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    An ensemble-based predictive mutation testing approach that considers impact of unreached mutants

    , Article Software Testing Verification and Reliability ; Volume 31, Issue 7 , 2021 ; 09600833 (ISSN) Aghamohammadi, A ; Mirian Hosseinabadi, S. H ; Sharif University of Technology
    John Wiley and Sons Ltd  2021
    Abstract
    Predictive mutation testing (PMT) is a technique to predict whether a mutant is killed, using machine learning approaches. Researchers have proposed various methods for PMT over the years. However, the impact of unreached mutants on PMT is not fully addressed. A mutant is unreached if the statement on which the mutant is generated is not executed by any test cases. We aim at showing that unreached mutants can inflate PMT results. Moreover, we propose an alternative approach to PMT, suggesting a different interpretation for PMT. To this end, we replicated the previous PMT research. We empirically evaluated the suggested approach on 654 Java projects provided by prior literature. Our results... 

    An ensemble-based predictive mutation testing approach that considers impact of unreached mutants

    , Article Software Testing Verification and Reliability ; Volume 31, Issue 7 , 2021 ; 09600833 (ISSN) Aghamohammadi, A ; Mirian Hosseinabadi, S. H ; Sharif University of Technology
    John Wiley and Sons Ltd  2021
    Abstract
    Predictive mutation testing (PMT) is a technique to predict whether a mutant is killed, using machine learning approaches. Researchers have proposed various methods for PMT over the years. However, the impact of unreached mutants on PMT is not fully addressed. A mutant is unreached if the statement on which the mutant is generated is not executed by any test cases. We aim at showing that unreached mutants can inflate PMT results. Moreover, we propose an alternative approach to PMT, suggesting a different interpretation for PMT. To this end, we replicated the previous PMT research. We empirically evaluated the suggested approach on 654 Java projects provided by prior literature. Our results... 

    The Bug Prediction Model Using Mutation Metrics

    , M.Sc. Thesis Sharif University of Technology Mohebbi, Ali (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    Abstract
    Software developers notice existence of faults by report of a fault in issue tracking systems or a failure in software tests. Then they try to locate the bug and understand the problem. Early detection of fault results in saving time and money and facilitates debugging process. Prediction models can be built and used easily by modern statistical tools. Software metrics are the most important part of prediction models. Therefore higher performance in models can be achieved using new and effective metrics. In this study, process metrics and metrics that built base on mutation analysis used and resulting models evaluated. In addition to using process metrics with mutation metrics, two group of... 

    A Probabilistic Approach to Assessing and Interpreting Test Suite Effectiveness

    , Ph.D. Dissertation Sharif University of Technology Agha Mohammadi, Alireza (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    Abstract
    The test suite effectiveness concerns the ability of test suites to reveal faults. Mutation testing is a de facto standard to assess the test suite effectiveness. However, mutation testing is a time-consuming process. Over the years, researchers have proposed two kinds of approaches. The first category is related to code coverage criteria and assess the total test suite effectiveness. The second is known as Predictive Mutation Testing (PMT). The suggested approach is probabilistic, being in different levels of abstraction (macro and micro). First, in the macro level, there is a code coverage criterion that not only does outperform existing code coverage but also does not have a statistically... 

    Program state coverage: A test coverage metric based on executed program states

    , Article 26th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2019, 24 February 2019 through 27 February 2019 ; 2019 , Pages 584-588 ; 9781728105918 (ISBN) Etemadi Someoliayi, K ; Jalali, S ; Mahdieh, M ; Mirian Hosseinabadi, S. H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    In software testing, different metrics are proposed to predict and compare test suites effectiveness. In this regard, Mutation Score (MS) is one of most accurate metrics. However, calculating MS needs executing test suites many times and it is not commonly used in industry. On the other hand, Line Coverage (LC) is a widely used metric which is calculated by executing test suites only once, although it is not as accurate as MS in terms of predicting and comparing test suites effectiveness. In this paper, we propose a novel test coverage metric, called Program State Coverage (PSC), which improves the accuracy of LC. PSC works almost the same as LC and it can be calculated by executing test... 

    CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes

    , Article Scientific Reports ; Volume 10, Issue 1 , 2020 Bayati, M ; Rabiee, H. R ; Mehrbod, M ; Vafaee, F ; Ebrahimi, D ; Forrest, A. R. R ; Alinejad Rokny, H ; Sharif University of Technology
    Nature Research  2020
    Abstract
    Analysis of cancer mutational signatures have been instrumental in identification of responsible endogenous and exogenous molecular processes in cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly interface for analysis of cancer mutational signatures is necessary. In this manuscript we introduce CANCERSIGN, which enables users to identify 3-mer and 5-mer mutational signatures within whole genome, whole exome or pooled samples. Additionally, this tool enables users to perform clustering on tumor samples based on the proportion of mutational signatures in... 

    A quantum mechanical approach towards the calculation of transition probabilities between DNA codons

    , Article BioSystems ; Volume 184 , 2019 ; 03032647 (ISSN) Ghasemi, F ; Shafiee, A ; Sharif University of Technology
    Elsevier Ireland Ltd  2019
    Abstract
    The role of quantum tunneling in altering the structure of nucleotides to each other and causing a mutational event in DNA has been a topic of debate for years. Here, we introduce a new quantum mechanical approach for analyzing a typical point-mutation in DNA strands. Assuming each codon as a base state, a superposition of codon states could provide a physical description for a set of codons encoding the same amino acid and there are transition amplitudes between them. We choose the amino acids Phe and Ile as our understudy bio-systems which are encoded by two and three codons, respectively. We treat them as large quantum systems and use double- and triple-well potential models to study the... 

    Generating Mutants from Android Event - Driven Programs

    , M.Sc. Thesis Sharif University of Technology Etemadi Some Oliayi, Khashayar (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    Abstract
    In the recent years, developing and using android applications has experienced a huge expansion. Due to the novelity of these applications and their environment for developers, we can find so many problems in their perfomance. At the same time as spread of developing these applications, new automatic and non-automatic methods are introduced for testing them. Usually mutation testing methods are used to evaluate new suggested software testing methods, so some rigorous and effective methods of mutation testing for android applications are needed too. Today, some primary methods are suggested for generating mutants of android applications which are not mature yet and have many defects. The goal... 

    Generating Mutants to Improve Test Suites: A Search-Based Approach

    , M.Sc. Thesis Sharif University of Technology Barati, Babak (Author) ; Mirian-Hosseinabadi, Hassan (Supervisor)
    Abstract
    Mutation testing is known to be one of the best strategies to improve the quality of test suites, consequently the quality of the software. However, some challenges make mutaton testing unpractical. One of the main challenges confronting mutation testing is that it demands exhustive computation and is time consuming because of the large number of mutants that need to be compiled and executed on the test cases of the test suite. Many researches have been conducted to reduce the number of mutants without losing the main characteristics of the all possible mutants. Most of these researches select the mutants without considering the characteristics of the test suite, therefore the reduced set of... 

    Generating Mutants for User Interface Testing in Web-based Applications

    , M.Sc. Thesis Sharif University of Technology Naderi, Mohammad Javad (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    Abstract
    In recent years, the user interface of web-based applications has become more and more complicated. Various technologies, architectures, and tools are being used to create a modern user interface. Users interact directly with the user interface, so its functionality has a significant impact on their satisfaction and it is required to design special test suites for the user interface. Furthermore, we need a method to measure the quality and effectiveness of test suites. An effective test suite is a test suite which is able to detect real faults. But this definition is ambiguous, and hence, not practical. A method called Mutation Testing solves this problem and instead of real faults, uses... 

    Coalescence, Recombinations and Mutations

    , Ph.D. Dissertation Sharif University of Technology Salamat, Majid (Author) ; Pardoux, Etienne (Supervisor) ; Zohori Zageneh, Bijan (Supervisor) ; Zamani, Shiva (Co-Advisor)
    Abstract
    This thesis is concentrated on some subjects on population genetics. In the rst part we give formulae including the expectation and variance of the height and the length of the ancestral recombination graph (ARG) and the expectation and variance of the number of recombination events and we show that the expectation of the length of the ARG is a linear combination of the expectation of the length of Kingman's coalescent and the expectation of the height of the ARG. Also we show give a relation between the expectation of the ARG and the expectation of the number of recombination events. At the end of this part we show that the ARG comes down from innity in the sense that we can dene it with X0... 

    Evolution of 'ligand-deffusion chreodes' on protein-surface models: A genetic-algorithm study

    , Article Chemistry and Biodiversity ; Volume 4, Issue 12 , 2007 , Pages 2766-2771 ; 16121872 (ISSN) Marashi, A ; Kargar, M ; Katanforoush, A ; Abolhassani, H ; Sadeghi, M ; Sharif University of Technology
    2007
    Abstract
    Lattice models have been previously used to model ligand diffusion on protein surfaces. Using such models, it has been shown that the presence of pathways (or 'chreodes') of consecutive residues with certain properties can decrease the number of steps required for the arrival of a ligand at the active site. In this work, we show that, based on a genetic algorithm, ligand-diffusion pathways can evolve on a protein surface, when this surface is selected for shortening the travel length toward the active site. Biological implications of these results are discussed. © 2007 Verlag Helvetica Chimica Acta AG, Zürich  

    Homozygous mutations in C14orf39/SIX6OS1 cause non-obstructive azoospermia and premature ovarian insufficiency in humans

    , Article American Journal of Human Genetics ; Volume 108, Issue 2 , 2021 , Pages 324-336 ; 00029297 (ISSN) Fan, S ; Jiao, Y ; Khan, R ; Jiang, X ; Javed, A. R ; Ali, A ; Zhang, H ; Zhou, J ; Naeem, M ; Murtaza, G ; Li, Y ; Yang, G ; Zaman, Q ; Zubair, M ; Guan, H ; Zhang, X ; Ma, H ; Jiang, H ; Ali, H ; Dil, S ; Shah, W ; Ahmad, N ; Zhang, Y ; Shi, Q ; Sharif University of Technology
    Cell Press  2021
    Abstract
    Human infertility is a multifactorial disease that affects 8%–12% of reproductive-aged couples worldwide. However, the genetic causes of human infertility are still poorly understood. Synaptonemal complex (SC) is a conserved tripartite structure that holds homologous chromosomes together and plays an indispensable role in the meiotic progression. Here, we identified three homozygous mutations in the SC coding gene C14orf39/SIX6OS1 in infertile individuals from different ethnic populations by whole-exome sequencing (WES). These mutations include a frameshift mutation (c.204_205del [p.His68Glnfs∗2]) from a consanguineous Pakistani family with two males suffering from non-obstructive... 

    Developmental barcoding of whole mouse via homing CRISPR

    , Article Science ; Volume 361, Issue 6405 , 2018 ; 00368075 (ISSN) Kalhor, R ; Kalhor, K ; Mejia, L ; Leeper, K ; Graveline, A ; Mali, P ; Church, G. M ; Sharif University of Technology

    Test based Software Repair Recommendation

    , M.Sc. Thesis Sharif University of Technology Rasekhi, Mahnaz (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    Abstract
    Debugging programs is a time-consuming and error-prone activity. So far, much research has tried to repair the programs automatically. Many of them try to change the location of the fault for a faulty program that fails at least one of its test cases so that all cases in the test suite pass. However, in real projects, the test suite is usually not enough, and the methods that aim to pass the test suite, often lead to the production of incorrect repairs, which is known as overfitting or weak test suite. In this regard, attention to methods based on program specification and the use of static code analysis have shown promising results. In this thesis, a method is presented that recommends... 

    Machine Learning Approaches for the Prediction of Pathogenicity in Genome Variations

    , M.Sc. Thesis Sharif University of Technology Sahebi, Alireza (Author) ; Sharifi Zarchi, Ali (Supervisor) ; Asgari, Ehsannedin (Supervisor)
    Abstract
    Genome mutations whose effects are not specified pose one of the challenges in identifying genetic diseases. Utilizing wet lab tests to detect the pathogenicity of variants can be time-consuming and fiscally expensive. A rapid and cost-effective solution to this problem is the use of machine learning-based variant effect predictors, which have the ability to determine whether a mutation is pathogenic or not. The objective of this research is to predict the pathogenicity of genome variations. The proposed model exclusively utilizes the protein sequence as its input feature and does not have access to other protein features. The data used to construct the model comprises mutations with... 

    A novel genetic algorithm based method for efficient QCA circuit design

    , Article Advances in Intelligent and Soft Computing, 25 May 2012 through 27 May 2012, New Delhi ; Volume 166 AISC, Issue VOL. 1 , 2012 , Pages 433-442 ; 18675662 (ISSN) ; 9783642301568 (ISBN) Kamrani, M ; Khademolhosseini, H ; Roohi, A ; Sharif University of Technology
    2012
    Abstract
    In this paper we have proposed an efficient method based on Genetic Algorithms (GAs) to design quantum cellular automata (QCA) circuits with minimum possible number of gates. The basic gates used to design these circuits are 2-input and 3-input NAND gates in addition to inverter gate. Due to use of these two types of NAND gates and their contradictory effects, a new fitness function has been defined. In addition, in this method we have used a type of mutation operator that can significantly help the GA to avoid local optima. The results show that the proposed approach is very efficient in deriving NAND based QCA designs  

    Statistical design of genetic algorithms for combinatorial optimization problems

    , Article Mathematical Problems in Engineering ; Volume 2011 , 2011 ; 1024123X (ISSN) Shahsavar, M ; Najafi, A. A ; Niaki, S. T. A ; Sharif University of Technology
    2011
    Abstract
    Many genetic algorithms (GA) have been applied to solve different NP-complete combinatorial optimization problems so far. The striking point of using GA refers to selecting a combination of appropriate patterns in crossover, mutation, and and so forth and fine tuning of some parameters such as crossover probability, mutation probability, and and so forth. One way to design a robust GA is to select an optimal pattern and then to search for its parameter values using a tuning procedure. This paper addresses a methodology to both optimal pattern selection and the tuning phases by taking advantage of design of experiments and response surface methodology. To show the performances of the proposed... 

    Content-based image retrieval based on relevance feedback and reinforcement learning for medical images

    , Article ETRI Journal ; Volume 33, Issue 2 , Apr , 2011 , Pages 240-250 ; 12256463 (ISSN) Lakdashti, A ; Ajorloo, H ; Sharif University of Technology
    Abstract
    To enable a relevance feedback paradigm to evolve itself by users' feedback, a reinforcement learning method is proposed. The feature space of the medical images is partitioned into positive and negative hypercubes by the system. Each hypercube constitutes an individual in a genetic algorithm infrastructure. The rules take recombination and mutation operators to make new rules for better exploring the feature space. The effectiveness of the rules is checked by a scoring method by which the ineffective rules will be omitted gradually and the effective ones survive. Our experiments on a set of 10,004 images from the IRMA database show that the proposed approach can better describe the semantic... 

    Concurrent project scheduling and material planning: a genetic algorithm approach

    , Article Scientia Iranica ; Volume 16, Issue 2 E , 2009 , Pages 91-99 ; 10263098 (ISSN) Sheikh Sajadieh, M ; Shadrokh, S ; Hassanzadeh, F ; Sharif University of Technology
    Abstract
    Scheduling projects incorporated with materials ordering results in a more realistic problem. This paper deals with the combined problem of project scheduling and material ordering. The purpose of this paper is to minimize the total cost of this problem by determining the optimal values of activity duration, activity finish time and the material ordering schedule subject to constraints. We employ a genetic algorithm approach to solve it. Elements of the algorithm, such as chromosome structure, unfitness function, crossover, mutation and local search operations are explained. The results of the experimentation are quite satisfactory