Development of a scaling factors framework to improve the approximation of software functional size with cosmic - iso19761
Notice bibliographique
Résumé
Many software development organizations strive to deliver high-quality products while keeping a balance between customer satisfaction, time, and budget. The estimation of the effort of software development projects is one of the major challenges of these software development organizations. This challenge is typically faced at early phases of the software development life cycle. To tackle this challenge, the software development organizations use early estimation techniques to obtain early effort estimates (i.e. a priori estimates) in order to help project managers and technical leaders in projects planning and management. One of the methodologies for a priori effort estimation is based on the approximation of the expected software functionality. This requires the use of a measurement method to quantify this functionality: the literature refers to the measurement of the functional size of software products—including business applications. Various international standards have been adopted to measure the functional size of software such as ISO 19761: COSMIC. However, during the early phases of the software development life cycle, and more specifically in the approximation of the functional size of the software expected to be developed, the lack of detailed and complete software requirements specifications is common, which leads to many challenges. For instance, the level of granularity (i.e. the level of details) of the functional requirements specifications of software is identified subjectively using intuition, experience and/or opinions of the field experts. Also, there is no standardized notation to define a standard set of scaling factors to be assigned by the requirements engineers to the functional requirements specifications of software projects to identify theirs levels of granularity. These challenges affect the quality of the functional size approximation of software development projects, since the result of the functional size approximation process is one of the primary inputs for the a priori effort estimation process. These challenges prevent the estimators of software projects from building realistic effort estimation models. The motivation of this research project is to help software organizations and in particular projects managers and technical leaders to build more accurate effort estimation models by improving one of the inputs for the effort estimation process, in order to improve the planning, the management, and the development of software at early phases of the software development life cycle. The goal of this research project is to improve one of the inputs of the a priori effort estimation process, and in particular the functional size approximation of software development projects. The main research objective is to design a framework—to be used by the requirements engineers—that assigns scaling factors to early versions of functional requirements specifications of software to identify their levels of granularity at the early stages of the software development life cycle. To achieve this research objective, the main phases of the research methodology are: • exploratory research: to investigate the impact of the research issue on the approximation of the functional size approximation process; • framework design: to design the framework that assigns scaling factors to functional requirements specifications to identify their levels of granularity; and • framework verification: to verify the usability of the framework by different groups of participants with different experience profiles, and to verify the applicability of the framework with a variety of case studies representing different software systems. The main outcome of this research project is a framework that consists of: a meta-model that identifies the relevant concepts and the relationships that need to be collected by the requirements engineers for achieving full functional specification of software requirements specifications, as well as criteria that identify the levels of granularity of software requirements specifications, and assign scaling factors to rank their levels of granularity. This framework is verified for usability with the same case study by three groups of practitioners in the software engineering industry and verified next for applicability with four case studies.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,006 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,007 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
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 ».