Software engineering is a discipline that undergone many improvements that aims to keep up with the new advancements in technologies and the modern business requirements through developing effective approaches to reach the final software product, agile software development is one of these successful approaches. Agile software development is a lightweight approach that was proposed to overcome the convolutional development methods’ limitations and to reduce the overhead and the cost while providing flexibility to adopt the changes in requirements at any stage, this is done by managing the tasks and their coordination through a certain set of values and principles. In this work, a comprehensive review that outlines the main agile values and principles, and states the key differences that distinguish agile methods over the traditional ones are presented. Then a discussion of the most popular agile methodologies; their life cycles, their roles, and their advantages and disadvantages are outlined. The recent state of art trends that adopts agile development especially in cloud computing, big data, and coordination are also explored. And finally, this work highlights how to choose the best suitable agile methodology that must be selected according to the task at hand, how sensitive the product is and the organization structure.

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Agile Software Development: Methodologies and Trends

At some point, the understudies have insufficient information to proceed further in their career, so getting right exhortation from experienced individual is vital which will be accomplished by establishing an online alumni interface. With this the alumni can communicate to the students regarding job opportunities and the students can share their department activities to the alumni. The proposed system has the dynamic architecture and less static content, which can empower the full duplex association between all graduated students and understudies. This paper portrays how the system will function and collaborate the graduated class with the present understudies.

Next Generation Web for Alumni Web Portal

This review paper covers the forensic-relevant literature in digital evidence from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol Review Papers 2019.pdf

Interpol review of digital evidence 2016 - 2019.

Database Forensic Investigation (DBFI) involves the identification, collection, preservation, reconstruction, analysis, and reporting of database incidents. However, it is a heterogeneous, complex, and ambiguous field due to the variety and multidimensional nature of database systems. A small number of DBFI process models have been proposed to solve specific database scenarios using different investigation processes, concepts, activities, and tasks as surveyed in this paper. Specifically, we reviewed 40 proposed DBFI process models for RDBMS in the literature to offer up-to-date and comprehensive background knowledge on existing DBFI process model research, their associated challenges, issues for newcomers, and potential solutions for addressing such issues. This paper highlights three common limitations of the DBFI domain, which are: 1) redundant and irrelevant investigation processes; 2) redundant and irrelevant investigation concepts and terminologies; and 3) a lack of unified models to manage, share, and reuse DBFI knowledge. Also, this paper suggests three solutions for the discovered limitations, which are: 1) propose generic DBFI process/model for the DBFI field; 2) develop a semantic metamodeling language to structure, manage, organize, share, and reuse DBFI knowledge; and 3) develop a repository to store and retrieve DBFI field knowledge.

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Database Forensic Investigation Process Models: A Review

CAPTCHA is one of the most common solutions to check if the user trying to enter a Website is a real person or an automated piece of software. This challenge-response test, implemented in many Internet Websites, emphasizes the gaps between accessibility and security on the Internet, as it poses an obstacle for the learning-impaired in the reading and comprehension of what is presented in the test. Various types of CAPTCHA tests have been developed in order to address accessibility and security issues. The objective of this study is to investigate how the differences between various CAPTCHA tests affect user experience among populations with and without learning disabilities. A questionnaire accompanied by experiencing five different tests was administered to 212 users, 60 of them with learning disabilities. Response rates for each test and levels of success were collected automatically. Findings suggest that users with learning disabilities have more difficulties in solving the tests, especially those with distorted texts, have more negative attitudes towards the CAPTCHA tests, but the response time has no statistical difference from users without learning disabilities. These insights can help to develop and implement solutions suitable for many users and especially for population with learning disabilities.

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CAPTCHA: Impact on User Experience of Users with Learning Disabilities

Ten years of critical review on database forensics research

User stories play an important role in extreme programming. Extreme programming is one of the popular processes from agile software development. Agile software development is an emerging method of software development, as compared to traditional approach. The success of software development is based on user stories satisfaction. As requirement engineering is the first phase in software development approach, user stories are written from customer requirements. This paper discusses about writing user stories by different ways which it may be treated positively or negatively and how it impact on requirement verification. User stories examples written in this paper are through experience gained from attendance monitoring project. In this paper first we have given brief idea about user stories with examples, and then we have described positive and negative user stories followed by conclusion and future work.

Agile software development: Positive and negative user stories

In today's world data is growing very rapidly, which we call as big data. To deal with these large data sets, currently we are using NoSQL databases, as relational database is not capable for handling such data. These schema less NoSQL database allow us to handle unstructured data. Through this paper we are comparing two NoSQL databases MongoDB and CouchBase server, in terms of image storage and retrieval. Aim behind selecting these two databases as both comes under Document store category. Major applications like social media, traffic analysis, criminal database etc. require image database. The motivation behind this paper is to compare database performance in terms of time required to store and retrieve images from database. In this paper, firstly we are going describe advantages of NoSQL databases over SQL, then brief idea about MongoDB and CouchBase and finally comparison of time required to insert various size images in databases and to retrieve various size images using front end tool Java.

Mongodb, couchbase: Performance comparison for image dataset

For any digital application, database positions at the heart of that application. Today with the big data requirement, databases are roaming from traditional relational databases towards NoSQL databases. The diverse numbers of database options are available under the NoSQL category. As per the database engine survey, MongoDB is the preferred NoSQL database among other databases. Due to numerous features available in MongoDB, this database is widely used in different applications. This database is fulfilling the needed requirements for upcoming applications. This paper is a study of indexing, which is one of the important artifacts of the database. Indexing is one of the special forms of the data structure. It plays an important role in performance improvement by saving execution time in terms of document scan. Use of indexing and its effect on query result is highlighted here. Another reason for selecting this artifact is indexing study is also important from a database forensics perspective. Database forensics is a detailed analysis of the database to find the origin of the problem.

MongoDB Indexing for Performance Improvement

Tamper detection is the ability of a software or a device to sense that an active attempt to fail the device integrity or data associated with the system, the detection of any attack or threat may enable the device to initiate the defensive actions accordingly. In NoSQL database, detecting the tamper is not simple as in relational database. This paper mainly focuses on the database security. Whether the data is secured or not? or the data is tampered? To detect any tamper in NoSQL database, the model is been built which uses the logs, port connections as an input and set the authorization and authentication level which helps to retrieve logs accordingly. The paper generates hash as well as checksum of NoSQL database files and log files for checking data integrity, and we have created a simple task manager which stores data in real time, which shows tamper in database.

Rupali M. Chopade

Papers

Ten years of critical review on database forensics research

Agile software development: Positive and negative user stories

Mongodb, couchbase: Performance comparison for image dataset

MongoDB Indexing for Performance Improvement

Tamper Detection in MongoDB and CouchDB Database