Energy-Efficient Multi-fragment Markov Model Guided Online Model-Based Testing for MPSoC

Vain, Jüri; Tsiopoulos, Leonidas; Kharchenko, Vyacheslav; Kaur, Apneet; Jenihhin, Maksim; Raik, Jaan; Nõmm, Sven

doi:10.1007/978-3-030-00253-4_12

Cited by 1 publication

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“…3. The lack of automation in the current MBT approaches [23,47,71, 72] 4. Others reasons, e.g., using petri nets to model time behavior aspects [13].…”

Section: Discussionmentioning

confidence: 99%

“…Time-behavior was the most com-mon performance aspect (Figure 7). Out of the 149 extracted performance requirements, time behavior was specified in (71) requirements (e.g., The system shall be able to search for a specified product in less than 1 second. 4 ), followed by capacity (38) (e.g., The system must handle at least 100 concurrent users and their Fig.…”

Section: Discussionmentioning

confidence: 99%

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An approach for performance requirements verification and test environments generation

2022

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Model-based testing (MBT) is a method that supports the design and execution of test cases by models that specify the intended behaviors of a system under test. While systematic literature reviews on MBT in general exist, the state of the art on modeling and testing performance requirements has seen much less attention. Therefore, we conducted a systematic mapping study on model-based performance testing. Then, we studied natural language software requirements specifications in order to understand which and how performance requirements are typically specified. Since none of the identified MBT techniques supported a major benefit of modeling, namely identifying faults in requirements specifications, we developed the Performance Requirements verificatiOn and Test EnvironmentS generaTion approach (PRO-TEST). Finally, we evaluated PRO-TEST on 149 requirements specifications. We found and analyzed 57 primary studies from the systematic mapping study and extracted 50 performance requirements models. However, those models don’t achieve the goals of MBT, which are validating requirements, ensuring their testability, and generating the minimum required test cases. We analyzed 77 Software Requirements Specification (SRS) documents, extracted 149 performance requirements from those SRS, and illustrate that with PRO-TEST we can model performance requirements, find issues in those requirements and detect missing ones. We detected three not-quantifiable requirements, 43 not-quantified requirements, and 180 underspecified parameters in the 149 modeled performance requirements. Furthermore, we generated 96 test environments from those models. By modeling performance requirements with PRO-TEST, we can identify issues in the requirements related to their ambiguity, measurability, and completeness. Additionally, it allows to generate parameters for test environments.

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“…3. The lack of automation in the current MBT approaches [23,47,71, 72] 4. Others reasons, e.g., using petri nets to model time behavior aspects [13].…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%