MétaCan
Menu
Back to cohort
Record W2105821857 · doi:10.1145/566171.566183

Investigating the use of analysis contracts to support fault isolation in object oriented code

2002· article· en· W2105821857 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2002
Typearticle
Languageen
FieldComputer Science
TopicSoftware Testing and Debugging Techniques
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIsolation (microbiology)Computer sciencePreconditionDesign by contractSoftware engineeringReuseObject-oriented programmingSoftwareInstrumentation (computer programming)Code (set theory)Object (grammar)Code reuseFault detection and isolationReliability engineeringRisk analysis (engineering)Programming languageSoftware systemEngineeringSoftware constructionSet (abstract data type)Artificial intelligence

Abstract

fetched live from OpenAlex

A number of activities involved in testing software are known to be difficult and time consuming. Among them is the isolation of faults once failures have been detected. In this paper, we investigate how the instrumentation of contracts could address this issue. Contracts are known to be a useful technique to specify the precondition and postcondition of operations and class invariants, thus making the definition of object-oriented analysis or design elements more precise. Our aim in this paper is to reuse and instrument contracts to ease testing. A thorough case study is run where we define contracts, instrument them using a commercial tool, and assess the benefits and limitations of doing so to support the isolation of faults. We then draw practical conclusions regarding the applicability of the approach and its limitations.

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.

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)0.000
metaresearch head score (Gemma)0.207
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.371
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.207
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.059
GPT teacher head0.265
Teacher spread0.206 · 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