Approaching Performance Testing from a Model-Based Testing Perspective

Abbors, Fredrik; Truşcan, Dragoş

doi:10.1109/valid.2010.22

Cited by 7 publications

(10 citation statements)

References 12 publications

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“…From the industry perspective, the performance testing process is usually very expensive, regarding infrastructure resources and generation of test scenarios and scripts [AT10]. Another significant gap to be highlighted is the lack of non-functional performance requirements in the system analysis, in addition to the absence of a standard documentation among the stakeholders about the problem domain, allowing a common understanding and interpretation of goals and aims of the system.…”

Section: Research Question: "How To Improve Model-based Performance Tmentioning

confidence: 99%

“…If not, the version is implanted in a performance environment to perform the load and stress testing. Some applications depend on the complexity of the production environment and the volume of infrastructure applied, given the high-level costs to maintain the replicated environment [AT10]. Lately, since the application attends to quality requirements established, e.g.…”

Section: Research Contextmentioning

confidence: 99%

See 1 more Smart Citation

Canopus: A Domain-Specific Language for Modeling Performance Testing

Bernardino

Zorzo

Rodrigues

2016

2016 IEEE International Conference on Software Testing, Verification and Validation (ICST)

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Section: Research Question: "How To Improve Model-based Performance Tmentioning

confidence: 99%

Section: Research Contextmentioning

confidence: 99%

Canopus: A Domain-Specific Language for Modeling Performance Testing

Bernardino

Zorzo

Rodrigues

2016

2016 IEEE International Conference on Software Testing, Verification and Validation (ICST)

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“…In this work, a test generation methodology is proposed to evaluate the impact of the interaction of wireless network quality and application configurations on the performance behaviour of mobile networked applications. We adopt a system‐level black‐box model‐based testing (MBT) approach . MBT is “a variant of testing that relies on explicit behavior models that encode the intended behaviors of software under test (SUT) and/or the behavior of its environment.…”

Section: Introductionmentioning

confidence: 99%

“…Abstracting software behaviour and/or the environment affecting this behaviour has many benefits for the whole development process. It allows focusing on certain aspects of the system and overlooking the less important ones (divide and conquer) . Another advantage of MBT is the automation of test case generation.…”

Section: Introductionmentioning

confidence: 99%

An end‐user‐centric test generation methodology for performance evaluation of mobile networked applications

Al‐tekreeti

Abdrabou

Naik

2019

Software Testing Verif & Rel

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We propose a model-based test generation methodology to evaluate the impact of the interaction of the wireless network and application configurations on the performance of mobile networked applications. We consider waiting time delay to model wireless network quality. We classify mobile applications into two groups. Group I represents applications where end-user experience is mainly affected by waiting time delay during service consumption, while group II represents applications where end-user experience is affected by waiting time delay before service consumption. Test generation is formulated as an inversion problem. However, for group I applications, solving the inversion problem is expensive. Therefore, we utilize metamorphic testing to mitigate the cost of test oracles. We formulate metamorphic test generation as maximization of the distance between seed and follow-up test cases. Two test coverage criteria are proposed: user experience and user-experience-and-input interaction. Network models are developed for a mobile device that has network access through a WiFi hot spot and uses either transmission control protocol or user datagram protocol. Two mobile applications are used to demonstrate the methodology: multimedia streaming and web browsing. Application of the methodology when user actions are taken into consideration is also addressed. The effectiveness of the methodology is evaluated using two metrics: the incurred time cost and redundancy in the generated test suite. The obtained results show the advantage of casting test generation as an inversion problem, compared with random testing. For apps with intensive performance models, combining metamorphic testing with the methodology has tremendously reduced the cost of test oracles. 15 of 38 state y. Therefore, the SUT desired behaviour introduces the following two constraints (Procedure 3.S1), where B, M , and L are defined as an integer number of multimedia frames:M Ä B and L Ä M 1:(4) 4.1.2. The wireless network model. The end user is streaming via a WiFi hot spot and using the UDP. We assume all the fluctuations in the wireless link and the queuing effects of the different routers along the path from the server to the client device manifest as a time delay. That is, packet loss is negligible. A reusable network model for the UDP scenario was developed in our previous work [15]. We have developed two analytical expressions for the mean and variance of packet interarrival time delay. The probability distribution was matched with the hyper-Erlang distribution. The network impact is captured by three operating parameters (NOPs): the data rate (D), the mean rate of frame arrivals into the access point ( ) per user, and the number of end users (N ) connected to the AP. The data rate according to the IEEE 802.11 a/g standard can be in one of the following values: 6, 9, 12, 18, 24, 32, 48, or 54 Mbps. It mainly relates to the quality of the wireless connection between the AP and the end user. Regarding the number of users N , the network model is validated...

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“…Nowadays, the increasing complexity of software systems creates new challenges for safety, where quality and reliability are highly required, but are difficult to be ensured. Testing is a necessary way to ensure the correctness of software systems in practice and to monitor if systems operate properly or not [1,9]. Written test programs should include a description of the functionality that needs to be tested.…”

Section: Introductionmentioning

confidence: 99%

Test Scenario Generation using Model Checking

Yin¹

2018

IJPE

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Testing, including designation, execution and bug analysis has been broadly adopted in various industries. Test cases must be designed to confirm the entire behavior of the object system. In practice, a test case normally includes a series of operations that cold conduct the system status eventually to fulfill the precondition of the targeted test case. However, the applications to trigger the function calls of the software system would often be manually composed in traditional test activities, which is difficult especially for complex concurrent systems. Insufficient testing might result in hidden system defects, which increases the likelihood of economic loss or human injury. Model checking is a formal technique that can check the properties of a system automatically with strictness, completeness, and traceability. In this paper, a novel formal approach is proposed to systematically generate test scenarios automatically with traceability by the model checking technique. Meanwhile, the scenarios are reliable and precise, and debugging also becomes easier. Moreover, despite the reduction in demand of an experienced test engineer to design the target test cases, the coverage could be improved as the tedious and complicated processes of test scenario generation are accomplished by the model checker. This method has been applied in two practical case studies, and the results show the effectiveness of the proposed approach in terms of high coverage, automation, traceability and reusability.

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Approaching Performance Testing from a Model-Based Testing Perspective

Cited by 7 publications

References 12 publications

Canopus: A Domain-Specific Language for Modeling Performance Testing

Canopus: A Domain-Specific Language for Modeling Performance Testing

An end‐user‐centric test generation methodology for performance evaluation of mobile networked applications

Test Scenario Generation using Model Checking

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