scholarly journals A Python based Design Verification Methodology

2021 ◽  
Vol 23 (06) ◽  
pp. 901-911
Author(s):  
Ankitha Ankitha ◽  
◽  
Dr. H. V. Ravish Aradhya ◽  

While the UVM-constrained random and coverage-driven verification methodology revolutionized IP and unit-level testing, it falls short of SoC-level verification needs. A solution must extend from UVM and enable vertical (IP to SoC) and horizontal (verification engine portability) reuse to completely handle SoC-level verification. To expedite test-case generation and use rapid verification engines, it must also provide a method to collect, distribute, and automatically amplify use cases. Opting a Python-based Design Verification approach opens the door to various such merits. Cocotb is a very useful, growing methodology which can be used for the same. This paper elaborates on the application of cocotb, an open-source framework hosted on Github which is based on CO-routine and CO-simulation of Testbench environment for verifying VHDL/Verilog RTL using Python. It employs equivalent design-reuse and functional verification concepts like UVM, however is implemented in Python, which is much simpler to understand and that leads to faster development and reduces the turnaround time.

Author(s):  
Rajvir Singh ◽  
Anita Singhrova ◽  
Rajesh Bhatia

Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.


2012 ◽  
Vol 58 (2) ◽  
pp. 587-595 ◽  
Author(s):  
Tarkan Tekcan ◽  
Vladimir Zlokolica ◽  
Vukota Pekovic ◽  
Nikola Teslic ◽  
Mustafa Gunduzalp

2018 ◽  
Vol 2018 ◽  
pp. 1-42 ◽  
Author(s):  
David Insa ◽  
Sergio Pérez ◽  
Josep Silva ◽  
Salvador Tamarit

In any alive and nontrivial program, the source code naturally evolves along the lifecycle for many reasons such as the implementation of new functionality, the optimization of a bottleneck, or the refactoring of an obscure function. Frequently, these code changes affect various different functions and modules, so it can be difficult to know whether the correct behaviour of the previous version has been preserved in the new version. In this paper, we face this problem in the context of the Erlang language, where most developers rely on a previously defined test suite to check the behaviour preservation. We propose an alternative approach to automatically obtain a test suite that specifically focusses on comparing the old and new versions of the code. Our test case generation is directed by a sophisticated combination of several already existing tools such as TypEr, CutEr, and PropEr; and it introduces novel ideas such as allowing the programmer to choose one or more expressions of interest that must preserve the behaviour, or the recording of the sequences of values to which those expressions are evaluated. All the presented work has been implemented in an open-source tool that is publicly available on GitHub.


2018 ◽  
Vol 9 (3) ◽  
pp. 15-35 ◽  
Author(s):  
Rajvir Singh ◽  
Anita Singhrova ◽  
Rajesh Bhatia

Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.


2008 ◽  
Vol 32 (5-6) ◽  
pp. 288-295 ◽  
Author(s):  
Mohammad Reza Kakoee ◽  
M.H. Neishaburi ◽  
Siamak Mohammadi

Sign in / Sign up

Export Citation Format

Share Document