Ravichandra Sadam

• Doctor of Philosophy
• Professor (Associate) at National Institute of Technology Warangal

In a critical software system, the testers have to spend an enormous amount of time and effort maintaining the software due to the continuous occurrence of defects. To reduce the time and effort of a tester, prior works in the literature are limited to using documented defect reports to automatically predict the severity of the defective software m...

We automatically generate code coverage in the verification phase with the help of PROMELA (a language used by Spin checker). PROMELA is a process metalanguage of the Spin model checker. We are presenting a method that automatically generates from Abstract State Machine (ASM) specifications test which fulfils the desired coverage. ASM is used to pr...

In medical imaging, Retinal Vessel Segmentation (RVS) plays a significant role in finding the pathological changes in retinal blood vessels that can be used to detect various diseases like arteriolosclerosis, high blood pressure, diabetes, etc. Recently, convolutional neural networks (CNNs) and U-shaped (encoder–decoder) based models have been wide...

You may develop a potential prediction model, but how can I trust your model that it will benefit my software?. Using a software defect prediction (SDP) model as a tool, we address this fundamental problem in machine learning research. This is a preliminary work targeted at providing an analysis of the developed binary SDP model in real-time workin...

Due to the advantages of economizing the testing resources such as cost, time, and consequently the manpower on the developing software project, research on software defect prediction (SDP) has gained traction in academia. Though many works in the literature discuss constraints that are limiting the final prediction performance, finding the essenti...

In a critical software system, the testers have to spend an enormous amount of time and effort to maintain the software due to the continuous occurrence of defects. Among such defects, some severe defects may adversely affect the software. To reduce the time and effort of a tester, many machine learning models have been proposed in the literature,...

Context Cross-project defect prediction (CPDP) models are being developed to optimize the testing resources. Objectives Proposing an ensemble classification framework for CPDP as many existing models are lacking with better performances and analysing the main objectives of CPDP from the outcomes of the proposed classification framework. Method Fo...

Context: Cross-project defect prediction (CPDP) models are being developed to optimize the testing resources. Objectives: Proposing an ensemble classification framework for CPDP as many existing models are lacking with better performances and analysing the main objectives of CPDP from the outcomes of the proposed classification framework. Method: F...

Service‐oriented architecture (SOA) has been widely used to design enterprise applications in the past two decades. The services in SOA are becoming complex with the increase in changing user requirements and SOA is still seen as monolithic from a deployment perspective. Monolithic services make the application complex, and it becomes difficult to...

The migration of service oriented architecture (SOA) based applications to microservices architecture is a current research trend in the domain of software engineering. Estimating the effort required for migration is a challenging task as the traditional methods are not suitable for this new architectural style of microservices. Service Points (SP)...

This Distributed systems have evolved rapidly as the demand for independent design, and deployment of software applications has increased. It has emerged from the monolithic style of client-server architecture to service-oriented architecture, and then to the trending microservices. Monolithic applications are difficult to update, maintain, and dep...

Distributed systems have evolved rapidly as the demand for independent design and deployment of software applications has increased. Web services and microservices are two styles of designing distributed applications based on the principles of Service-Oriented Architecture (SOA). After the evolution of microservices, software architects are in chao...

Predicting the defect-proneness of a module can reduce the time, effort, manpower, and consequently the cost to develop a software project. Since the causes of software defects are difficult to identify, a wide range of machine learning models are still being developed to build a high performing prediction systems. For this reason, an hybrid approa...

Service oriented architecture (SOA) has been widely used in the design of enterprise applications over the last two decades. Though SOA has become popular in the integration of multiple applications using the enterprise service bus, there are few challenges related to delivery, deployment, governance, and interoperability of services. To overcome t...

Public key cryptography is based on two popular mathematical hard problems namely the integer factorization and discrete logarithm problem. Number Field Sieve (NFS) and Function Field Sieve (FFS) are the most efficient and widely used algorithms to solve integer factorization and discrete logarithm problems. The main phases of these algorithms are...

Continuous publication of statistics collected from various location-based applications may compromise users’ privacy as the statistics could be procured from users’ private data. Differential Privacy (DP) is a new privacy notion that offers a strong privacy guarantee to all users who participate in the statistics. However, the existing DP mechanis...

Microservices has emerged as a new architectural style of designing applications to overcome the challenges of service oriented architecture (SOA). With the evolution of microservices architecture, architects have started migrating legacy applications to microservices. However, some of the architects are in chaos whether to migrate the application...

Trajectory Data have been considered as a treasure for various hidden patterns which provide deeper understanding of the underlying moving objects. Several studies are focused to extract repetitive, frequent and group patterns. Conventional algorithms defined for Sequential Patterns Mining problems are not directly applicable for trajectory data. S...

The rapid growth in the usage of location-based services has resulted in extensive research on users’ trajectory data publishing. But, a key concern here is a potential breach of user privacy through various linkage attacks by an efficient adversary. There exist a few privacy preservation methods to defend against either single or combination of li...