Prashant Johri

Work place: School of Computing Science and Engineering, Galgotias University,Uttar Pradesh and 201310,India



Research Interests: Data Structures and Algorithms, Data Mining, Computing Platform, Computer Architecture and Organization, Pattern Recognition


Prashant Johri is Professor & Director GIMT( MCA), Galgotias Institute of Management &
Technology UP Technical University, Greater Noida, India. He has published several papers in International/National Journals and Proceedings. His areas of research are Software Reliability, Data Mining and Warehousing, Big Data Security & Privacy, Big Data Open Platform and Pattern Recognition.

Author Articles
Security Challenges, Authentication, Application and Trust Models for Vehicular Ad Hoc Network- A Survey

By Akash Vaibhav DilendraShukla Sanjoy Das Subrata Sahana Prashant Johri

DOI:, Pub. Date: 8 May 2017

Vehicular Ad hoc Network could manage the various critical issues of road transport. That is why it is the most crucial field of research for most of the researchers. This survey paper discusses various issues related to Security Challenges, Security Architecture actors, Security Authentication, Application Constraints, various trust models etc. this paper encourages you to think about various fields of work need to be carried out in this field for the better VANET environment. Various schemes have been mentioned which could be improved further as per considering various real time conditions.

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Opinion based on Polarity and Clustering for Product Feature Extraction

By Sanjoy Das Bharat Singh Saroj Kushwah Prashant Johri

DOI:, Pub. Date: 8 Sep. 2016

In recent time, with the rapid development of web 2.0 the number of online user-generated review of product is increases very rapidly. It is very difficult for user to read all reviews and handle all websites to make a valuable decision at feature level. The feature level opinion mining has become very infeasible when people write same feature with contrary words or phrases. To produce a relevant feature based summary of domain synonyms words and phrase, need to be group into same feature group. In this work, we focus on feature based opinion mining and proposed a dynamic system for generate feature based summary of specific feature with specific polarity of opinion according to customer demand on periodic base and changed the summary after a span of period according to customer demand. First a method for feature (frequent and infrequent) extraction using the probabilistic approach at word-level. Second identify the corresponding opinion word and make feature-opinion pair. Third we designed an algorithm for final polarity detection of opinion. Finally, assigning the each feature-opinion pair into the respective feature based cluster (positive, negative or neutral) to generate the summary of specific feature with specific opinion on periodic base which are helpful for user. The experiment results show that our approach can achieves 96%accuracy in feature extraction and 92% accuracy in final polarity detection of feature-opinion pair in feature based summary generation task.

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Resource Allocation Policies for Fault Detection and Removal Process

By Md. Nasar Prashant Johri Udayan Chanda

DOI:, Pub. Date: 8 Nov. 2014

In software testing, fault detection and removal process is one of the key elements for quality assurance of the software. In the last three decades, several software reliability growth models were developed for detection and correction of faults. These models were developed under strictly static assumptions. The main goal of this article is to investigate an optimal resource allocation plan for fault detection and removal process of software to minimize cost during testing and operational phase under dynamic condition. For this we develop a mathematical model for fault detection and removal process and Pontryagain’s Maximum principle is applied for solving the model. Genetic algorithm is used to find the optimal allocation of fault detection and removal process. Numerical example is also solved for resource allocation for fault detection and remoal process.

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Dynamic Effort Allocation Problem Using Genetic Algorithm Approach

By Md. Nasar Prashant Johri Udayan Chanda

DOI:, Pub. Date: 8 Jun. 2014

Effort distribution plays a major role in software engineering field. Because the limited price projects are becoming common today, the process of effort estimation becomes crucial, to control the budget agreed upon. In last 10 years, numerous software reliability growth models (SRGM) have been developed but majority of model are under static assumption. The basic goal of this article is to explore an optimal resource allocation plan to minimize the software cost throughout the testing phase and operational phase under dynamic condition using genetic algorithm technique. This article also studies the resource allocation problems optimally for various conditions by investigating the activities of the model parameters and also suggests policies for the optimal release time of the software in market place.

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Software Testing Resource Allocation and Release Time Problem: A Review

By Md. Nasar Prashant Johri Udayan Chanda

DOI:, Pub. Date: 8 Feb. 2014

Software testing Resource allocation and release time decisions are vital for the software systems. The objective behind such critical decisions may differ from firm to firm. The motive of the firm may be maximization of software reliability or maximization of number of faults to be removed from each module or it may be minimization of number of faults remaining in the software or minimization of testing resources. Taking into consideration these different aims, various authors have investigated the problem of resource allocation and release time problem. In this paper we investigate various software release policies and resource allocation problem, for example, policies based on the dual constraints of cost and reliability.

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