ÌÇÐÄvlog

Biography

Dr. Anu is the Associate Director of the School of Computing (SoC) and an Associate Professor of Computer Science at ÌÇÐÄvlog. Dr. Anu joined Montclair State in Fall 2018. Before joining Montclair State, he received a PhD in Software Engineering from North Dakota State University. Dr. Anu's research interests include software engineering, human error in software engineering, empirical software engineering, computer science education (CSED), and human factors in cybersecurity. Dr. Anu's recent work is funded by NSF and NJDOE and focuses on supporting K-12 teachers in developing a standards-aligned, high-quality K-12 computer science program. The primary goal of this research effort is to increase the number of K-12 educators who are well-prepared to teach high-quality, standards-based computer science courses to K-12 students. 

Undergraduate Courses Taught at ÌÇÐÄvlog: 
# CSIT 416 - IT Project Management  
# CSIT 315 - Software Engineering I 
# CSIT 415 - Software Engineering II
# CSIT 104 - Python Programming I
# CSIT 460 - Computer Security

Graduate Courses Taught at ÌÇÐÄvlog: 
# CSIT 590 - Cyberspace Governance, Policy, and Ethics
# CSIT 555 - Database Systems
# CSIT 610 - IT Project Management 
# CSIT 615 - Advanced Topics in Software Engineering

Undergraduate Courses Taught at North Dakota State University: 
# CSCI 116 - Business Use of Computers (Sessions: SP10, FA10, SP11)

Research

Dr. Vaibhav Anu's research expertise lies in the areas of software engineering, software quality, and the human factors that shape how software is designed, developed, and secured. His interdisciplinary research examines how human cognitive errors, biases, and decision-making during software development can lead to defects, poor requirements, and security vulnerabilities—and how better engineering practices can prevent those problems. His work brings together software engineering, cognitive psychology, empirical research, and artificial intelligence to develop and evaluate practical approaches for improving software quality. A central focus of his research is software verification and validation, including requirements and design inspections, human-error-based approaches to identifying software defects, and the use of machine learning and data mining to analyze software requirements, inspection reports, and security vulnerability data. His research has produced tools, taxonomies, empirical methods, and evidence-based practices aimed at helping developers identify not only software defects, but also the human errors that cause them.

Dr. Anu's research products include a widely cited Human Error Taxonomy for Software Requirements, which provides a systematic framework for understanding the cognitive errors that contribute to problems in software requirements, as well as empirical studies examining how human-error information can improve requirements inspections and defect prevention. His work has also extended this human-centered perspective to cybersecurity, including research on programmer-induced vulnerabilities and the use of software metrics to predict vulnerable components. More recent research examines software design errors and the use of machine learning and natural-language processing for software requirements and security. His scholarship has also received recognition in computer science education, including an Exemplary CS Educational Research Paper Award at SIGCSE, and his current work extends into computer science education and interdisciplinary STEM education, including efforts supported by NSF and the New Jersey Department of Education.

Dr. Anu is also an experienced educator who connects research with practical computing education. At ÌÇÐÄvlog, he has taught undergraduate and graduate courses spanning software engineering, IT project management, Python programming, computer security, database systems, cybersecurity governance and ethics, and advanced software engineering. His teaching and research emphasize preparing students not simply to build software, but to understand the processes, human factors, security considerations, and management decisions that determine whether software is reliable, usable, and secure.

Program Highlight: CS for Everyone Everywhere (CSEE) Program

The ÌÇÐÄvlog CS for Everyone Everywhere (CSEE) Program supports participating Local Educational Agency (LEA) representatives in developing a standards-aligned, high-quality K-12 computer science program. This project is funded by NJ DOE (NJDOE Standards 22E00178). Weblink:

 

Publications

Selected Journal Publications, Listed in Reverse Chronological Order:

1. Agrawal, T., Walia, G. S., & Anu, V. (2024). Development of a software design error taxonomy: A systematic literature review. SN Computer Science, 5(5), 467.
2. Dave, D., Celestino, A., Varde, A.S, & Anu, V., "Management of Implicit Requirements Data in Large SRS Documents: Taxonomy and Techniques, " ACM SIGMOD Record, vol. 51, no. 2, pp. 18–29, July 2022.
3. Anu, V., "Information Security Governance Metrics: A Survey and Taxonomy," Information Security Journal: A Global Perspective, vol 31, issue 4, pp. 466-478, published online: May 2021.
4. Sultana, K.Z., Anu, V., and Chong, T.*, "Using Software Metrics for Predicting Vulnerable Classes and Methods in Java Projects: A Machine Learning Approach," Journal of Software: Evolution and Process (JSEP), vol 33(3), e2303.
5. Anu, V., Hu, W., Carver, J., Walia, G., and Bradshaw, G. "Development of a Human Error Taxonomy for Software Requirements: A Systematic Literature Review", Elsevier Information and Software Technology (IST) Journal, vol 103, pp. 112–124. November 2018.

Selected Conference Proceedings, Listed in Reverse Chronological Order:

1. Williams-Nash, A. S., Hagiwara, S., Herbert, K. G., Marlowe, T. J., Goldstein, R. A., & Anu, V. (2025, February). Preparing K-8 Teachers to Teach and Infuse Computer Science Across All Subjects. In Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1 (pp. 1232-1238).
2. Agrawal, T., Walia, G. S., & Anu, V. (2025). Insights from an Industry Survey on Software Design Errors. In SEKE (pp. 348-353).
3. Anu, V., Sultana, K.Z., and Samanthula, B.K., "A Human Error Based Approach to Understanding Programmer-Induced Software Vulnerabilities," 2020 IEEE International Symposium on Software Reliability Engineering Workshops (IEEE ISSRE), Coimbra, Portugal. October 12-15, 2020.
4. Anu, V., Walia, G., Hu, W., and Carver, J., Bradshaw, G. "Issues and Opportunities for Human Error-based Requirements Inspections: An Exploratory Study", 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2017).
5. Anu, V., Walia, G., and Bradshaw, G. "Incorporating Human Error Education into Software Engineering Courses via Error-based Inspections", 48th ACM Technical Symposium on Computer Science Education (SIGCSE 2017). Seattle, Washington, USA. March 8 – 11, 2017.

For a complete list of Dr. Anu's publications, please visit the links below:

• Google Scholar Profile:
• ORCID: