A constraint-based approach to the representation of software usage models

Poore, Jesse H.; Walton, Gwendolyn H.; Whittaker, James A.

doi:10.1016/s0950-5849(00)00101-4

Cited by 28 publications

(18 citation statements)

References 5 publications

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“…Researchers have proposed many kinds of methods of structuring usage model, which can be summarized to the following methods [9,10,11]: Musa's Method, based on expert experiences, historical data and complex software model. Musa's method is only a guiding thought of structuring usage model and lacks a specific implementation.…”

Section: Usage Models 21 Structuring the Usage Modelmentioning

confidence: 99%

“…It is difficult to obtain the transition probability among states of an UM directly from historical data and experts; however, it is easy to obtain the constraint description (linear or non-linear) of each operation from an expert [11]. Then we calculate the operation transition probabilities according to constraints.…”

Section: Transition Probabilitymentioning

confidence: 99%

“…A huge number of test cases are required to satisfy the probability distribution of the actual usage situation; otherwise, the reliability test will lose its original meaning. Researchers have proposed many kinds of methods of structuring usage model, which can be summarized to the following methods: Musa's Method [9], based on expert experiences [11], historical data and complex software model [16]. Musa's method is only a guiding thought of structuring usage model lacking a specific implementation.…”

Section: Relation Work 51 the Construction Of Software Usage Modelmentioning

confidence: 99%

“…The method of [9] is quite simple and cannot be applied to complex software. The method of [11] cannot reflex calling relation and constraint relation among modules. In addition, with the growing of the quantity of modules, the complexity of this method is increasing sharply.…”

Section: Relation Work 51 the Construction Of Software Usage Modelmentioning

confidence: 99%

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Large scale software test data generation based on collective constraint and weighted combination method

2017

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Original scientific paper Software reliability test is to test software with the purpose of verifying whether the software achieves reliability requirements and evaluating software reliability level. Statistical-based software reliability testing generally includes three parts: building usage model, test data generation and testing. The construction of software usage model should reflect user's real use as far as possible. A huge number of test cases are required to satisfy the probability distribution of the actual usage situation; otherwise, the reliability test will lose its original meaning. In this paper, we first propose a new method of structuring software usage model based on modules and constraint-based heuristic method. Then we propose a method for the testing data generation in consideration of the combination and weight of the input data, which reduces a large number of possible combinations of input variables to a few representative ones and improves the practicability of the testing method. To verify the effectiveness of the method proposed in this paper, four groups of experiments are organized. The goodness of fit index (GFI) shows that the proposed method is closer to the actual software use; we also found that the method proposed in this paper has a better coverage by using Java Pathfinder to analyse the four sets of internal code coverage.Keywords: constraint; data generation; GFI; software reliability testing; usage model; weighted combination Generiranje ispitnih podataka za softver zasnovano na kolektivnom ograničenju i ponderiranoj metodi kombinacijeIzvorni znanstveni članak Ispitivanje pouzdanosti softvera znači ispitivanje softvera kako bi se provjerilo da li udovoljava zahtjevima pouzdanosti i kako bi se procijenio njegov stupanj pouzdanosti. Statistički temeljeno ispitivanje pouzdanosti softvera općenito uključuje tri dijela: izgradnju modela, generiranje ispitnih podataka i ispitivanje. Stvaranje modela upotrebe softvera treba što je više moguće odražavati korisnikovu stvarnu primjenu. Potreban je ogroman broj ispitivanih slučajeva da bi se zadovoljila distribucija vjerojatnoće u slučaju stvarne upotrebe; inače će ispitivanje pouzdanosti izgubiti originalno značenje. U ovom radu najprije predlažemo novu metodu strukturiranja modela primjene softvera zasnovanu na modulima i heurističkoj metodi koja se temelji na ograničenjima. Zatim predlažemo metodu za generiranje podataka za ispitivanje uzimajući u obzir kombinaciju i težinu ulaznih podataka što smanjuje veliki broj mogućih kombinacija ulaznih varijabli na samo nekoliko reprezentativnih i povećava praktičnost primjene ispitne metode. U svrhu provjere učinkovitosti metode predložene u ovom radu, organizirane su četiri grupe eksperimenata. Ispravnost odgovarajućeg indeksa (GFI-goodness of fit index) pokazuje da je predložena metoda bliža upotrebi aktualnog softvera; također smo ustanovili da ima bolju pokrivenost kod uporabe Java Pathfinder-a za analizu četiri niza pokrivenosti internog koda.

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Section: Usage Models 21 Structuring the Usage Modelmentioning

confidence: 99%

Section: Transition Probabilitymentioning

confidence: 99%

Section: Relation Work 51 the Construction Of Software Usage Modelmentioning

confidence: 99%

Section: Relation Work 51 the Construction Of Software Usage Modelmentioning

confidence: 99%

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Large scale software test data generation based on collective constraint and weighted combination method

2017

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“…Poore et al [3] define a two-phase construction process for an operational profile using Markov chain models. The structural phase establishes the states and transitions of the model, and the statistical phase assigns the transition probabilities.…”

Section: Introductionmentioning

confidence: 99%

Systematic Operational Profile Development for Software Components

Shukla¹,

Carrington²,

Strooper³

11th Asia-Pacific Software Engineering Conference

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Model‐Based Software Testing

El-Far

Whittaker

2002

Encyclopedia of Software Engineering

111

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Software testing requires the use of a model to guide such efforts as test selection and test verification. Often, such models are implicit, existing only in the head of a human tester, applying test inputs in an ad hoc fashion. The mental model testers build encapsulates application behavior, allowing testers to understand the application's capabilities and more effectively test its range of possible behaviors. When these mental models are written down, they become sharable, reusable testing artifacts. In this case, testers are performing what has become to be known as model-based testing. Model-based testing has recently gained attention with the popularization of models (including UML) in software design and development. There are a number of models of software in use today, a few of which make good models for testing. This paper introduces model-based testing and discusses its tasks in general terms with finite state models (arguably the most popular software models) as examples. In addition, advantages, difficulties, and shortcoming of various model-based approaches are concisely presented. Finally, we close with a discussion of where model-based testing fits in the present and future of software engineering.

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A constraint-based approach to the representation of software usage models

Cited by 28 publications

References 5 publications

Large scale software test data generation based on collective constraint and weighted combination method

Large scale software test data generation based on collective constraint and weighted combination method

Systematic Operational Profile Development for Software Components

Model‐Based Software Testing

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