Research Methodology in CS

CSEG3060 · Course Content Delivery Plan · Autumn Semester 2026 (04 Aug – 02 Dec 2026)

L-T-P: 3-0-0 Credits: 3 6 Units 45 Contact Hours CIA 50% · Mid 20% · End 30%
Home Assignments Course Plan Delivery Plan (Excel)

Course Objectives

  1. Familiarize students with research problem identification.
  2. Introduce various research methodologies in computing science.
  3. Promote ethical conduct in research.
  4. Enhance technical writing and proposal development skills.
  5. Provide insights into intellectual property and patents.

Course Outcomes

  • CO1: Identify and formulate research problems using defined criteria and characteristics.
  • CO2: Utilize various investigative approaches and methodologies for problem-solving in computing science research.
  • CO3: Demonstrate ethical conduct and awareness of research ethics and plagiarism.
  • CO4: Produce technically sound, well-structured research reports and proposals.
  • CO5: Analyze and apply knowledge of intellectual property rights, particularly patents, in computing science.

Course Content Delivery Plan

Pick your section to see your own dates, timings and venues. Slides are linked against each lecture as they are delivered.

 

The calendar yields 43 teaching slots for CCVT and 44 for Full Stack AI after Independence Day, the Mid-Semester examination week (assumed 21–26 Sep), Gandhi Jayanti, Dussehra, the Diwali break (assumed 04–10 Nov) and Guru Nanak Jayanti. Closely related topics are therefore merged so that every syllabus item is still covered. Units II and III are delivered in an activity-led format and complete by 30 September — Unit II in seven sessions (13 syllabus hours) and Unit III in four (8 syllabus hours) — which brings Class Test 1 forward to 12 September and Quiz 2 to the last September slot. The slots this frees are held as reserved sessions in November, to be allocated to revision, project clinics or extended coverage. Dates marked as assumptions should be confirmed against the official UPES academic calendar.

Textbooks

  1. Stuart Melville & Wayne Goddard, Research Methodology: An Introduction for Science & Engineering Students.
  2. R. Ganesan, Research Methodology for Engineers, MJP Publishers.

Reference Books

  • Steven Skiena, The Algorithm Design Manual, Springer.

Evaluation

  • Continuous Internal Assessment — 50% (ten components × 10 marks)
  • Mid-Semester Examination — 20%
  • End-Semester Examination — 30%