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Record W1506565716

Software product quality requirements engineering method: soquarem

2012· article· en· W1506565716 on OpenAlexaff
Witold Suryn, Rachida Djouab

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceRequirementSoftware quality controlSoftware engineeringRequirements engineeringSoftware quality analystQuality (philosophy)Software quality managementSystems engineeringQuality of analytical resultsProcess managementSoftware qualityQuality managementSoftware developmentRisk analysis (engineering)Quality policyEngineeringSoftwareOperations managementManagement system
DOInot available

Abstract

fetched live from OpenAlex

The IT industry needs reliable data about Requirements (QRs) to adequately evaluate systems and their architecture. management of the software product is an emerging discipline aiming to enhance the software product quality by addressing its quality requirements. Dealing with this kind of is not easy and implies much effort from practitioners, better involvement of interested stakeholders and a solid knowledge in quality management techniques. In fact they are vague, difficult to define and often conflict with other requirements. New approaches toward QRs management are developed to resolve problems of traditional software engineering views as: a) lack of systematic guidelines on how to elicit QRs; b) difficulty to identify QRs and to represent them in models and processes. In the context of a proposal for a SOftware product QUAlity Requirements Engineering Method (SOQUAREM), this thesis provides a structured QRs engineering process with its supporting ISO/IEC SQuaRE 25030 standard, management techniques and concepts. SOQUAREM process spans 2 high levels of abstraction (business and system) and six conceptual phases such as: identification and refinement of business goals, derivation and consolidation of the quality attributes and their integration into the functional process. The proposed SOQUAREM illustrates in a structured and easy to use way how several concepts can be combined at different organizational levels to identify, represent, document and retrace quality attributes. This document is divided into six chapters: the first chapter presents a background and related work on Quality requirements in general and on various quality management methods such as MOQARE (Misuse-Oriented QuAlity Requirements Engineering)), IESE NFR (Institute for Experimental Software Engineering Non Functional Requirements), Soft Goal Notation (Chung Framework), FDAF (Formal Design and Analysis Framework) and ATAM (Architecture Tradeoff Analysis Method). The second chapter introduces the research topic with its objectives, its limits, the research methodology and research steps. The third chapter describes the research execution by analyzing the current situation of quality with the resulted indicators from academic and industrial environments and formulating the future of the proposed research solution. An overview of the innovative aspects of proposed method like its specific features, metamodel, building process, and process structure are pinpointed. The fourth chapter describes primarily the most important parts of the research which are the development of a new quality engineering method called SOftware product QUAlity Requirements Engineering Method including fundamentals, key concepts and a process model. The fifth chapter presents an illustrative example applied to a building automation system called MSLite. Applicability of SOQUAREM process in this example is developed and analyzed. The last chapter presents a conclusion on this research work and its expected evolution in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.705
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.364
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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