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Software requirement artifacts such as manuals request for proposals, and software requirements specification (SRS) are commonly focused on functional requirements. In most SRS files, nonfunctional requirements do not formally encoded or encoded as a whole, not for an individual design problem. Moreover, these nonfunctional requirements are intermingled with functional requirements. Therefore, these nonfunctional requirements need special attention to understand for successful project development. These nonfunctional requirements have an impact on each other and optimal tradeoff is required for balanced nonfunctional requirements set. NFRs have a negative and positive tradeoff with each other such as increase confidentiality, decrease the availability, and enhance authenticity. So, an optimum tradeoff among these design problem within a module is required to have better design decisions. Instead of considering all nonfunctional requirements, the NFRs that have mutual tradeoff is considered. In this paper, we devised a novel document annotation scheme for SRS and extracted nonfunctional requirements from these annotated artifacts. In the next step, we classified NFRs into two classes security triad and performance triad, and the cost is assumed constant for each NFR. From the design problem, the tradeoff ratio is calculated among NFRs associated with it. Then, the production possibility graph is plotted to estimate the optimum tradeoff ratio within the module. For estimation economic optimum from a set of NFR, iso-cost graphs by assuming the constant cost. Some hypothetical variations in cost are also examined using 3D iso-cost graph. The reason to measure these tradeoff is to make design decision more empirical and helpful for the selection of design patterns, especially secure design patterns.

Islamophobia is a sentiment against the Muslim community; recently, atrocities towards Muslim communities witnessed this sentiment globally. This research investigates the correlation between how news stories covered by mainstream news channels impede the hate speech/Islamophobic sentiment. To examine the objective mentioned above, we shortlisted thirteen mainstream news channels and the ten most widely reported Islamophobic incidents across the globe for experimentation. Transcripts of the news stories are scraped along with their comments, likes, dislikes, and recommended videos as the users’ responses. We used a word embedding technique for sentiment analysis, e.g., Islamophobic or not, three textual variables, video titles, video transcripts, and comments. This sentiment analysis helped to compute metric variables. The I-score represents the extent of portrayals of Muslims in a particular news story. The next step is to calculate the canonical correlation between video transcripts and their respective responses, explaining the relationship between news portrayal and hate speech. This study provides empirical evidence of how news stories can promote Islamophobic sentiments and eventually atrocities towards Muslim communities. It also provides the implicit impact of reporting news stories that may impact hate speech and crime against specific communities.