The AGEDIS tools for model based testing

Hartman, Alan; Nagin, Kenneth

doi:10.1145/1007512.1007529

Cited by 68 publications

(30 citation statements)

References 3 publications

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“…Several prior designs focus on analysis from one or a few specific perspectives, such as locating errors in the realized behavior of the SUT [7,9,10,12] or ensuring model validity and coverage [5,6,7]. In our RCA design, the interface provided to the Analysis Code subcomponent gives access to all available test data, enabling correlation between any or all of the data types in the analysis algorithm code.…”

Section: Rca Analysis Implementation and Case Studymentioning

confidence: 99%

“…Most studied designs are presented in the context of a specific tool chain assembled from several software components [5,6,7] or a single system [12]. Endeavors for providing an adaptable framework customizable for different data types have been mentioned in [5] but details on implementing the customization are not given.…”

Section: Rca Analysis Implementation and Case Studymentioning

confidence: 99%

“…Realization of MBT is usually based on deploying a tool chain consisting of software for e.g. model development, test case generation, test execution and report generation [6,7]. MBT tool chains can be built from off-the-shelf components [6,8], and a number of different MBT tools exist from various vendors ranging from academic to commercial software [1].…”

Section: Introductionmentioning

confidence: 99%

“…In many cases, test cases return as either passed or failed, and further analysis is needed to find the causes of actual behavior differing from expected behavior [7,9]. Software failures may arise because of multiple correlations within occurring events.…”

Section: Introductionmentioning

confidence: 99%

“…Model-based analysis has also been applied to other purposes related to MBT, e.g., model validation [5,6,7] and test case selection [12]. Different approaches for implementing analysis include rule-based systems [9,12], estimation using Bayesian analysis [13] and sequence-based pattern recognition [10].…”

Section: Introductionmentioning

confidence: 99%

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Adaptable Design for Root Cause Analysis of a Model-Based Software Testing Process

Nieminen

Räty

2015

2015 12th International Conference on Information Technology - New Generations

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Model-Based Testing (MBT) is a method for automating software testing and improving fault detection by using an abstracted model of the system under test to systematically generate and execute test cases. One of the main challenges in MBT is the efficient locating of fundamental causes of errors, which can be achieved using root cause analysis. As MBT is being applied to many diverse domains using various tools and tool chains, tool adaptability is an important factor to consider. We define the design for an automated Root Cause Analyzer (RCA) tool adaptable for different MBT testing scenarios and environments. In our RCA design, analysis is configured using rules for evaluating output data of other MBT components. We present an example of RCA application for a case study in mobile telecommunications testing to demonstrate the integration and adapting of our design into an existing tool chain. Within the case study, the RCA tool is successful in locating causes of errors, and is able to interface with MBT components and exploit their data in analysis. The research is based on the constructive method of the related publications and technologies and the results are derived by the implemented RCA tool.

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Section: Rca Analysis Implementation and Case Studymentioning

confidence: 99%

Section: Rca Analysis Implementation and Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Adaptable Design for Root Cause Analysis of a Model-Based Software Testing Process

Nieminen

Räty

2015

2015 12th International Conference on Information Technology - New Generations

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Modeling and Verification of Real‐Time Systems using the IF Toolset

Bozga¹,

Graf²,

Mounier³

et al. 2008

Modeling and Verification of Real‐Time Systems

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A practical model‐based statistical approach for generating functional test cases: application in the automotive industry

Awédikian

Yannou

2012

Software Testing Verif & Rel

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SUMMARYWith the growing complexity of industrial software applications, industrials are looking for efficient and practical methods to validate the software. This paper develops a model‐based statistical testing approach that automatically generates online and offline test cases for embedded software. It discusses an integrated framework that combines solutions for three major software testing research questions: (i) how to select test inputs; (ii) how to predict the expected results of a test; and (iii) when to stop testing software. The automatic selection of test inputs is based on a stochastic test model that accounts for the main particularity of embedded software: time sensitivity. Software test practitioners may design one or more test models when they generate random, user‐oriented, or fault‐oriented test inputs. A formal framework integrating existing and appropriate specification techniques was developed for the design of automated test oracles (executable software specifications) and the formal measurement of functional coverage. The decision to stop testing software is based on both test coverage objectives and cost constraints. This approach was tested on two representative case studies from the automotive industry. The experiment was performed at unit testing level in a simulated environment on a host personal computer (automatic test execution). The two software functionalities tested had previously been unit tested and validated using the test design approach conventionally used in the industry. Applying the proposed model‐based statistical testing approach to these two case studies, we obtained significant improvements in performing functional unit testing in a real and complex industrial context: more bugs were detected earlier and in a shorter time. Copyright © 2012 John Wiley & Sons, Ltd.

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The AGEDIS tools for model based testing

Cited by 68 publications

References 3 publications

Adaptable Design for Root Cause Analysis of a Model-Based Software Testing Process

Adaptable Design for Root Cause Analysis of a Model-Based Software Testing Process

Modeling and Verification of Real‐Time Systems using the IF Toolset

A practical model‐based statistical approach for generating functional test cases: application in the automotive industry

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