Aprna Tripathi

E-Governance challenges and cloud benefits

The worldwide revolution in Internet is changing our lives in terms of the way we work, learn and interact. These changes naturally should reflect the way government functions in terms of the organization of the government, its relationship with its citizens, institutions and businesses and cooperation with other governments. E-Governance, especially in developing countries, is looked upon as a means to change the very concept of governance resulting in empowerment of the citizens and increased transparency in public dealings by the governments; increased efficiencies in delivery of public goods is an inherent underlying assumption. Government aims to deliver more interactive services to citizens and businesses through E-Governance. For this, cloud computing may lead to significant cost savings. Cloud computing permits to uniformly cover the whole country with e-government solutions, independently of divergence of local administrative units that may be better or worse prepared to provide e-services. Service-oriented architecture facilitates provision of compound services covering whole customer processes, where a customer may be a citizen or an enterprise. And also a analysis of cloud computing and its application in the context of e-government.

An Improved History-Based Test Prioritization Technique Technique Using Code Coverage

Prioritization of test cases provides a way to run test cases with the highest priority earliest. Numerous empirical studies have shown that prioritization can improve a test suite’s rate of fault detection. Software testers prioritize test cases, to reduce the cost of regression testing. History Based Approach is one of the methods to prioritize the test cases. This approach takes into account the history of each of the test cases of the test suite such as fault detection, number of executions and other such factors to prioritize the test cases in the coming sessions. This paper extends the above approach to the modified lines. The modified lines are being prioritized first and subsequently followed by the concerned test cases. The proposed approach has been able to detect fault faster than the previous approach with less effort in comparison to the previous approach.

A metric for package level coupling

Several software development activities are based on object oriented paradigm. Such software projects comprise of packages that are collection of correlated classes which can be reused. This reusability of a package depends on its cohesion and coupling strength. To determine the coupling and cohesion, there are several established metrics at the class level, but at the package level, such reliable and established metrics rarely exist. To address this important issue, a new metric, termed as package level coupling (PLC) is proposed in this paper. The metric estimates the quality, as well as reusability of the object-oriented software. The connections among these packages and sub-connections among the classes, related to different packages are used to determine the proposed metric, i.e., PLC. To establish the proposed metric, it is successfully experimented over four large java-based open source software comprising of multiple packages. Further, it is statistically correlated with the help of various parameters, i.e., number of sub-connections and number of classes of the package. The experimental results show a very weak correlation between the proposed PLC and the number of classes in the package. Spearman’s Rank correlation coefficient is used to illustrate the correlation between sub-connection and PLC. A smaller value of 0.108 is obtained signifying that there is no strong correlation between these two parameters. Further, a correlation between PLC and number of classes obtained is −0.061, signifying that these two parameters tends towards independency while other existing approaches are highly dependent on number of classes.

A Design Phase Understandability Metric Based on Coupling and Cohesion for Object-Oriented Systems

As the software size grows, the maintenance become challenging. To make it easier, there is a need to measure some quality parameters in earlier phases of software development. Understandability has a major contribution to control the maintainability. Coupling and cohesion are two well-accepted parameters to measure the software quality parameters. In this paper, a model is proposed to measure the understandability that is based on coupling and cohesion.

SRS Based Estimation of Software Maintenance Effort

Software maintenance effort estimation has always been a challenge for the software practitioners, as it consumes about half of the overall development costs. The effort required to develop or maintain software depend on the complexity of yet to be developed software. The proposed measure estimates the requirement-based complexity based on SRS document of yet to be developed software for systematic and early prediction of software maintenance effort using Software Requirements Specifications (SRS) document of the proposed software. The result obtained validates that, the proposed maintenance measure is a comprehensive one and compares well with various other prevalent measures proposed in the past. The computation of proposed maintenance effort estimation involves least overhead as compared to others.

Event Correlation for Intrusion Detection Systems

Intrusion Detection System (IDS) have grown into a mature and feature rich technology that provides advanced features to detect intrusion and provide responses. It also allows the management system for security analysis by monitoring, configuring and analyzing the intrusion data. A better understanding of alerts by using a general framework and infrastructure for detecting intrusions through event correlation strategy minimizes the amount of data generated. Event correlation techniques are needed for two reasons. First, network attack detection is usually based on information or data received from distributed sensors, e.g. intrusion detection systems. During attacks, the generated amount of events is hard to handle and so it is difficult to evaluate the current attack situation for a larger network. Thus, the concept of event or alert correlation has been introduced. Event correlation paints a picture of what is now being called as network or cyber situational awareness and tries to guide the security administrator on the actions that he can take to mitigate the crisis. The aim of the event correlation for intrusion detection system (IDS) is to improve security by correlating events and reduce the workload on an IDS analyst. This correlation has been achieved by getting together similar alerts, thus allowing the analyst to only look at a few alerts instead of hundreds or thousands of alerts. In this paper, we correlate the results of SNORT Intrusion Detection System (IDS) with SEC (Simple Event Correlator) by taking the input from the MIT DARPA (Defense advanced Research Projects Agency) dataset. The alerts generated from Snort are very large and so it is difficult for the administrators to identify them. Here we correlate the alerts based on same name coming from different IP address. This correlation removes the duplication of alerts and thus reduces the information overload on the administrator.

Use Case Based Approach to Analyze Software Change Impact and Its Regression Test Effort Estimation

Software needs to be maintained and changed to satisfy the new requirement and existing faults. Without analyzed changes, change implemented to software often cause unexpected ripple effects. To avoid this and diminish the risk of performing undesirable changes, an impact analysis of the change is done. Software Change Impact Analysis (SCIA) needs to be computed at every change request for software systems, to access the impact information for several critical software engineering tasks such as risk analysis, effort estimation, and regression testing. The use of UML analysis/design models on large projects lead to a large number of interdependent UML diagrams. Paper proposes a UML model based approach strictly to use use-case diagram for impact analysis that is applicable in early decision making and change planning. Later, by using the impact set we estimate the regression test effort required for the effected change in the software. The reduction in test effort observed ranges from 47 to 95 %, saving significant software testing cost.

A New Design Based Software Coupling Metric

The increasing need for software quality measurements has led to extensive research into software metrics and the development of software metric tools. Creating components which are reusable is seen as one of the best practice in industry today. To create reusable components the dependency between each component should be as low as possible. Hence, to maintain high quality software, developers need to strive for a low-coupled and highly cohesive design. However, as mentioned by many researchers, coupling and cohesion metrics lack formal and standardized definitions and thus for each metric there is more than one interpretation. This paper introduces our view of measurement of coupling for Java projects and our implementation approach. Coupling metrics are calculated at class level by considering the relationships between the methods of classes.

Quality Validation of Software Design before Change Implementation

Change in any software application seems to be very simple when someone demands it, but the complexity of the task appears during implementation phase. Change implementation is acceptable when it includes the requested functionality as well as improves and preserves the quality of software. Complexity is an important issue for software development as it affects the cost, effort and quality of the product. Change complexity could be helpful in analyzing the impact of change. This paper focuses on measuring the software complexity that analyzes the quality of software design. To measure the complexity, UML class diagram is considered. Additionally, the goal of this paper is to identify the best possible design among various possible solutions to implement requested change in the existing system that does not adversely affects the software design of the existing software. Here, the change type considered is only new requests made by user or client.

Software Change Validation before Change Implementation

Software maintenance is the most demanding and most expensive task of the software development. Quality of the regression testing decides the quality of the maintained software. Several approaches, code-based and model- based are recommended in literature to minimize the regression test suit. This paper proposes the model based technique to validate the change before implementation. The approach considers the SRS and UML class diagram for earlier change validation. We update the SRS for including the requested change and prepare difference_SRS file that contain the differences of old and new SRS. After imposing these changes in UML class diagram, dependency matrix for both old and new class diagram and a difference dependency matrix from these two dependency matrices is generated we map the entire changes one by one form difference_SRS file to difference dependency matrix. Using the approach, we have concluded a case study and observed impressive gains in terms of less requirement of regression testing effort. The result shows that the approach allows the implementation of change only after validating the requested change after the design phase. Keywords: Software Change Validation, SRS, Regression Testing, Class Diagram, UML and Dependency Matrix.