Construction Technique of Large Operational Profiles for Statistical Software Testing

Takagi, Toshihisa; Furukawa, Zengo

doi:10.1007/978-3-319-00804-2_14

Cited by 2 publications

(4 citation statements)

References 9 publications

(23 reference statements)

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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%

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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%

“…The method of [9] is quite simple and cannot fit complex software. The method of [10,11] 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: Usage Models 21 Structuring the Usage Modelmentioning

confidence: 99%

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

2017

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“…Tomohiko Takagi and Zengo Furukawa [13] presented a novel construction technique of a huge operational profiles concerning to effectively apply statistical testing to the large software project is implemented on a tight schedule by constructing elemental operational profiles, small operational profiles that represent usage characteristics of components of SUT. The key idea is that an operational profile of the whole of SUT is too extensive to be built physically, but operational profile of the components of SUT are small so that it is easy to be constructed.…”

Section: User Profilementioning

confidence: 99%

“…Applying statistical user profile approach is exceptionally valuable in improving the software quality and reliability in reduce testing efforts and also reduce the software development cost [8,12]. Moreover, implementing the automation to collect the user profile would help reduce in human errors as the user profiles are the most important part of the approach and therefore require special attention from testers [9,13]. …”

Section: Evaluation Of the Test Case Effectivenessmentioning

confidence: 99%

Input Modeling Prioritization Using Statistically User Profile for Pairwise Test Case Generation with Constraints Handling

Nakornburi¹,

Suwannasart²

2017

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Abstract. Pairwise testing is a widely used technique for software testing with the reduced size of the test suite and able to detect interactions that trigger the system's faults. In addition, pairwise testing test suites must be able to take constraints between input parameters and parameter values into account. In current practice, identifying and selecting input parameters and parameter values usually depends on tester skills that might not be sufficient. Input parameters and parameter values modeling and tools for easily guiding and prioritizing the selection of optimal input parameters and parameter values for the SUT is also required. In this work, we present an approach for prioritizing input parameters and parameter values modeling using statistical user profile. Our approach is implemented in a tool called UPPTCT which provides the ability to handle constraints on input parameters and parameter values for pairwise testing in order to generate test cases. We conduct experiments to evaluate test case effectiveness and compare our tool with other renowned pairwise test generation and constraints handling tools. The experimental results show that the effectiveness of our approach is significantly more efficient and effective than random testing as a large portion of reported defects with regard to statically user profile were caught by our approach. Furthermore, our tool performs better in some cases and performs comparable results for generating test cases upon input parameters and parameter values for both with constraints handling and without constraints handling.

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Construction Technique of Large Operational Profiles for Statistical Software Testing

Cited by 2 publications

References 9 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

Input Modeling Prioritization Using Statistically User Profile for Pairwise Test Case Generation with Constraints Handling

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