S V ACHUTA RAO - Academia.edu (original) (raw)
Papers by S V ACHUTA RAO
The Internet and computer networks are exposed to an increasing number of security threats. With ... more The Internet and computer networks are exposed to an increasing number of security threats. With new types of attacks appearing continually, developing flexible and adaptive security oriented approaches is a severe challenge. In this context, anomaly-based network detection techniques are a valuable technology to protect target systems and networks against malicious activities. However, despite the variety of such methods described in the literature in recent years, security tools incorporating anomaly detection functionalities are just starting to appear, and several important problems remain to be solved. This paper begins with an exercise of the most well-known anomaly-based detection techniques. Then, available platforms, systems under development and research projects in the area are presented. Finally, we outline the main challenges to be dealt with for the wide scale deployment of anomaly-based detectors, with special emphasis on assessment issues. Network anomaly detection i...
Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or fram... more Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or framework delivering an inappropriate or surprising result, or making it perform in an unintended way. Software Defect Prediction (SDP) finds defective modules in software. The final product ought to have as few defects as possible to create top notch software. Early software defects discovery prompts diminished development costs and rework effort and better software. Software metrics guarantee quantitative methods to survey software quality. Software metrics are helpful to software process and product metrics. Thus, a defect prediction study is critical to guarantee quality software and software metric aggregation. In this study, the efficiency of classifier for SDP is assessed. Diverse classifiers like Naïve Bayes, K Nearest Neighbor (KNN), C4.5 and Multilayer Perceptrons Neural Network (MLPNN) are assessed for SDP.
In the last decade, empirical studies on object-oriented design metrics have shown some of them t... more In the last decade, empirical studies on object-oriented design metrics have shown some of them to be useful for predicting the faults-proneness of classes in object-oriented software systems. It would be valuable to know how object-oriented design metrics and class fault-proneness are related when fault severity is taken into account. In this paper we use logistic regression and principal component methods to empirically investigate the usefulness of object-oriented design metrics, specially a subset of the Chidamber and Kemerer suite in predicting fault-proneness when taking fault severity into account. In the era of Object Oriented software metrics demand for quality software has undergone with rapid growth during the last few years. This is leading to an increase in the development of metrics for measuring the properties of software such as coupling, cohesion and inheritance that can be used in early Quality assessments. Much effort has been developed to the development and empi...
Metrics are usually defined on a micro level like methods, classes and packages. These are failed... more Metrics are usually defined on a micro level like methods, classes and packages. These are failed to provide an adequate picture of the entire system effectively. By combine different metrics with varying output values and ranges to get insight in the evolution of the macro level system. We listed various metrics like Product, Project & Process and also various aggregation techniques in Traditional methods such as mean, median, sum, and cardinality; in Distribution fittings such as Log-Normal, Exponential, Negative binomial; and in Inequality Indices such as Theil, Gini, Kolm and Atkinson. The theoretical criteria in Domain, Range, and Invariance & Decomposability of various metrics are discussed. The Aggregation Techniques from simple mathematical operations to more complex operations to get Macro level system would be helpful as the outliers get pulled into the larger amounts of data. The Developers or Managers have an understanding of the parts of system are still needed to make ...
Software Defect Prediction (SDP) focuses on the detection of system modules such as files, method... more Software Defect Prediction (SDP) focuses on the detection of system modules such as files, methods, classes, components and so on which could potentially consist of a great amount of errors. SDP models refer to those that attempt to anticipate possible defects through test data. A relation is present among software metrics and the error disposition of the software. To resolve issues of classification, for the past many years, Neural Networks (NN) have been in use. The efficacy of such networks rely on the pattern of hidden layers as well as in the computation of the weights which link various nodes. Structural optimization is performed in order to increase the quality of the network frameworks, in two separate cases: The first is the typically utilized approximation error for the present data, and the second is the capacity of the network to absorb various issues of a general class of issues in a rapid manner along with excellent precision. The notion of Back Propagation (BP) is qui...
International Journal of Advanced Intelligence Paradigms
To assure the quality of software an important activity is performed namely software defect predi... more To assure the quality of software an important activity is performed namely software defect prediction (SDP). Historical databases are used to detect software defects using different machine learning techniques. Conversely, there are disadvantages like testing becomes expensive, poor quality and so the product is unreliable for use. This paper classifies the severity of defects by using a method based on optimised neural network (NN). In full search space, a solution is found by many meta-heuristic optimisations and global search ability has been used. Hence, high-quality solutions are finding within a reasonable period of time. SDP performance is improved by the combination of meta-heuristic optimisation methods. For class imbalance problem, meta-heuristic optimisation methods such as genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) are applied. The above method is based on SFLA and the experimental outputs show that it can do better than Leven berg Marquardt based NN system (LM-NN).
Research Journal of Applied Sciences, Engineering and Technology, 2016
Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or fram... more Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or framework delivering an inappropriate or surprising result, or making it perform in an unintended way. Software Defect Prediction (SDP) finds defective modules in software. The final product ought to have as few defects as possible to create top notch software. Early software defects discovery prompts diminished development costs and rework effort and better software. Software metrics guarantee quantitative methods to survey software quality. Software metrics are helpful to software process and product metrics. Thus, a defect prediction study is critical to guarantee quality software and software metric aggregation. In this study, the efficiency of classifier for SDP is assessed. Diverse classifiers like Naive Bayes, K Nearest Neighbor (KNN), C4.5 and Multilayer Perceptrons Neural Network (MLPNN) are assessed for SDP.
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
Software metrics and quality models have a very important role to play in measurement of software... more Software metrics and quality models have a very important role to play in measurement of software quality. A number of well-known quality models and software metrics are used to build quality software both in industry and in academia. Development of software metrics is an ongoing process with new metrics being continuously tried out. However, during our research on measuring software quality using object oriented design patterns, we faced many issues related to existing software metrics and quality models. For a particular situation of interest, any established metric can be used. If none is found to be appropriate, a new metric can be devised. In this paper, we discuss some of these issues and present our approach to software quality assessment.
Applied Mathematical Modelling, 2013
ABSTRACT
The Internet and computer networks are exposed to an increasing number of security threats. With ... more The Internet and computer networks are exposed to an increasing number of security threats. With new types of attacks appearing continually, developing flexible and adaptive security oriented approaches is a severe challenge. In this context, anomaly-based network detection techniques are a valuable technology to protect target systems and networks against malicious activities. However, despite the variety of such methods described in the literature in recent years, security tools incorporating anomaly detection functionalities are just starting to appear, and several important problems remain to be solved. This paper begins with an exercise of the most well-known anomaly-based detection techniques. Then, available platforms, systems under development and research projects in the area are presented. Finally, we outline the main challenges to be dealt with for the wide scale deployment of anomaly-based detectors, with special emphasis on assessment issues. Network anomaly detection i...
Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or fram... more Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or framework delivering an inappropriate or surprising result, or making it perform in an unintended way. Software Defect Prediction (SDP) finds defective modules in software. The final product ought to have as few defects as possible to create top notch software. Early software defects discovery prompts diminished development costs and rework effort and better software. Software metrics guarantee quantitative methods to survey software quality. Software metrics are helpful to software process and product metrics. Thus, a defect prediction study is critical to guarantee quality software and software metric aggregation. In this study, the efficiency of classifier for SDP is assessed. Diverse classifiers like Naïve Bayes, K Nearest Neighbor (KNN), C4.5 and Multilayer Perceptrons Neural Network (MLPNN) are assessed for SDP.
In the last decade, empirical studies on object-oriented design metrics have shown some of them t... more In the last decade, empirical studies on object-oriented design metrics have shown some of them to be useful for predicting the faults-proneness of classes in object-oriented software systems. It would be valuable to know how object-oriented design metrics and class fault-proneness are related when fault severity is taken into account. In this paper we use logistic regression and principal component methods to empirically investigate the usefulness of object-oriented design metrics, specially a subset of the Chidamber and Kemerer suite in predicting fault-proneness when taking fault severity into account. In the era of Object Oriented software metrics demand for quality software has undergone with rapid growth during the last few years. This is leading to an increase in the development of metrics for measuring the properties of software such as coupling, cohesion and inheritance that can be used in early Quality assessments. Much effort has been developed to the development and empi...
Metrics are usually defined on a micro level like methods, classes and packages. These are failed... more Metrics are usually defined on a micro level like methods, classes and packages. These are failed to provide an adequate picture of the entire system effectively. By combine different metrics with varying output values and ranges to get insight in the evolution of the macro level system. We listed various metrics like Product, Project & Process and also various aggregation techniques in Traditional methods such as mean, median, sum, and cardinality; in Distribution fittings such as Log-Normal, Exponential, Negative binomial; and in Inequality Indices such as Theil, Gini, Kolm and Atkinson. The theoretical criteria in Domain, Range, and Invariance & Decomposability of various metrics are discussed. The Aggregation Techniques from simple mathematical operations to more complex operations to get Macro level system would be helpful as the outliers get pulled into the larger amounts of data. The Developers or Managers have an understanding of the parts of system are still needed to make ...
Software Defect Prediction (SDP) focuses on the detection of system modules such as files, method... more Software Defect Prediction (SDP) focuses on the detection of system modules such as files, methods, classes, components and so on which could potentially consist of a great amount of errors. SDP models refer to those that attempt to anticipate possible defects through test data. A relation is present among software metrics and the error disposition of the software. To resolve issues of classification, for the past many years, Neural Networks (NN) have been in use. The efficacy of such networks rely on the pattern of hidden layers as well as in the computation of the weights which link various nodes. Structural optimization is performed in order to increase the quality of the network frameworks, in two separate cases: The first is the typically utilized approximation error for the present data, and the second is the capacity of the network to absorb various issues of a general class of issues in a rapid manner along with excellent precision. The notion of Back Propagation (BP) is qui...
International Journal of Advanced Intelligence Paradigms
To assure the quality of software an important activity is performed namely software defect predi... more To assure the quality of software an important activity is performed namely software defect prediction (SDP). Historical databases are used to detect software defects using different machine learning techniques. Conversely, there are disadvantages like testing becomes expensive, poor quality and so the product is unreliable for use. This paper classifies the severity of defects by using a method based on optimised neural network (NN). In full search space, a solution is found by many meta-heuristic optimisations and global search ability has been used. Hence, high-quality solutions are finding within a reasonable period of time. SDP performance is improved by the combination of meta-heuristic optimisation methods. For class imbalance problem, meta-heuristic optimisation methods such as genetic algorithm (GA) and shuffled frog leaping algorithm (SFLA) are applied. The above method is based on SFLA and the experimental outputs show that it can do better than Leven berg Marquardt based NN system (LM-NN).
Research Journal of Applied Sciences, Engineering and Technology, 2016
Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or fram... more Aim of study software defect is a flaw, miscalculation, or failure, in a computer program or framework delivering an inappropriate or surprising result, or making it perform in an unintended way. Software Defect Prediction (SDP) finds defective modules in software. The final product ought to have as few defects as possible to create top notch software. Early software defects discovery prompts diminished development costs and rework effort and better software. Software metrics guarantee quantitative methods to survey software quality. Software metrics are helpful to software process and product metrics. Thus, a defect prediction study is critical to guarantee quality software and software metric aggregation. In this study, the efficiency of classifier for SDP is assessed. Diverse classifiers like Naive Bayes, K Nearest Neighbor (KNN), C4.5 and Multilayer Perceptrons Neural Network (MLPNN) are assessed for SDP.
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
Software metrics and quality models have a very important role to play in measurement of software... more Software metrics and quality models have a very important role to play in measurement of software quality. A number of well-known quality models and software metrics are used to build quality software both in industry and in academia. Development of software metrics is an ongoing process with new metrics being continuously tried out. However, during our research on measuring software quality using object oriented design patterns, we faced many issues related to existing software metrics and quality models. For a particular situation of interest, any established metric can be used. If none is found to be appropriate, a new metric can be devised. In this paper, we discuss some of these issues and present our approach to software quality assessment.
Applied Mathematical Modelling, 2013
ABSTRACT