Generation of Test Cases for Identification of Crime against Women through HLR and VLR

Hemant Kumar *

Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow, Uttar Pradesh, 226025, India.

Rishi Shukla

Department of Law, Ram Manohar Lohia National Law University, Lucknow, Uttar Pradesh, 226012, India.

Prem Kumar Gautam

Department of Law, Ram Manohar Lohia National Law University, Lucknow, Uttar Pradesh, 226012, India.

Manjusha Tiwari

Department of Law, Ram Manohar Lohia National Law University, Lucknow, Uttar Pradesh, 226012, India.

Vipin Saxena

Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow, Uttar Pradesh, 226025, India.

*Author to whom correspondence should be addressed.


Abstract

In recent years, it is observed that crimes against women are increasing exponentially growth manner and the nature of the crime may be sexual harassment at any place including the workplace, acid attack at any place, rape, domestic violence, and many more which the criminal may leave his location treated as visitor location for performing criminal activities against the women whose mobile is treated as a home location. In the present work, a criminal scene is established through the mathematical technique for matching these two locations for identification of the crime. From the literature, it is observed that mathematical matching techniques are not in use for the identification of crime. The purpose of the present work is to fill this gap by developing a Unified Model by the use of Unified Modeling Language which has been validated through valid test cases after implementing the model in the Python programming language.

Keywords: Crime, women, criminal, VLR, HLR and matching technique


How to Cite

Kumar , Hemant, Rishi Shukla, Prem Kumar Gautam, Manjusha Tiwari, and Vipin Saxena. 2023. “Generation of Test Cases for Identification of Crime Against Women through HLR and VLR”. Journal of Advances in Mathematics and Computer Science 38 (12):50-59. https://doi.org/10.9734/jamcs/2023/v38i121857.

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