human-centered Agile Software Engineering Summary xiii (HASE) collaboration development platform to support more than 400 students who selforganized into 80 teams to practice ASD.In these experiments, we have focused on two research directions.The first research direction is to study the agile software development process, through data collections in the lab and interactions with the software developers during software engineering course studies.The second research direction is to design new collaboration tools for agile team members to deal with difficult situations such as detecting users' real goals from specific stories, allocating tasks to novice members or distributed team members based on current contexts, and dealing with possible task delay or team member's emotional crisis.These two research directions are mutually reinforcing: the analysis of agile software development process inspires better development of the HASE platform, and the problems discovered through the usage of HASE platform shed light on the issues of the current agile software development process.These two aspects are integrated as a human computation system (HCS), in which human and computer work together to solve problems in the agile software development process.In this research, we treat agile process as a HCS and explore the usage of goal-oriented method, agent-oriented method and emotion modeling method to allow agile teams to quantitatively handle human factors during the development process with fewer burdens.Our research mainly focuses on the following questions in ASD practice: How to help product owners or project managers uncover stakeholders' real goals hidden in user stories described in natural language and intuitively present them to the team? How to assist developers decide whether to accept or refuse new tasks based on the current situation before a new iteration start? How does the developers' mood or team morale swing affect the task performing process and the quality of artifacts? Summary xivTo address these three questions, we have conducted a series of experiments, simulations and data analysis, and contributed a series of solutions and insights in this research, including 1) a Goal Net based method to enhance goal and requirement management for ASD process, 2) a novel Simple Multi-Agent Real-Time (SMART) approach to enhance intelligent task allocation for ASD process, 3) a Fuzzy Cognitive Map (FCM) based method to enhance emotion and morale management for ASD process, 4) a large-scale in-depth empirical analysis of human factors in the agile development process through the continuous observation of student ASD teams, and 5) the identification of an ASD process as a humancomputation system that uses humans to perform tasks that computers are not good at and computers to assist human decision making.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».