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Record W4280607813 · doi:10.18280/isi.270218

Use Case Realization in Software Reverse Engineering

2022· article· en· W4280607813 on OpenAlexvenueno aff
Yanti Andriyani, Ibnu Daqiqil Id, Evfi Mahdiyah, Al Aminuddin

Bibliographic record

VenueIngénierie des systèmes d information · 2022
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
FundersUniversitas Riau
KeywordsReverse engineeringComputer scienceSoftware engineeringUse Case DiagramSoftware systemProcess (computing)Table (database)Systems engineeringSoftware developmentDomain (mathematical analysis)SoftwareUnified Modeling LanguageClass diagramData miningEngineeringProgramming language

Abstract

fetched live from OpenAlex

The Use Case Diagram (UCD) is a visual form of system design that helps software developers comprehend the system behavior. Maintaining and updating the system can be a difficult task when it has no visualization of a system behavior or software requirement specification document. Reverse engineering is an approach used to extract software requirement specifications from the existing systems. Research in reverse engineering has shown various techniques in which the processes are not fully understood. This study analyzes the University Community Services Information System (UCSIS) as the existing system in three processes: identifying the system domain process, elaborating system features by implementing the event table, and constructing the use case realization. The results showed that a UCD could be generated through the reverse engineering process on the existing system. Furthermore, a new feature for system improvement can also be detected using this method. It is expected that the reverse engineering approach in this study can be used as guidance for the software development team in extracting the use case diagram from the existing systems.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.007
Open science0.0000.000
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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations6
Published2022
Admission routes1
Has abstractyes

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