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Record W1552571656

Software construction by composition of components

2010· article· en· W1552571656 on OpenAlexaff
Hamdan Msheik

Bibliographic record

VenueEspace École de technologie supérieure (École de technologie supérieure) · 2010
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceComponent-based software engineeringSoftware engineeringSoftware constructionSoftware developmentComponent (thermodynamics)Package development processSoftwareSoftware frameworkSoftware systemProgramming language
DOInot available

Abstract

fetched live from OpenAlex

In the continuously evolving era of software technological advances, software complexity and requirements change grow at increasing paces. Developing software using traditional approaches to meet the growing demand for functionalities and computation, in particular for large scale software, produces software applications which are characterized as being monolithic, difficult to reuse and costly to develop. To address those issues, componentbased software development has emerged among other approaches and has already produced a noteworthy positive impact. Nevertheless, component-based software development still suffers from a number of drawbacks and limitations.
\n
\nThe aim of this research project is to improve software construction by composition of components. Traditionally, reusable components may exhibit a bloating syndrome caused by bundled but unused set of members which vary according to application contexts and business domains. Furthermore, reusable components may suffer from chaotic amalgamation of code elements. Component members' bloating and a chaotic amalgamation of code elements limitations can be partially attributed to the lack of modular components. Typically, software constmctors rewrite from scratch newer software components (even though many code parts exist), retrofit or customize existing components to satisfy applications'
\nrequirements. In addition to these two limitations, software components suffer also from version mismatches due to the use of different versions of the same component.
\n
\nTo address the aforementioned limitations a new approach is proposed in this research work. Our approach is based on composition of atomic or enhanced modularity components. This new approach will contribute to the improvement of component-based software construction by alleviating some of the limitations facing it. It The focus of our research targets particularly the constmction phase of the software development lifecycle.
\n
\nThe main generic goal of this research project is:
\n• To improve software construction based on components composition by providing an approach which shifts and promotes software construction from a traditional construction approach based heavily on code writing and amalgamation to an approach relying increasingly on components composition.
\n
\nThe specific objectives of this research are:
\n• To propose and specify a software component model which provides remedies for some of the limitations facing software construction by components composition.
\n• To provide a reference implementation for this component model.
\n• To design a measurement method to measure components" unwanted members.
\n• To provide a prototype tool to measure components" unwanted members.
\n• To propose a component versioning mechanism.
\n• To provide a prototype tool to detect component versions mismatches.
\n
\nThe approach presented in this thesis is partly derived from the observation of product development processes implemented in traditional engineering disciplines. It can be argued that this approach represents a step forward in the evolution of software constmction based on components composition for it provides a simple and fluid components composition approach. The application and use of this composition approach reduces the need to retrofit and customize existing components as has been done traditionally. The software constructor relies more and more on selective composition of enhanced modularity components which suit particular application requirements. Moreover, this approach leads to additional secondary benefits which can be exploited in the use of fine-grained testing and in conducting various component measurements that ultimately benefit the software constmction process as a whole.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0060.002
Research integrity0.0020.004
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 head0.010
GPT teacher head0.247
Teacher spread0.238 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2010
Admission routes1
Has abstractyes

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