Empirical Models

Duration: 5 min

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Module outline

  1. English Comprehension/Verbal Ability: Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Vocabulary, Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Subject Verb Agreement (Verb Noun Agreement), Tenses, Verb, Articles, Preposition, Conjunction, Pronoun, Noun, Adjectives, Adverb, Modals, Cloze Test (Cloze Passage), Active Passive Voice (Voice), Direct and Indirect Speech, Sentence Construction
  2. Logical Ability: Coding Decoding, Directions (Direction Test), Analogy, Inequality, Data Sufficiency, Series (Number and Letter Series) (Numerical Relations and Reasoning), Syllogisms, Seating Arrangements, Puzzle Solving (Puzzles), Blood Relations, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Ranking, Order and Sequence, Logical Sequence Of Words, Data Arrangement, Venn Diagram, Calendar, Clock
  3. Quantitative Ability: Logarithm, Permutation and Combination, Probability, Profit and Loss, Speed Time and Distance, Mixture and Alligation, Partnership, Simple Interest and Compound Interest, Percentage, Ratio and Proportion (Ratios), Average, Time and Work, Pipe and Cistern, Number System, Divisibility Rules, HCF LCM, Algebra, Powers and Exponents (Surds and Indices), Mensuration and Geometry, Age Problems, Data Interpretation, Sequence and Series (Series)
  4. Basic Analytical Ability: Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Analytical Reasoning (Counting Figures Reasoning), Cubes & Dices, Selection Decision Table (Decision Making)
  5. Computer Programming: Pseudo Codes, Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir
  6. DBMS (Computer Science): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Transaction Management, Concurrency Control, Database Security & Authorization
  7. SQL (Computer Science): SQL
  8. OS (Computer Science): Introduction to OS, Process Management, CPU Scheduling, Deadlock, Process Synchronization, Threads & Process Creation, Memory Management, Virtual Memory, File Management
  9. Computer Networks (Computer Science): Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security
  10. Data Structures (Computer Science): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  11. OOPs (Computer Science): Object Oriented Programming (OOPS)
  12. Software Engineering (Computer Science): Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  13. SVAR Conversational - Spoken English: Communication Assessment
  14. HR Interview: MR & HR Interview Preparation
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video provides a lecture on software estimation models, specifically focusing on empirical models and the COCOMO (Construction Cost Model) framework. The presentation begins by defining empirical models as estimation techniques that use formulas derived from historical data, based on metrics like Lines of Code (LOC) or Function Points (FP). It then introduces the COCOMO model, developed by Barry Boehm in 1981, as the most widely used and universally accepted regression-based estimation technique. The lecture details the three primary software classes defined by COCOMO: Organic (application), Semidetached (utility), and Embedded (system), explaining that classification is based on product and team characteristics. The video concludes by presenting a worked example, writing the formula 'E = 100 pm' on the screen, which represents the effort (E) in person-months for a project, illustrating the application of the model.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video opens with a title card for 'SOFTWARE ENGINEERING' from 'Knowledge Gate'. The lecture begins by defining 'Empirical models' as estimation models that use empirically derived formulas for predicting based on LOC or FP. The instructor explains that different authors provide different mathematical formulas for these models. The slide states that out of all COCOMO models, the most versatile and universally accepted one is being discussed. The instructor, visible in a small window, begins to explain the concept, and the text 'E = 100 pm' is written on the screen, representing a formula for effort estimation.

  2. 2:00 – 4:49 02:00-04:49

    The lecture transitions to the COCOMO (1981) model, which is described as the most widely used estimating technique. The instructor explains it is a regression-based model developed by Barry Boehm, which postulates three important classes of software. The slide lists these as Organic (application), Semidetached (utility), and Embedded (system). The instructor elaborates on the classification criteria, stating that product characteristics and development team characteristics are considered. Examples are given: data processing and scientific programs are applications, while compilers and linkers are utilities. The slide also mentions that the relative complexity of these three categories is in the ratio 1:3:9 for application, utility, and system programs, respectively. The instructor continues to explain the model's application, with the 'E = 100 pm' formula remaining visible on the screen as a key example.

The video presents a structured lesson on software cost estimation, progressing from the general concept of empirical models to the specific, widely-accepted COCOMO framework. It establishes the foundational idea that estimation relies on formulas derived from past data, then narrows the focus to COCOMO as the premier model. The core of the lesson is the classification of software into three distinct types—Organic, Semidetached, and Embedded—based on their complexity and development context. This classification is crucial for applying the COCOMO model correctly, as it dictates the parameters used in the estimation formula, which is exemplified by the 'E = 100 pm' equation. The synthesis of these concepts provides a clear methodology for estimating software project effort.

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