Automated Coverage Directed Test Generation Using a Cell-Based Genetic Algorithm

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Automated Coverage Directed Test Generation Using a Cell-Based Genetic Algorithm
  Automated Coverage Directed Test GenerationUsing a Cell-Based Genetic Algorithm Amer Samarah A ThesisinThe Departmentof Electrical and Computer EngineeringPresented in Partial Fulfillment of the Requirementsfor the Degree of Master of Applied Science atConcordia UniversityMontr´eal, Qu´ebec, CanadaSeptember 2006c  Amer Samarah, 2006  CONCORDIA UNIVERSITYSchool of Graduate StudiesThis is to certify that the thesis preparedBy:  Amer Samarah Entitled:  Automated Coverage Directed Test Generation Using a Cell-Based Genetic Algorithm and submitted in partial fulfilment of the requirements for the degree of  Master of Applied Science complies with the regulations of this University and meets the accepted standardswith respect to srcinality and quality.Signed by the final examining committee:Dr. Rabin RautDr. Peter GrogonoDr. Amir G. AghdamDr. Sofi`ene TaharApproved byChair of the ECE Department2006Dean of Engineering  ABSTRACTAutomated Coverage Directed Test Generation Using aCell-Based Genetic Algorithm Amer SamarahFunctional verification is a major challenge of the hardware design development andverification cycle. Several approaches have been developed lately in order to tacklethis challenge, including coverage based verification. Within the context of cover-age based verification, many metrics have been proposed to capture and verify thedesign functionality. Some of the used metrics are code coverage, FSM coverage,and functional coverage point that capture design specifications and functionalities.Defining the appropriate functional coverage points (monitors) is a quite tricky andnon-trivial problem. However, the real bottleneck concerns generating suitable testpatterns that can adequately activate those coverage points and achieve high cover-age rate.In this thesis, we propose an approach to automatically generate proper directivesfor random test generators in order to activate multiple functional coverage pointsand to enhance the overall coverage rate. In contrast to classical blind random simu-lation, we define an enhanced genetic algorithm procedure performing the optimiza-tion of coverage directed test generation (CDG) over domains of the system inputs.The proposed algorithm, which we call Cell-based Genetic Algorithm (CGA), in-corporates unique representation and genetic operators especially designed for CDGproblems. Rather than considering the input domain as a single unit, we split itinto a sequence of cells (subsets of the whole input’s domain) which provide rich andflexible representations of the random generator’s directives. The algorithm auto-matically optimizes the widths, heights and distribution of these cells over the wholeinputs domains with the aim of enhancing the effectiveness of using test generation.We illustrate the efficiency of our approach on a set of designs modeled in SystemC.iii  ACKNOWLEDGEMENTS First and foremost, my wholehearted thanks and admire are due to the HolyOne, Allah, Who has always been with me through out my entire struggle in lifewiping out all my fears, for oblation His countless blessings. My sincere apprecia-tion to the Hani Qaddumi Scholarship Foundation (HQSF) that has granted me apostgraduate scholarship at Concordia University.I would like to express my sincere gratitude to my advisor, Dr. Sofi`ene Taharfor his guidance, support, patience, and his constant encouragement. His expertiseand competent advice have not only shaped the character of my thesis but also myway of thinking and reasoning. Also, I would like to specially thank Dr. Ali Habibi,Concordia University, for his invaluable guidance. Without his insight and steering,needless to say, this thesis would have never got completed.I would like to thank Dr. Nawwaf Kharma, Concordia University, for hisunique approach of teaching and for valuable discussions on my thesis. His con-tribution played a major role in finalizing this thesis. Many thanks to my thesiscommittee members, Dr. Peter Grogono and Dr. Amir G. Aghdam, for reviewingmy thesis and for their valuable feedback.To all my fellow researchers in the Hardware Verification Group (HVG) atConcordia University, thank you for encouragement, thoughtful discussions, andproductive feedback. Special thanks for Mr. Falah Awwad for introducing me toDr. Sofi`ene Tahar. I would also like to express my appreciation for my friends, Sa-her Alshakhshir, Ize Aldeen Alzyyed, Mohammed Abu Zaid, Mohammed Othman,Alaa Abu Hashem, Hafizur Rahman, Asif Ahmad, Abu Nasser Abdullah, and HajaMoindeen for always supporting and being there for me at the time of my need.Finally, I wish to express my gratitude to my family members for offeringwords of encouragements to spur my spirit at moments of depression.iv  This thesis is lovingly dedicated toMy Mother, ADLA SHALHOUB for all I started in her armsAndMy Father, TAYSIR SAMARAH for his fervent love for my educationv
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