cyclomatic complecity.pptx
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Cyclomatic complexity of a code section is the quantitative measure of the number of linearly independent paths in it. It is a software metric used to indicate the complexity of a program. It is computed using the Control Flow Graph of the program. The nodes in the graph indicate the smallest group of commands of a program, and a directed edge in it connects the two nodes i.e. if second command might immediately follow the first command.
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How to calculte Cyclomatic Complexity through various methods
A brief description about cyclomatic complexity is given.Various methods along with an example is described to calculate it. Advantages and disadvantages are also mentioned.
Cyclomatic complexity
Detail about cyclomatic complexity, formula to measure cyclomatic complexity and how this metric useful in software testing and uses of cyclomatic complexity etc.
A WHITE BOX TESTING TECHNIQUE IN SOFTWARE TESTING : BASIS PATH TESTING
Software Testing is the emerging and important field of IT industry because without the concept of software testing, there is no quality software which is produced in the industry. Verification and Validation are the two basic building blocks of software testing process. There are various testing tactics, strategies and methodologies to test the software. Path Testing is one such a methodology used to test the software. Basically, path testing is a type of White Box/ Glass Box/ Open Box/ Structural testing technique. It generates the test suite based on the number of independent paths that are presented in a program by drawing the Control Flow Graph of an application. The basic objective of this paper is to acquire the knowledge on the basis path testing by considering a sample of code and the implementation of path testing is described with its merits and demerits.
7-White Box Testing.ppt
White box testing involves close examination of a program's internal structure and logic flows. Test cases are designed to exercise specific conditions and loops by following logical paths through the code. This ensures all independent paths, logical decisions, loops, and internal data structures are tested. Basis path testing is a white box technique that uses flow graphs and cyclomatic complexity to identify the minimum number of test cases needed to guarantee every statement is executed at least once. Cyclomatic complexity represents the number of independent paths in a program and is used to derive a basis set of test cases that force execution of every path.
Calculation of Cyclomatic complexity
This document summarizes a session on software engineering that covered basis path testing and cyclomatic complexity. It defines basis path testing as designing test cases to execute all linearly independent paths in a program based on its control flow graph (CFG). The CFG describes the program's control flow and can be constructed by representing statements as nodes and control transfers as edges. Cyclomatic complexity provides a way to determine the maximum number of independent paths and required test cases. It is calculated based on the number of edges and nodes in the CFG or bounded areas in the graph. The document outlines three methods for computing cyclomatic complexity from the graph properties.
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White box testing involves testing internal paths, logic, and calculations of a program. It helps ensure data processing and calculations are correct by testing all paths and lines of code through techniques like path coverage and line coverage. McCabe's cyclomatic complexity metrics measure the number of independent paths in a program to help determine test coverage needs. Software qualification and reusability testing check if code and documentation meet standards to help with maintenance, reuse, and developing new software using existing code. While white box testing helps improve quality, it also has higher costs since it requires an experienced tester with knowledge of the internal program structure.
Control Flow Testing
Control flow testing is a white box testing technique that uses the program's control flow graph to design test cases that execute different paths through the code. It involves creating a control flow graph from the source code, defining a coverage target like branches or paths, generating test cases to cover the target, and executing the test cases to analyze results. It is useful for finding bugs in program logic but does not test for missing or extra requirements.
Fault Modeling for Verilog Register Transfer Level
As the complexity of Very Large Scale Integration
(VLSI) increases, testing becomes tedious. Currently fault
models are used to test digital circuits at gate level or at levels
lower than gate. Modeling faults at these levels, leads to
increase in the design cycle time period. Hence, there is a
need to explore new approaches for modeling faults at higher
levels. This paper proposes fault modeling at the Register
Transfer Level (RTL) for digital circuits. Using this level of
modeling, results are obtained for fault coverage, area and
test patterns. A software prototype, FEVER, has been developed
in C which reads a RTL description and generates two output
files: one a modified RTL with test features and two a file
consisting of set of test patterns. These modified RTL and test
patterns are further used for fault simulation and fault
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and Gate level modeling for ISCAS benchmarks and the
results of the same are presented. Results are obtained using
Synopsys, TetraMax and it is shown that it is possible to achieve
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How to calculte Cyclomatic Complexity through various methods
A brief description about cyclomatic complexity is given.Various methods along with an example is described to calculate it. Advantages and disadvantages are also mentioned.
Cyclomatic complexity
Detail about cyclomatic complexity, formula to measure cyclomatic complexity and how this metric useful in software testing and uses of cyclomatic complexity etc.
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This document summarizes a session on software engineering that covered basis path testing and cyclomatic complexity. It defines basis path testing as designing test cases to execute all linearly independent paths in a program based on its control flow graph (CFG). The CFG describes the program's control flow and can be constructed by representing statements as nodes and control transfers as edges. Cyclomatic complexity provides a way to determine the maximum number of independent paths and required test cases. It is calculated based on the number of edges and nodes in the CFG or bounded areas in the graph. The document outlines three methods for computing cyclomatic complexity from the graph properties.
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Control Flow Testing
Control flow testing is a white box testing technique that uses the program's control flow graph to design test cases that execute different paths through the code. It involves creating a control flow graph from the source code, defining a coverage target like branches or paths, generating test cases to cover the target, and executing the test cases to analyze results. It is useful for finding bugs in program logic but does not test for missing or extra requirements.
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As the complexity of Very Large Scale Integration
(VLSI) increases, testing becomes tedious. Currently fault
models are used to test digital circuits at gate level or at levels
lower than gate. Modeling faults at these levels, leads to
increase in the design cycle time period. Hence, there is a
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modeling, results are obtained for fault coverage, area and
test patterns. A software prototype, FEVER, has been developed
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1. Basis path testing is a white-box testing technique that aims to design test cases to execute all independent paths in a program. It uses control flow graphs and cyclomatic complexity metrics to determine the minimum number of tests required.
2. Key steps include drawing a control flow graph, calculating cyclomatic complexity to determine the number of independent paths, identifying a basis set of paths, and generating test cases to execute each path. This helps reduce redundant testing and maximize code coverage.
3. The document also discusses other software testing techniques like condition testing, data flow testing, loop testing, equivalence partitioning, and path testing. It provides details on the objectives, principles, and processes involved in each technique.
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As the complexity of Very Large Scale Integration (VLSI) is growing, testing becomes tedious and tougher. As of now fault models are used to test digital circuits at the gate level or below that level. By using fault models at the lower levels, testing becomes cumbersome and will lead to delays in the design cycle. In addition, developments in deep submicron technology provide an opening to new defects. We must develop efficient fault detection and location methods in order to reduce manufacturing costs and time to market. Thus there is a need to look for a new approach of testing the circuits at higher levels to speed up the design cycle. This paper proposes on Register Transfer Level (RTL) modeling for digital circuits and computing the fault coverage. The result obtained through this work establishes that the fault coverage with the RTL fault model is comparable to the gate level fault coverage.
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growing set of gate-level simulation (GLS) applications including design for test (DFT) and lowpower considerations. As a result, in order to complete the verification requirements on time,
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and for the simulator to be run in high-performance mode. This application note describes
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growing set of gate-level simulation (GLS) applications including design for test (DFT) and lowpower considerations. As a result, in order to complete the verification requirements on time,
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The Farmers (Empowerment and Protection) Agreement on Price Assurance and Farm Services Act, 2020 is an act of the Indian Government that creates a national framework for contract farming through an agreement between a farmer and a buyer before the production or rearing of any farm produces.
Data Frames and Scatterplots in R language ujjwal matoliya.pptx
In the section on exploring Q→Q relationships, you loaded a “data frame” called h
A data frame is R’s representation of a table
Columns and rows can have names
Each column can contain data of a different type
E.g. some columns might be numerical data, and some might be categorical
Categorical variables in R are called factors
By contrast, a matrix is a table in which all the data are the same type
Add layers to a ggplot2 plot by adding layers to the plot, using the various geom_xxx functions
To create a scatterplot, use geom_point(): ggplot(h2, aes(x=height, y=weight)) + geom_point()
To color the points, simply use the color parameter: ggplot(h2, aes(x=height, y=weight)) + geom_point(aes(color=gender))
To specify the colors, use scale_color_manual(): ggplot(h2, aes(x=height, y=weight)) + geom_point(aes(color=gender)) + scale_color_manual(values=c("blue","red"))
The ggplot2 package provides functionality for more sophisticated plots
Install the package, if you haven’t already install.packages(“ggplot2”)
Load the library library(“ggplot2”)
Let’s just fix the gender column: h2 <- h h2$gender <- ifelse(h2$gender==1, “Female”, “Male”)
Start a plot with the ggplot(…) function, specifying the data to use and the aesthetics, which can include a mapping to the x-axis and y-axis: ggplot(h2, aes(x=height, y=weight))
This just creates a blank plot
Floyd’s and Warshal’s Algorithm ujjwal matoliya.pptx
The Floyd Warshall algorithm is for solving the All Pairs Shortest Path problem. The problem is to find shortest distances between every pair of vertices in a given edge weighted directed Graph.
Floyd-Warshall Algorithm is an algorithm for solving All Pairs shortest path problem which gives the shortest path between every pair of vertices of the given graph.
Floyd-Warshall Algorithm is an example of dynamic programming.
The main advantage of Floyd-Warshall Algorithm is that it is extremely simple and easy to implement.
Floyd-Warshall Algorithm is best suited for dense graphs since its complexity depends only on the number of vertices in the graph.
For sparse graphs, Johnson’s Algorithm is more suitable.
congestion ujjwal matoliya.pptx
What is congestion?
A state occurring in network layer when the message traffic is so heavy that it slows down network response time.
Effects of Congestion
As delay increases, performance decreases.
If delay increases, retransmission occurs, making situation worse.
Global Attributes Window Event Attributes Form Events Ujjwal matoliya.pptx
HTML global attributes are those attributes which are common for all HTML elements. The global attributes are supported by both standard and non-standard element.
The global attributes can be used with all elements, although it may not have any effect on some elements.
The accesskey attribute specifies a shortcut key to activate/focus an element.
The accesskey attribute value must be a single character (a letter or a digit).
The class attribute specifies one or more class names for an element.
The class attribute is mostly used to point to a class in a style sheet. However, it can also be used by a JavaScript (via the HTML DOM) to make changes to HTML elements with a specified class.
Instruction format UJJWAL MATOLIYA.pptx
3 bit is used for opcode part. Memory reference instruction uses 12 bit for addressing part. 1 bit for addressing mode. For direct address most significant bit is set to zero and for indirect address MSB is set to one
Zero address instructions
One address instructions
Two address instructions
Three address instructions
IT does not use any address field in the computational instruction
ADD and MUL instruction don’t use any address field of the stack (set of memory location); however, address field is necessary for PUSH and POP instruction
THE instruction with one address format use only one address field.
IT use accumulator (AC) register for all types of data manipulation
THE instructions with two address format uses two address fields.
Each address field can specify a register or a memory location.
example are: ADD, MOV , CMP, BIS etc.
The various formats for specifying operand are called addressing modes.
Immediate/Implied addressing mode
Register addressing mode
Register Indirect
Auto Increment / Auto decrement
Direct addressing mode
Indirect addressing mode
Relative addressing mode
Index addressing mode
Immediate/Implied addressing mode
Register addressing mode
Register Indirect
Auto Increment / Auto decrement
Direct addressing mode
Indirect addressing mode
Relative addressing mode
Index addressing mode
Base Register addressing mode
javascript function ujjwal matoliya.pptx
A function is a group of reusable code which can be called anywhere in your program. This eliminates the need of writing the same code again and again. It helps programmers in writing modular codes. Functions allow a programmer to divide a big program into a number of small and manageable functions.
The most common way to define a function in JavaScript is by using the function keyword, followed by a unique function name, a list of parameters (that might be empty), and a statement block surrounded by curly braces.
A JavaScript function can have an optional return statement. This is required if you want to return a value from a function. This statement should be the last statement in a function.
In the above program, variable x is used to store the function. Here the function is treated as an expression. And the function is called using the variable name.
The function above is called an anonymous function.
string functions in SQL ujjwal matoliya.pptx
SQL string functions are used primarily for string manipulation.
The initcap() function converts the first letter of each word in a string to upper case, and converts any remaining characters in each word to lowercase.
Query: SELECT initcap(ename) FROM employee;
* LCASE () is a synonym for LOWER ().
* Returns the string str with all characters changed to lowercase according to the current character set mapping.
Example1: SELECT lower(ename) from employee ;
Returns the length of the string str measured in bytes. A multi-byte character counts as multiple bytes. This means that for a string containing five two-byte characters,
LENGTH() returns 10, whereas CHAR_LENGTH() returns 5.
Query: SELECT LENGTH('ename') from employee ;
Returns the string str with all remstr prefixes or suffixes removed. If none of the specifiers BOTH, LEADING, or TRAILING is given, BOTH is assumed. remstr is optional and, if not specified, spaces are removed.
Example: SELECT TRIM(‘ reena ') from dual;
jdbc Java Database Connectivity ujjwal matoliya jdbc.pptx
JDBC stands for Java Database Connectivity. JDBC is a Java API to connect and execute the query with the database. It is a part of JavaSE (Java Standard Edition). JDBC API uses JDBC drivers to connect with the database
Before JDBC, ODBC API was the database API to connect and execute the query with the database. But, ODBC API uses ODBC driver which is written in C language (i.e. platform dependent and unsecured). That is why Java has defined its own API (JDBC API) that uses JDBC drivers (written in Java language).
We can use JDBC API to handle database using Java program and can perform the following activities:
Connect to the database
Execute queries and update statements to the database
Retrieve the result received from the database.
compiler design ujjwal matoliya 2nd sem MCA.pptx
The document discusses syntax directed translation (SDT). It defines SDT as grammar plus semantic rules. It provides examples of using SDT for arithmetic expressions, infix to postfix conversion, and generating intermediate code. It also discusses how to evaluate an SDT using a top-down and bottom-up approach. Finally, it defines the differences between synthesized and inherited attributes, and S-attributed and L-attributed SDT.
3 address code ujjwal matoliya.pptx
Intermediate code can translate the source program into the machine program. Intermediate code is generated because the compiler can’t generate machine code directly in one pass. Therefore, first, it converts the source program into intermediate code, which performs efficient generation of machine code further. The intermediate code can be represented in the form of postfix notation, syntax tree, directed acyclic graph, three address codes, Quadruples, and triples.
Three address code
Three-address code is an intermediate code. It is used by the optimizing compilers.
In three-address code, the given expression is broken down into several separate instructions. These instructions can easily translate into assembly language.
Each Three address code instruction has at most three operands. It is a combination of assignment and a binary operator.
Three address code is used in compiler applications:
Optimization: Three address code is often used as an intermediate representation of code during optimization phases of the compilation process. The three address code allows the compiler to analyze the code and perform optimizations that can improve the performance of the generated code.
Code generation: Three address code can also be used as an intermediate representation of code during the code generation phase of the compilation process. The three address code allows the compiler to generate code that is specific to the target platform, while also ensuring that the generated code is correct and efficient.
Debugging: Three address code can be helpful in debugging the code generated by the compiler. Since three address code is a low-level language, it is often easier to read and understand than the final generated code.
2-3 tree ujjwal matoliya .pptx
It stand for multi-way search tree
Multi-way search trees are a generalized version of binary trees
That allow for efficient data searching and sorting
In contrast to binary search trees, which can only have two children per node
Multi-way search trees can have multiple children per node
2-3 Trees
2-3 trees are the data structure same as trees, but it has some different properties like any node can have either single value or double value. So, there are two types of nodes in 2-3 trees:
Search:
If T is empty, return False (key cannot be found in the tree).
If current node contains data value which is equal to K, return True.
If we reach the leaf-node and it doesn’t contain the required key value K, return False.
Recursive Calls:
If K < currentNode.leftVal, we explore the left subtree of the current node.
Else if currentNode.leftVal < K < currentNode.rightVal, we explore the middle subtree of the current node.
Else if K > currentNode.rightVal, we explore the right subtree of the current node.
Insertion:
There are 3 possible cases in insertion which have been discussed below:
Case 1: Insert in a node with only one data element
Case 2: Insert in a node with two data elements whose parent contains only one data element.
Case 3: Insert in a node with two data elements whose parent also contains two data elements.
Deletion
To delete a value, it is replaced by its in-order successor and then removed.
If a node is left with less than one data value then two nodes must be merged together.
If a node becomes empty after deleting a value, it is then merged with another node.
Graph in Discrete mathemaetics.pptx
A graph G = (V, E) consists of a set of vertices V = { V1, V2, . . . } and set of edges E = { E1, E2, . . . }. The set of unordered pairs of distinct vertices whose elements are called edges of graph G such that each edge is identified with an unordered pair (Vi, Vj) of vertices. The vertices (Vi, Vj) are said to be adjacent if there is an edge Ek which is associated to Vi and Vj. In such a case Vi and Vj are called end points and the edge Ek is said to be connect/joint of Vi and Vj.
Quick Sort in data structure.pptx
Quick Sort is one of the different Sorting Technique which is based on the concept of Divide and Conquer, just like merge sort. But in quick sort all the heavy lifting(major work) is done while dividing the array into sub arrays , while in case of merge sort, all the real work happens during merging the sub arrays . In case of quick sort, the combine step does absolutely nothing.
Hadoop With R language.pptx
Hadoop is an open-source framework which was founded by the ASF - Apache Software Foundation. It is used to store process and analyze data that are huge in volume. Hadoop is written in Java, and it is not OLAP (Online Analytical Processing). It is used for batch/offline processing. It is being used by Facebook, Google, Twitter, Yahoo, LinkedIn, and many more. Moreover, it can be scaled up just by adding nodes in the cluster.R is an open-source programming language. It is best suited for statistical and graphical analysis. Also, if we need strong data analytics and visualization features, we have to combine R with Hadoop.
The purpose behind R and Hadoop integration:
To use Hadoop to execute R code.
To use R to access the data stored in Hadoop.
Hadoop Streaming is a utility that allows users to create and run jobs with any executable as the mapper and/or the reducer. Using the streaming system, we can develop working Hadoop jobs with just enough knowledge of Java to write two shell scripts which work in tandem.
LOGIC FAMILY.pptx
Digital logic family is a group of logic gates constructed using passive devices like a resistor, transistor, diodes, etc. Such devices have compatible logic levels and supply voltage with certain characteristics.According to the components used, there are different types of logic families. Some of the logic families include Resistor-Transistor logic(RTL), Diode-Transistor logic(DTL), Transistor-transistor logic(TTL), Emitter coupled logic(ECL), PMOS, NMOS, and CMOS circuits.
Transaction.pptx
The concurrency control is the process to maintain the data where there are multiple resources or users are accessing the data element and performing the database operations. There are several enterprise systems such as banking, ticket booking, and traffic light systems that use a shared database as part of the data store associated with concurrent transactions.
Congestion control algorithms.pptx
A state occurring in network layer when the message traffic is so heavy that it slows down network response time.
Effects of Congestion
As delay increases, performance decreases.
If delay increases, retransmission occurs, making situation worse.
computer graphic.pptx
This document summarizes different 2D transformations including translation, rotation, reflection, and shearing. It defines each transformation type and provides examples of applying them to geometric objects like lines, polygons, and circles. Rotation is described as changing an object's angle and can be clockwise or counterclockwise. Reflection produces a mirror image across an axis like the x-axis or y-axis. Shearing distorts an object's shape by sliding its layers in one or both axes. Examples are given of applying each transformation to triangles and calculating the new coordinates.
Game playing With AI.pptx
Game Playing is an important domain of artificial intelligence. Games don’t require much knowledge; the only knowledge we need to provide is the rules, legal moves and the conditions of winning or losing the game.
Both players try to win the game.
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cyclomatic complecity.pptx
- 1. Software Engineering Assignment :- Cyclomatic Complexity Submitted By Ujjwal matoliya
- 2. INDEX Cyclomatic complexity Use of Cyclomatic Complexity Advantages of Cyclomatic Complexity Disadvantages of Cyclomatic Complexity
- 3. Cyclomatic complexity of a code section is the quantitative measure of the number of linearly independent paths in it. It is a software metric used to indicate the complexity of a program. It is computed using the Control Flow Graph of the program. The nodes in the graph indicate the smallest group of commands of a program, and a directed edge in it connects the two nodes i.e. if second command might immediately follow the first command. Cyclomatic complexity
- 4. 1 2 3 6 4 5 7 8 11 9 10 Example –flow chat
- 6. V(G) = E – N + 2 where, E = the number of edges in the control flow graph N = the number of nodes in the control flow graph Cyclomatic complexity V(G) V(G) = E(11) – N(9) + 2 = 4
- 7. No. of regions = 4 V(G)= No. of predicate nodes +1 = 3+1 =4
- 8. Use of Cyclomatic Complexity: Determining the independent path executions thus proven to be very helpful for Developers and Testers. It can make sure that every path have been tested at least once. Thus help to focus more on uncovered paths. Code coverage can be improved. Risk associated with program can be evaluated.
- 9. Advantages of Cyclomatic Complexity: It can be used as a quality metric, gives relative complexity of various designs. It is able to compute faster than the Halstead’s metrics. It is used to measure the minimum effort and best areas of concentration for testing. It is able to guide the testing process. It is easy to apply.
- 10. Disadvantages of Cyclomatic Complexity: It is the measure of the programs’s control complexity and not the data the data complexity. In this, nested conditional structures are harder to understand than non-nested structures. In case of simple comparisons and decision structures, it may give a misleading figure.