Anil Kumar Tripathi

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• PhD
• Professor (Full) at Indian Institute of Technology BHU

Evaluating the quality of user stories is crucial for the success of agile software development. This paper investigates the efficacy of Large Language Models (LLMs) in assessing the quality of individual user stories using the Quality User Story (QUS) framework, which categorizes quality criteria into syntactic, semantic, and pragmatic dimensions....

Estimating the number of defects in a software project before the testing phase can reduce the enormous amount of development cost and help in allocating testing resources optimally and efficiently. However, estimating the number of defects in each module of a successive version of the software system will be more efficient in minimizing the develo...

Cloud computing, edge computing, replicated databases, and various modern technologies adopt distributed computing concepts for a reliable, high-performance, large-scale computational platform. In distributed computing, leader election is a fundamental problem because the elected leader helps coordinate and utilize the resources efficiently. Severa...

Cross-project fault prediction (CPFP) uses data sets from projects to predict faulty/non-faulty modules. Cross-project fault number estimation (CPFNE) is one step ahead of CPFP, because it not only predicts faulty modules but also estimates the number of faults in that module. In this article, we proposed a new computational architecture using a de...

Cloud computing, edge computing, replicated databases, and various modern technologies are adopting distributed computing concepts for a reliable, high-performance, large-scale computational platform. In distributedcomputing, leader election is a fundamental problem because the elected leader helps coordinate andutilize the resources efficiently. S...

Due to high impact of internet technology and rapid change in software systems, it has been a tough challenge for us to detect software defects with high accuracy. Traditional software defect prediction research mainly concentrates on manually designing features (e.g., complexity metrics) and inputting them into machine learning classifiers to dist...

Group decision making (GDM) involving consensus reaching process (CRP) attempts to achieve a consensus among Decision-Makers (DMs) before coming to a final decision. Computer-based decision support systems are present to support the decision-making process called the Group Decision Support Systems (GDSS). The traditional GDSS being centralized is s...

A new consensus mechanism, Proof of Karma (PoK), is proposed based on karma (actions) of nodes. PoK incorporates a self-stabilizing leader election algorithm based on karma score to ensure consistency in the system. In PoK, both new and existing nodes get a fair chance to earn profit by becoming a leader and adding a valid block to the blockchain....

In Group Decision-Making (GDM), decision-makers (DMs) who are experts take wise decisions. But in systems such as smart cities, IoT, and e-democracy, the acceptance and survival of the decision given by the experts depend on the experience of citizens and end-users. Hence, an attempt can be made to use the citizens' perceptions. A potential solutio...

This study focuses on two issues of group decision-making (GDM). First, the multiple rounds of feedback recommendations in the consensus reaching process (CRP) make GDM inefficient. The second is no involvement of heterogeneous decision-makers (DMs), possibly end-users as stakeholders apart from the experts. To address the first issue, a novel thre...

Decision-making appears as a complex and challenging task when it requires finding the most suitable alternative among the numerous alternatives in the presence of multiple, usually conflicting criteria. At the same time, stakeholders expect a simple, transparent, and traceable decision-making method. Multi-Criteria Decision-Making (MCDM) methods r...

In this work, we propose a multi-tier architectural model to separate functionality and security concerns for distributed cyber-physical systems. On the line of distributed computing, such systems require the identification of leaders for distribution of work, aggregation of results, etc. Further, we propose a fault-tolerant leader election algorit...

This work presents a self-stabilizing leader election algorithm for arbitrary network topology. Here, we introduce the concept of the provisional leader that helps to improve the system performance. The proposed algorithm identifies r comparatively higher potential leader capable nodes in the system and designates the highest potential node among t...

The idea of industry 4.0 is quite pertinent for CPS. The integration of cyber components enhances a physical system’s capabilities by incorporating intelligence into objects and services. On the other hand, these systems are more vulnerable to cyber-attacks than traditional hard-wired electro-mechanical systems and infrastructure as they are access...

Torus network topology offers many advantages such as higher speed, lower latency, better fairness, and lower energy consumption. For these kinds of benefits, nowadays, it is used to construct many parallel and distributed systems like IBM Blue Gene, IBM Sequoia, Mira, and Sugon TC8600. In parallel and distributed computing, multiple nodes act toge...

Software defect prediction (SDP) is the process of detecting fault-prone classes or modules in a software system. It helps in allocating resources before the testing phase more optimally. Due to a lack of an adequate dataset, defects can be predicted by employing data from different projects to train the classifier called cross-project defect predi...

The quality of the defect datasets is a critical issue in the domain of software defect prediction (SDP). These datasets are obtained through the mining of software repositories. Resent studies claims over the quality of the defect dataset. It is because of inconsistency between bug/clean fix keyword in fault reports and the corresponding link in t...

Predicting defects during software testing reduces an enormous amount of testing effort and help to deliver a high‐quality software system. Owing to the skewed distribution of public datasets, software defect prediction (SDP) suffers from the class imbalance problem, which leads to unsatisfactory results. Overfitting is also one of the biggest chal...

Several prediction approaches are contained in the arena of software engineering such as prediction of effort, security, quality, fault, cost, and re-usability. All these prediction approaches are still in the rudimentary phase. Experiments and research are conducting to build a robust model. Software Fault Prediction (SFP) is the process to develo...

In a distributed system, multiple nodes work together to build a highly available, reliable, resource shareable, and fault-tolerant system to achieve a common goal. Here, multiple nodes work together to complete a task, so coordination is essential among these nodes. Electing a node as a system leader from among all the nodes can be a possible solu...

Enhanced quality with reduced cost and reduced time-to-market is the primary goal of any software industry. Researchers and practitioners are trying to aspire it with many techniques. Object-oriented framework is the promising technology to promote reuse, thus realizing desired goal. Inherently complex design and large size of a framework make it d...

Reducing energy consumption in processors has become a critical issue in cluster systems. The dynamic voltage and frequency scaling (DVFS) is one of the effective techniques to minimize energy consumption in processors when executing parallel applications. These applications may consist of many interrelated tasks that may be computed when their pre...

With the proliferation of a number of IoT-based service providers in the market, it would be difficult to select a suitable IoT service as per the requirement among the vast pool of available services showing similar capabilities. Quality-of-service (QoS) parameters that define a service may be used for doing an appropriate selection. Here we consi...

Predicting the number of bugs in a software system intensifies the software quality and turns down the testing effort required in software development. It reduces the overall cost of software development. The evolution of hardware, platform, and user requirements leads to develop the next version of a software system. In this article, we formulate...

In software fault prediction systems, there are many hindrances for detecting faulty modules, such as missing values or samples, data redundancy, irrelevance features, and correlation. Many researchers have built a software bug prediction (SBP) model, which classify faulty and non-faulty module which are associated with software metrics. Till now v...

Efficient scheduling is critical for achieving improved performance of distributed applications where an application is to be considered as a group of interrelated tasks and represented by a task graph. In this work, we present a clustering-based scheduling algorithm called effective critical path (ECP) to schedule precedence constrained tasks on m...

In multiprocessor environments, the scheduling algorithms play a significant role in maximizing system performance. In this paper, we propose a clustering‐based task scheduling algorithm called Edge Priority Scheduling (EPS) for multiprocessor environments. The proposed algorithm extends the idea of edge zeroing heuristic and uses the concept of ed...

In Parallel and Distributed computing environments, power optimization is emerging as one of the most important issues in achieving high system performance. Nowadays processing units in computer systems are designed by using software controlled Dynamic Voltage Frequency Scaling (DVFS) to reduce the energy consumption of processing units. In this wo...

Meta-patterns are a sort of basic object-oriented constructs that have been used to design an object-oriented framework. It has been used to precisely describe possible design pattern of a framework at meta-level to manifest framework hot-spots and its corresponding adaptability. The present study is an attempt to develop a genetic algorithm approa...

Unified Modeling Language (UML) has been frequently used as one of the most powerful object-oriented graphical modeling tool for designing and modeling a safety-critical and control system since past decades. UML can capture all the system requirements, and the developed model is well understood by all the stakeholders. However, UML model has some...

Probabilistic Safety Assessment approach has been successfully applied in engineering, economics, computer science, and statistics to resolve a wide range of safety-related problems. However, using the Probabilistic Safety Assessment for quantifying the safety of a safety-critical system is a challenging task in the Safety Engineering community. Th...

Using Probabilistic Reliability analysis for Quantifying Reliability of a system is already a common practice in the Reliability Engineering community. This method plays an essential role in analyzing the Reliability of nuclear plants and their various components. In Nuclear Power Plants Reactor Core Cooling System is a component of prime importanc...

Cloud computing is an emerging distributed computing paradigm that solves immense scientific applications through distributing computing resources over the Internet. These applications may have a huge number of tasks that may increase their execution costs, if not scheduled appropriately. Thus, scheduling of tasks is one of the key challenges in cl...

Efficient scheduling algorithms play an essential part in heterogeneous computing systems to achieve high performance. The problem of producing an optimal schedule for the precedence-constrained tasks is recognized to be an NPcomplete problem. To work out this problem, the researchers have already been proposed various scheduling algorithms in the...

In the past several decades, significant attention has been devoted to the quality assessment of safety-critical (SC) and control systems from many perspectives such as its reliability, safety, and performance. Researchers are continuing to put their efforts to ensure these dependability attributes. This study summarises the state of the art in the...

The state space models has been successfully applied in engineering, statistics, computer science and economics to solve a broad range of dynamical systems problems; like safety analysis, reliability analysis, performability analysis, etc. However, embedding the complete and accurate system requirements in such models is quite challenging. Analyzin...

Any risk in safety-critical or control applications may lead to catastrophic disaster; hence, safety is a primary concern for such applications. The impact of risk varies from minor inconvenience and cost to personal injury, significant economic loss, and death. Therefore, a safety assessment process should be an inherent part of the system develop...

State-space modeling is useful for prognostics of safety-critical systems. However, building such a model that embeds all the system requirements is a challenge. Furthermore, it requires expertise and hence isn't easily understood by all the stakeholders. UML can handle these challenges. A proposed approach converts a UML model into a state-space m...

Existing methods to predict software reliability using the Markov chain are based on assumed state-transition probabilities. A new prediction approach applied to a nuclear plant's feed-water system yielded results that were 96.9 percent accurate relative to the system's actual reliability. Across 38 operational datasets, the average accuracy was 99...

Early prediction of software reliability may be used to evaluate design feasibility, compare design alternatives, identify potential failure areas, trade-off system design factors, track reliability improvements, identify the cost overrun at an early stage and to provide optimal development strategies. Many researchers have proposed different appro...

A distributed computing system provides a platform for execution of concurrently executable communicating modules or tasks of software applications. We have developed a software for computing best reliable task allocation of redundant distributed system with different redundancy levels. In this paper the effect of accumulated execution time/intermo...

Distributed Computing System (DCS) is the natural candidate for the future computing system and in recent past it has received much attention in the computing community. Before the system is fully available for use, certain Important issues are to be resolved. An essential phase in Operating System (OS) of the DCS is task allocation, which is an NP...

Early prediction of software reliability provides basis for evaluating potential reliability during early stages of a project. It also assists in evaluating the feasibility of proposed reliability requirements and provides a rational basis for design and allocation decisions. Many researchers have proposed different approaches to predict the softwa...

The computation of a set of performance indicators of a computer-based system can be achieved through dependability analysis. Researchers have proposed several methods and tools that have an ability to give a prognosis for the failure of a computer-based system. These tools and methods are classified into three main approaches: model-based, data-dr...

Instrumentation and Control systems are the nervous system of a nuclear power plant. They monitor all facets of the plant’s health and help respond with care and adjustments needed, thus ensuring goals of efficient power production and safety. Due to safety significance of I&C, it becomes increasingly important to have a design verification methodo...

Quantifying software reliability, such as performance and dependability, through stochastic behavior models (or labeled transition systems) is already a common practice in the software analysis community. However, those models are usually too fine grained to represent an accurate view of the software system by its stakeholders. Scenarios, on the ot...

Knowledge engineering applied to the Component Based Software Engineering (CBSE) field is an important research area that focuses on identification, specification and validation of knowledge and experiences acquired during various phases of component based software development cycle. This work presents a systematic approach to knowledge identificat...

This study presents a newer approach for maturity analysis of component-based software processes. Conventional maturity models aim at learning from experiences of different activities so as to attain maturity. In case of component-based software, we have additional requirements of tracking maturity of software components and the composition process...

Computer based safety critical systems are progressively replacing analog systems in safety-critical applications like nuclear power plants. Hence these systems require modeling techniques to estimate performability in the early stages of the system development life cycle. This paper addresses the dynamic modeling of Test Facility of a safety criti...

Importance of testing has been realized in literature now, although late, but has been realized. Testing of Non Functional Requirement still remains unattended by the Software engineering Community. It is still being given second hand treatment from its specification, design to Testing. We try to analyze the contributory factors of testability of N...

Multimedia Information may have multiple semantics depending on context, a temporal interest and user preferences. Hence we are exploiting the plausibility of context associated with semantic concept in retrieving relevance information. We are proposing an Affective Feature Based Implicit Contextual Semantic Relevance Feedback (AICSRF) to investiga...

Software Development has started experiencing the need of consideration of NFR (Non Functional Requirements) for producing high quality acceptable software. Mostly software engineering literature has considered only for testing Functional Requirements. In context of such a need this work attempts to consider NFR, resulting from quality concerns of...

This study presents a quantitative approach for dependency analysis of Component Based Software (CBS) systems. Various types of dependency, in a C BS, have been observed through 'assumptions' and based on these observations some derived dependency relationships are proposed. The proposed dependency relationships are validated theoretically and an e...

Several recurring patterns of classes exist in many object oriented software as an experience of developers. Design Pattern Detection is an important part of many solutions to Software Reuse practices. Design pattern instances are highly important and useful for program understanding and software maintenance. Hence an automatic and reliable design...

Design Pattern Detection is a part of many solutions to Software Engineering problems. It is a part of reengineering process and thus gives significant information to the designer. Design Pattern improves the program understanding and software maintenance. Therefore, a reliable design pattern discovery is required. Graph theoretic approaches have b...

In a component-based software development life cycle, selection of preexisting components is an important task. Every component that has to be reused has an associated risk of failure of not meeting the functional and non-functional requirements. A component's failure would lead a developer to look for some other alternative of combinations of COTS...

In recent times, computer based systems are frequently used for protection and control in the various industries viz Nuclear, Electrical, Mechanical, Civil, Electronics, Medical, etc. From the operating experience of those computer based systems, it has been found that the failure of which can lead to the severe damage to equipments or environmenta...

Design Pattern Detection has been documented so far in the literature. The knowledge of design Pattern existence in the program improves the program understanding and software maintenance. Design pattern is a technology for design reuse. Experts store their experiences in the form of design patterns. Reengineering done by novice users will be succe...

Software frameworks, common and reusable to the development of a family of applications, are pre-implemented architectures having predefined points of variability. During framework reuse, implementation of one (or more than one) of the different possible alternatives of the variability take place. Variability is the number of possible variant imple...

Sarkar's edge zeroing heuristic for scheduling precedence constrained task graphs on parallel systems can be viewed as a priority based algorithm in which the priority is assigned to edges. In this algorithm, the priority is taken as the edge weight. This can also be viewed as a module dependent priority function that is defined for pairs of module...

In many object oriented softwares, there are recurring patterns of classes. With the help of these patterns specific design problem can be solved and object oriented design becomes more flexible and reusable. Design Pattern Detection is a part of solutions to Software Engineering difficulties. Mining of design pattern instances is important for pro...

In many object oriented softwares, there are recurring patterns of classes. Design pattern instances are important for program understanding and software maintenance.Hence a reliable design pattern mining is required. Here we are applying decision tree approach followed by subgraph isomorphism technique for design pattern detection.

Design Pattern Detection is a part of many solutions to Software Engineering difficulties. It is a part of reengineering process and thus gives important information to the designer. Design Pattern existence improve the program understanding and software maintenance. With the help of these patterns specific design problem can be solved and object o...

Design Pattern Detection is a part of many solutions to Software Engineering difficulties. It is a part of reengineering process and thus gives important information to the designer. Design Pattern existence improve the program understanding and software maintenance. With the help of these patterns specific design problem can be solved and object o...

Dependence analysis among software components is still a challenging issue for practitioners and researchers. We propose the representation of dependence among software components as a Component Interaction Graph (CIG). We make use of a well known data structure consisting of "two linear arrays" to represent the CIG. Based on this representation, w...

Design Patterns are proven solution to common recurring design problems. Design Pattern Detection is most important activity that may support a lot to re-engineering process and thus gives significant information to the designer. Knowledge of design pattern exists in the system design improves the program understanding and software maintenance. The...

Frameworks are developed to capture the recurring design practices in terms of skeletons of software subsystems/ systems. They are designed 'abstract' and 'incomplete' and are designed with predefined points of variability, known as hot spots, to be customized later at the time of framework reuse. Frameworks are reusable entities thus demand strict...

Frameworks are time-tested highly reusable architectural skeleton structures. They are designed 'abstract' and 'inco-mplete' and are designed with predefined points of variability, known as hot spots, to be customized later at the time of framework reuse. Frameworks are reusable entities thus demand stricter and rigorous testing in comparison to on...

Frameworks provide large scale reuse by providing skeleton structure of similar applications. But the generality, that a framework may have, makes it fairly complex, hard to understand and thus to reuse. Frameworks have been classified according to many criteria. This paper proposes two types of framework (based on the concept of 'generality') name...

The Capability Maturity Model (proposed by SEI-CMU) does not consider Component Based Software Engineering (CBSE) principles in its considerations of levels and KPAs. It is therefore necessary to consider a model that is based on peculiarities and importance of CBSE and hence a new model under the name ICMM (Integrated Component Maturity Model) for...

For many decades, nanotechnology has been developed with cooperation from researchers in several fields of studies including physics, chemistry, biology, material science, engineering, and computer science. In this paper, we explore the nanotechnology development community and identify the needs and opportunities of computer science research in nan...

Frameworks provide large scale reuse by providing skeleton structure ofsimilar applications. But, the generality, that a framework may have, makes itfairly complex, hard to understand and thus to reuse. This paper defines andanalyzes two types of frameworks: tight and loose. It then proposes a strategyfor framework development methodology that lead...

Component-based development (CBD), an approach to develop a software system with the help of reusable software components, has its own challenges because its parallel development process, coding style, system life cycle, etc. are required to be different from those of conventional software development. In this work, an attempt has been made to cons...

A number of algorithms is proposed for allocation of tasks in a DCS. Most of them did not consider allocation of various unrelated tasks partitioned into modules by taking into account the architectural capability of the processing nodes and the connectivity among them. This work considers allocation of disjoint multiple tasks with corresponding mo...

IntroductionGA for Task Allocation The Fitness FunctionReliability ExpressionAlgorithmIllustrative ExamplesDiscussions and Conclusion Reference The Fitness FunctionReliability Expression