Masters Programs

MS Computer Science

Program Educational Objectives

After 3-5 years of graduation, the graduates will be able to:

  • Apply the advanced computing knowledge for solving real-world problems in general and areas of national importance in particular.
  • Adopt innovative approaches and pursue career growth by engaging in higher studies and/or conducting research in computing.

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Advanced Computing Knowledge

An ability to apply advanced knowledge of computer science and related domains for the solution of complex computing problems.


Problem Analysis

An ability to identify, formulate, research literature, and analyze complex computing problems reaching substantiated conclusions.


Design/Developm ent of Solutions

An ability to design solutions for complex computing problems and develop systems, modules or algorithms that meet academic and industrial needs.



An ability to investigate complex computing problems in a methodical way including literature survey, design and conduct of experiments, analysis and interpretation of experimental data, and synthesis of information to derive valid conclusions.


First Semester

Code Course Title Credit Hours
 CSC-XXXX  Core Course-I  3
 CSC-XXXX  Core Course -II  3
 CSC-XXXX  Elective-I  3
 CSC-XXXX  Elective-II  3
 Total  12

Second Semester

Code Course Title Credit Hours
 CSC-XXXX  Core Course-III  3
 CSC-XXXX  Core Course –IV  3
 CSC-XXXX  Elective-III  3
 CSC-5071  Elective-IV (Research Methodology)  3
 Total 12

Third Semester

Code Course Title Credit Hours
CSC-6072  MS Thesis-I  3
 TEX-5078 Elective-V (Functional Textiles)  2
 Total  5

Fourth Semester

Code Course TitleCredit Hours
 CSC-6072  MS Thesis-II  3
 Total Credit Hours of Program 32
Registration in “MS Thesis - I” is allowed provided the student has:
a. Earned at least 18 credits
b. Passed the “Research Methodology” course; and
c. CGPA is equal to or more than 2.5
Core Courses for MS (Computer Science)
At least four courses must be taken from the following
CSC-XXX Advanced Analysis of Algorithms
CSC-XXX Advanced Operating Systems
CSC-XXX Theory of Programming Languages
CSC-XXX Theory of Automata – II
CSC-XXX Advanced Computer Architecture


Registration in “MS Thesis - I” is allowed provided the student has:


a.            Earned at least 18 credits

b.           Passed the “Research Methodology” course; and

c.            CGPA is equal to or more than 2.5  


Core Courses for MS (Computer Science)

At least four courses must be taken from the following

CSC-5071            Advanced Analysis of Algorithms

CSC-5072            Advanced Operating Systems

CSC-5073            Theory of Programming Languages

CSC-5076            Theory of Automata – II

CSC-5074            Advanced Computer Architecture

List of Elective Courses



Course Title

Credit Hours


Control Systems and Robotics 



Real Time Operating Systems 



Advanced Networking



Network Security



Topics in Computer Networking



Advanced Artificial Intelligence



Wireless Networks



Complex Networks



Web Mining



Advanced Compiler Design I



Advanced Compiler Design II



Advanced Machine Learning Techniques



Advanced Digital Image Processing



Big Data Analytics



Advanced Human Computer Interaction



Advanced Distributed Systems



Advance Simulation & Modeling



Research Methodology



Advanced Data Mining


(This list is not exhaustive and new courses can be added to this category at any time depending upon availability of the instructor)

Course Specifications

Advanced Computational Theory

Automata theory, formal languages, Turing machines, computability theory and reducibility, computational complexity, determinism, non-determinism, time hierarchy, space hierarchy, NP completeness, selected advanced topics.

Advanced Analysis of Algorithms

Advanced algorithm analysis including the introduction of formal techniques and the underlying mathematical theory. NP-completeness. Search Techniques. Randomized Algorithms. Heuristic and Approximation Algorithms. Topics include asymptotic analysis of upper and average complexity bounds using big-O, little-o, and theta notation. Fundamental algorithmic strategies (brute-force, greedy, divide-and- conquer, backtracking, branch-and-bound, pattern matching, and numerical approximations) are covered. Also included are standard graph and tree algorithms. Additional topics include standard complexity classes, time and space tradeoffs in algorithms, using recurrence relations to analyze recursive algorithms, non-computable functions, the halting problem, and the implications of non-computability. Algorithmic animation is used to reinforce theoretical results. Upon completion of the course, students should be able to explain the mathematical concepts used in describing the complexity of an algorithm, and select and apply algorithms appropriate to a particular situation.

Advanced Operating Systems

This course will cover Introduction to Characterization of Modern Operating Systems; file systems, memory management techniques, Process scheduling and resource management. In System Models architectural models, Inter process Communication, Issues of Security in Distributed Systems (Partial coverage), Distributed File System, Concurrency Control in Distributed Systems; Problems of Coordination and Agreement in Distributed Systems Replication, Advantages and requirements, Fault-tolerant services, Mobile and Ubiquitous Computing.

Digital Signal Processing

One- and N-dimensional signals and  systems, Sampling theorem, Discrete-time Fourier transform, discrete Fourier transform, fast Fourier transform, z-transforms,  stability  and  minimum  phase    signals/systems, Linear filtering of signal, Time domain, Difference equations and convolution, Impulse invariance, bilinear transform, FIR filter design, 2D filter design, Statistical signal processing, Stochastic signals, correlation functions and power density spectra, Optimal filtering, Wiener filters, Adaptive filters, LMS and array processing.

Parallel and Distributed Computing

Why use parallel and distributed systems?  Why not use them? Speedup and Amdahl’s Law, Hardware architectures, multiprocessors (shared memory), networks of workstations (distributed memory), clusters (latest variation). Software architectures, threads and shared memory, processes   and message passing, distributed shared memory (DSM), distributed shared data (DSD).   Possible research and project topics, Parallel Algorithms, Concurrency and synchronization, Data and work partitioning, Common parallelization strategies, Granularity, Load balancing, Examples, parallel search, parallel sorting, etc. Shared-Memory Programming, Threads, Pthreads, Locks and semaphores, Distributed-Memory Programming, Message Passing, MPI, PVM. Other Parallel Programming Systems, Distributed shared memory, Aurora, Scoped behaviour and abstract data types, Enterprise, Process templates. Research Topics.

Control Systems and Robotics

Review of classical control analysis methods. Nyquist stability criterion. Classical design using frequency domain methods, phase lead and lag controllers, PID   controllers. Relay auto tuning. Introduction to state space methods. State space models, state transformations, solution of the state equations. Controllability and observability.   Design using state feedback. LQR design, pole placement, use of observers. Introduction to robotics. Transducers, actuators and robot control.

Real Time Operating Systems

The principles of real-time and embedded systems inherent in many hardware platforms and applications being developed for engineering and science as well as for ubiquitous systems, including robotics and manufacturing, interactive and multimedia, immersive and omnipresent applications. Real-time and quality of service system principles, understand real-time operating systems and the resource management and quality of service issues that arise, and construct sample applications on representative platforms. Platforms range from handheld and mobile computers to media and real-time server systems. Platforms may also include specialized systems used in application- specific contexts, such as autonomous robotics, smart sensors, and others.

Advanced Networking

Review of basic concepts, The OSI Model, packet and circuit switching, network topology, ISDN.  The TCP/ IP protocol stack, IP, ARP, TCP and UDP, DNS, ICMP, Internet Addressing, Routing, IP Multicast, RSVP, Next Generation IP – Ipng, Wireless, Radio basics, Satellite Systems, WAP, current trends, Issues with wireless over TCP.  Congestion Control, Control vs. Avoidance. Algorithms, Congestion in the Internet. Mobile IP, Voice over IP (VoIP), VPNs, Network Security. Management, Quality of Service (QoS), network vs. Distributed systems management Protocols, web-based management.

 Network Security

Introduction, Cryptology and simple cryptosystems, Conventional encryption techniques, Stream and block ciphers, DES, More on Block Ciphers, The Advanced Encryption Standard. Confidentiality, Message authentication, Hash functions, Number theory and algorithm complexity, Public key Encryption. RSA and Discrete Logarithms, Elliptic curves, Digital signatures. Key management schemes, Identification schemes, Dial-up security. E-mail security, PGP, S-MIME, Kerberos and directory authentication. Emerging Internet security standards, SET, SSL and IPsec, VPNs, Firewalls, Viruses, Miscellaneous topics.

Topics in Computer Networking

This course offers an advanced introduction and research perspectives in the areas of switch/router architectures, scheduling for best-effort and guaranteed services, QoS mechanisms and architectures, web protocols and applications, network interface design, optical networking, and network economics. The course also includes a research project in computer networking involving literature survey, critical analysis, and finally, an original and novel research contribution. Typical topics can be listed below, Overview of packet switching networks and devices. Fundamentals of Internet Protocol (IP) networking. Route lookup algorithms. Router architecture and performance. Detailed operation of Internet routing protocols such as Open Shortest Path First (OSPF) and Border Gateway Protocol (BGP). Integrated and differentiated network service models. Traffic Engineering (TE) concepts and mechanisms including label assignment, label distribution, and constraint-based routing algorithms. Multi-protocol label switching and its generalization. Quality of service mechanisms for multimedia and real-time communications. TE-based routing and signaling protocols. Fundamentals of per-flow and aggregate scheduling algorithms. Application-level and network- level signaling protocols for data, voice, and video communications. Resource signaling and resource reservation protocols. Worst-case analysis for multimedia networking.

Network Administration

Through completion of this course, students will be able to plan, install, and configure a Web Server, manage, monitor, and optimize a Web Server, and design and implement a Web Site on the Web Server created.

Wireless Networks

This course covers fundamental techniques in design and operation of first, second, and third generation wireless networks, cellular systems, medium access techniques, radio propagation models, error control techniques, handoff, power control, common air protocols (AMPS, IS-95, IS-136, GSM, GPRS, EDGE, WCDMA, cdma2000, etc), radio resource and network management. As an example for the third generation air interfaces, WCDMA is discussed in detail since it is expected to have a large impact on future wireless networks. This course is intended for graduate students who have some background on computer networks.

Network Performance Evaluation

This is an advanced course in networks and protocols. Analytical, simulation and experimental methods should be used to evaluate and design networks and protocols. Investigate network management tools and techniques.

Theory of Programming Languages

Introduction and History, Syntax   and Semantics, Control Structures, Types, Logic Programming, Functional Programming and Lambda calculus, Concurrent and Distributed Programming, Dataflow, Object-Oriented Programming.

Advanced Compiler Design-I

An in-depth study of compiler backend design for high-performance architectures. Topics include control-flow and data-flow analysis, classical optimization, instruction scheduling, and register allocation. Advanced topics include memory hierarchy management, optimization for instruction-level parallelism, modulo scheduling, predicated and speculative execution. The class focus is processor- specific compilation techniques, thus familiarity with both computer architecture and compilers is recommended

Advanced Compiler Design-II

The course should consist of one or two major projects. Theoretical study should depend on the level of the first course Design I and the student needs.

Intelligent User Interfaces

The increasing complexity of software and the proliferation of information makes intelligent user interfaces increasingly important. The promise of interfaces that are knowledgeable, sensitive to our needs, agile, and genuinely useful has motivated research across the world to advance the state of the art and practice in user interfaces that exhibit intelligence. The text covers the topic well.

Multimedia Database

Introduction, Overview of Relational and Object- Relational Data Representations, Text/Document Databases, Multidimensional Data Structures, similarity- based search (spatial, image, audio), XML Databases, Temporal Data Models, Logical Frameworks.

Computer Vision

Concepts behind computer-based recognition and extraction of features from raster images. Applications of vision systems and their limitations. Overview of early, intermediate and high-level vision, Segmentation, region splitting and merging, quad tree structures for segmentation, mean and variance pyramids, computing the first and second derivatives of images using the isotropic, Sobel and Laplacian operators, grouping edge points into straight lines by means of the Hough transform, limitations of the Hough transform, parameterization of conic sections. Perceptual grouping, failure of the Hough transform, perceptual criteria, improved Hough transform with perceptual features, grouping line segments into curves. Overview of mammalian vision, experimental results of Hubel and Weisel, analogy to edge point detection and Hough transform, Relaxation labelling of images, detection of image features, grouping of contours and straight lines into higher order features such as vertices and facets. Depth measurement in images

Rich Internet Applications

This course covers the concept and technology evolution regarding the internet applications and the use of interface tools. Mainly, the course can focus on any one of the technologies of modern day, for example, macromedia’s FLASH. However, the course will use the concepts of data structures, object oriented programming, programming languages and the software design and engineering to develop projects of medium to large magnitude

Requirement Engineering

Definition of requirements engineering and role in system development, Fundamental concepts and activities of requirements engineering, Information elicitation techniques, Modeling scenarios Fundamentals of goal-oriented requirements engineering, Modeling behavioral goals, Modeling quality goals, Goal modeling heuristics, Object modeling for requirements engineering, Object modeling notations, Object modeling heuristics, Identifying objects from goals, Modeling use cases and state machines, Deriving operational requirements from goals, Requirements Specification, Requirements verification and validation Management of inconsistency and conflict, requirements engineering risks, the role of quality goals in the requirements selection process, Techniques for requirements evaluation, selection and prioritization, Requirements management, Requirements traceability and impact analysis.

Software System Architecture

Definition and overview  of software architecture, the architecture business cycle, Understanding and achieving quality attributes, Attribute-driven design, Documenting software architecture, Evaluating software architecture, Architecture reuse Life-cycle view of architecture design and analysis methods, The QAW, a method for eliciting critical quality attributes, such as availability, performance, security, interoperability, and modifiability, Architecture Driven Design, Evaluating a software architecture (ATAM, CBAM, ARID), Principles of sound  documentation, View types, styles, and views, Advanced concepts such as refinement, context diagrams, variability, software interfaces, and how to document interfaces, Documenting the behavior of software elements and software systems, Choosing relevant views, Building a documentation  package

Software System Quality

What Is Software Quality, Quality Assurance, Quality Engineering, Software Testing, Testing, Concepts, Issues, and Techniques, Test Activities, Management, and Automation, Coverage and Usage Testing Based on Checklists and Partitions, Input Domain Partitioning and Boundary Testing, Coverage and Usage Testing Based on Finite-State Machines and Markov Chains, Control Flow, Data Dependency, and Interaction Testing, Testing Techniques, Adaptation, Specialization, and Integration. Quality Assurance Beyond Testing, Defect Prevention and Process Improvement, Software Inspection, Formal Verification, Fault Tolerance and Failure Containment, Comparing Quality Assurance Techniques and Activities. Quantifiable Quality Improvement, Feedback Loop and Activities for Quantifiable Quality Improvement, Quality Models and Measurements, Defect Classification and Analysis, Risk Identification for Quantifiable Quality Improvement, Software Reliability Engineering. Sample labs and assignments, Use of automated testing tools, Testing of a wide variety of software, Application of a wide variety of testing techniques, Inspecting of software in teams, comparison and analysis of results.

Research Methodology

The students have to perform meta analyses of 25-30 research papers selected in current research topics in International Journals. Topic and papers will be selected with approval from the instructor. Conference papers are not allowed for review. Students have to read all such papers and prepare the analysis related to models, methods, findings and come up with what has been done related to selected area of research and research gaps if any are explicitly identified with future work.

Software Case Tools, Applications

The students will be appraised of, Case tools, techniques, CASE in software development process, Traditional CASE methodologies, Emerging CASE methodologies, OO Design, Specific CASE tools, specialized design tools, Managing CASE methodologies. As part of course, students will be assigned a real life problem for development through CASE tools.


  1. BS Computer Science / BS Information Technology / BS Software Engineering / M.Sc Computer Science / IT or 16 years  equivalent degree from HEC recognized university/institute with a minimum CGPA 2.00/4.00 or first division in annual system.
  2. The applicant must pass NTS/NTU-GAT (General) test with minimum 50/100 marks prior to apply (please see Test Banner for more information on main page of this website). 
  3. The applicant must not be already registered as a student in any other academic program in Pakistan or abroad.
  4. Result waiting applicants may apply for admission, however their merit will be finalized only on submission of final BS/M.Sc or equivalent official transcript or degree.
  5. Relevant Admission Committee will determine relevancy of terminal degree and decide deficiency course/s (if any) at the time of admission interview, the detail of which will be provided to the student in his/her admission letter/email.
  6. Deficiency course/s will be treated as non-credit and qualifying course/s for which student will also pay extra dues as per fee policy. Those course/s will neither be mentioned in student’s final transcript nor will be included for calculation of CGPA. However, the student may obtain his/her a separate transcript for completion of deficiency course/s.

Note: The student will submit his/her publication from his/her thesis research work and submit to his/her supervisor. Final defense will be held after the submitted publication of student will be notified as “Under Review” or “Under Consideration” by a journal. It will be compulsory for graduate student to include his/her Supervisor’s name in his/her publication.

Merit Criteria

Admission merit will be prepared according to the following criteria:

 BS or Equivalent  60% weightage
 NTS GAT (General)  30% weightage
 Interview  10% weightage


Fee Head1st 2nd3rd4th
Admission Fee (Once) 25000 - - -
Certificate Verification Fee (Once) 2000 - - -
University Security (Refundable) 5000 - - -
Red Crescent  Donation (Once) 100 - - -
University Card Fee (Once) 300 - - -
Degree Fee (Once) - - - 5000
Tuition Fee (Per Semester) 30,000 30,000 21,000 21,000
Library Fee (Per Semester) 3000 3000 3000 3000
Examination Fee (Per Semester) 3000 3000 3000 3000
Medical Fee (Per Semester) 2000 2000 2000 2000
Student Activity Fund (Per Semester) 2000 2000 2000 2000
Endowment Fund (Per Semester) 1000 1000 1000 1000
TOTAL 73,400 41,000 32,000 37,000