Earned Value Management (EVM) measures project performance against a baseline plan. It identifies deviations in budget and schedule, aids project managers in taking earlier corrective actions against cost and schedule overruns. Although the literature highlights the significance of scope by adopting it as a leading indicator to measure project success or failure. However, EVM does not include scope when evaluating the performance of any software project. While considering the importance of scope and its ever-changing nature, it is imperative to measure the effect of changes in scope on the project plan. To analyse such effects, this study aims to enhance the traditional EVM by incorporating scope into it. The main objectives of this paper are: i) to extract the effects of project scope changes, ii) to map extracted effects of project scope changes with Software Project Scope Rating Index (SPSRI) elements, and iii) to quantify the extracted effects and integrate them with EVM. An extensive literature review is conducted to achieve the first objective, which results in the seventeen unique effects; that were used to map with SPSRI elements. To forecast the variations in scope for a given project budget, Monte Carlo simulations were run on the top eight scope elements, whereas, the results were incorporated with EVM to identify the deviations between actual and projected values of scope's score and cost. Finally, the multivariate regression model was used to evaluate the influence of individual element on the overall estimated cost of the project. The correlation between the independent variables (SPSRI elements) and the dependent variable (overall cost) was calculated along with the valuation of each independent variable on the dependent variable. Moreover, the effects are statistically shown that independent variables have influenced the dependent variable. This technique could assist the project managers to forecast deviations in project scope earlier.

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Nowadays, location-based services are being widely popularized due to their massive usage in current and emerging technologies. These services are based on searching out areas of interest which are likely to be accessed by users. Despite helping users worldwide, Location Based Services (LBSs) Systems endanger users' privacy because a user must provide personal information in order to use the services. Users thus become easy prey for assailants to access their social and personal lives. This problem is a giant issue for contemporary technologies because they are increasingly being used with the passage of time. Many existing solutions have attempted to resolve the challenges, but they face some serious dilemmas regarding the preservation of privacy. In order to address the privacy challenges in LBS systems, in this paper we have introduced a new Hierarchy Based Location Privacy (HBLP) model that protects the user's privacy, including the user's query time and identity and location information. The proposed model protects the user's privacy by using pseudo identity exchange, an aggregation protocol, and the concepts of Forest User (FU), Tree User (TU), and Child Users (CU) with k-anonymity and t-closeness, which is a reasonable combination for privacy provision for a user's query time, identity, and location. In order to evaluate the privacy protection level, we implemented the HBLP model in a Riverbed (Opnet) simulation and compared the results with existing state-of-the-art privacy-provisioning methods. The results showed that HBLP protected all the privacy attributes when a user interacts with an LBS system. INDEX TERMS Location based services, user privacy, NTTP, point of interest.