This document provides summaries of common digital forensics tools including grep/egrep, sort, awk, sed, uniq, date, and Windows findstr. It explains what each tool is used for and provides examples of basic usage and useful flags. The overall purpose is to serve as a quick reference guide for forensic analysts to help with computer investigations.
LZ77 and LZ78 are two lossless data compression algorithms that achieve compression by replacing repeated data with references to a single copy of that data (LZ77) or a built dictionary (LZ78). LZ77 uses length-distance pairs to encode matches while LZ78 outputs dictionary indices and new characters. Both algorithms form the basis of modern compression standards like DEFLATE, and were important milestones in data compression.
The document provides an interview questions and answers guide for C programming language. It includes questions on topics such as the definition of C language, differences between functions like printf and sprintf, static variables, unions, linked lists, storage classes in C, and hashing. For each question, it provides multiple detailed answers explaining concepts in C programming such as memory allocation, strings, pointers, macros and more.
Stay Tuned for the Video Presentation on this new Lossless Data Compressor founded by P. B. Alipour since 2009. Thesis report available at: http://www.bth.se/fou/cuppsats.nsf/bbb56322b274389dc1256608004f052b/d6e604432ce79795c125775c0078148a!OpenDocument
This is an introduction to python ppt. This PPT has basic information about python. This may be first-class to the learner. It describes the fundamentals of python from history to basic programming skills. It allows the learner to learn how to start coding in python
4Developers 2018: The turbulent road to byte-addressable storage support at t...PROIDEA
The advent of new persistent memory technologies that are extremely fast and accessible at the CPU level is an opportunity to rethink many of the assumptions that were made during the design of storage interfaces in programming languages and supporting libraries. Many of the currently employed solutions will need to be designed from scratch with the new paradigms in mind to achieve full benefit of using this type of memory. But radical changes are never easy, and this one is no exception. Many researchers and industry experts have been working on this topic for a long time, and here's what they came up with. This lecture will introduce the broader aspects of persistent memory and what is currently being done to enable existing operating systems and programming languages to support this new type of technology. It will focus on C++ related activities and discuss the standardization efforts currently planned for full native language support.
This document discusses various ways to handle command line parameters, create delays, and generate random numbers in C programs. It explains that command line parameters are stored in the Program Segment Prefix and copied into argv by startup code. It provides an example to retrieve parameters directly from the PSP. It also discusses using DOS interrupt 0x15 to create delays measured in microseconds, and using the rand() and srand() functions to generate pseudorandom numbers based on a seed value.
This document provides an introduction and overview to the Haskell programming language. It discusses Haskell's core concepts like pure functions, immutable data, static typing, and lazy evaluation. It also covers common Haskell tools and libraries, how to write simple Haskell programs, and how to compile and run Haskell code. The document uses examples and interactive sessions to demonstrate Haskell syntax and show how various language features work.
This document provides summaries of common digital forensics tools including grep/egrep, sort, awk, sed, uniq, date, and Windows findstr. It explains what each tool is used for and provides examples of basic usage and useful flags. The overall purpose is to serve as a quick reference guide for forensic analysts to help with computer investigations.
LZ77 and LZ78 are two lossless data compression algorithms that achieve compression by replacing repeated data with references to a single copy of that data (LZ77) or a built dictionary (LZ78). LZ77 uses length-distance pairs to encode matches while LZ78 outputs dictionary indices and new characters. Both algorithms form the basis of modern compression standards like DEFLATE, and were important milestones in data compression.
The document provides an interview questions and answers guide for C programming language. It includes questions on topics such as the definition of C language, differences between functions like printf and sprintf, static variables, unions, linked lists, storage classes in C, and hashing. For each question, it provides multiple detailed answers explaining concepts in C programming such as memory allocation, strings, pointers, macros and more.
Stay Tuned for the Video Presentation on this new Lossless Data Compressor founded by P. B. Alipour since 2009. Thesis report available at: http://www.bth.se/fou/cuppsats.nsf/bbb56322b274389dc1256608004f052b/d6e604432ce79795c125775c0078148a!OpenDocument
This is an introduction to python ppt. This PPT has basic information about python. This may be first-class to the learner. It describes the fundamentals of python from history to basic programming skills. It allows the learner to learn how to start coding in python
4Developers 2018: The turbulent road to byte-addressable storage support at t...PROIDEA
The advent of new persistent memory technologies that are extremely fast and accessible at the CPU level is an opportunity to rethink many of the assumptions that were made during the design of storage interfaces in programming languages and supporting libraries. Many of the currently employed solutions will need to be designed from scratch with the new paradigms in mind to achieve full benefit of using this type of memory. But radical changes are never easy, and this one is no exception. Many researchers and industry experts have been working on this topic for a long time, and here's what they came up with. This lecture will introduce the broader aspects of persistent memory and what is currently being done to enable existing operating systems and programming languages to support this new type of technology. It will focus on C++ related activities and discuss the standardization efforts currently planned for full native language support.
This document discusses various ways to handle command line parameters, create delays, and generate random numbers in C programs. It explains that command line parameters are stored in the Program Segment Prefix and copied into argv by startup code. It provides an example to retrieve parameters directly from the PSP. It also discusses using DOS interrupt 0x15 to create delays measured in microseconds, and using the rand() and srand() functions to generate pseudorandom numbers based on a seed value.
This document provides an introduction and overview to the Haskell programming language. It discusses Haskell's core concepts like pure functions, immutable data, static typing, and lazy evaluation. It also covers common Haskell tools and libraries, how to write simple Haskell programs, and how to compile and run Haskell code. The document uses examples and interactive sessions to demonstrate Haskell syntax and show how various language features work.
LZW is a lossless data compression algorithm that replaces repeated strings of characters with codes. It works by starting with a dictionary of single characters and building the dictionary as more data is encoded. Strings are replaced with codes which are output, and new strings are added to the dictionary. For decompression, the same dictionary is rebuilt from the codes to reconstruct the original data losslessly. LZW is particularly effective for text compression and was used widely in GIF images due to its good compression ratio and efficiency.
Pointers and arrays in memory.
Memory is just a long string of bytes addressed by locations. Variables are represented by their addresses. Programs can also deal with addresses via pointers. Pointers contain the address of the data they point to. Arrays are blocks of contiguous memory that can be accessed using indexes that calculate the address from the starting point. Functions use stack frames to manage local variables that are destroyed when the function exits.
The document discusses different data compression techniques, focusing on lossless dictionary-based compression algorithms like Lempel-Ziv (LZ). It explains how LZ algorithms like LZW work by building an adaptive dictionary during compression and decompression. The LZW algorithm is described through examples. Advantages of LZW include no need to explicitly transfer the dictionary and fast encoding/decoding through table lookups. Problems like running out of dictionary space are also addressed.
This document summarizes research on optimizing the LZ77 data compression algorithm. The researchers present a method to improve LZ77 compression by using variable triplet sizes instead of fixed sizes. Specifically, when the offset is equal to the match length, they represent it with a "doublet" of just length and next symbol, saving bits compared to the standard triplet representation. They show this optimization achieves higher compression ratios than the conventional LZ77 algorithm in experiments. The decoding process is made slightly more complex to identify doublets versus triplets but still allows decompressing the encoded data back to the original.
The document describes the LZW data compression algorithm. It begins with an introduction to data compression and the lossless LZW algorithm. It then explains the basic LZ78 algorithm and how LZW compression works using a dictionary-based approach to encode repeated data sequences. The encoding and decoding processes are described through examples. Applications and implementations of LZW are also discussed.
Deep Learning for Machine Translation: a paradigm shift - Alberto Massidda - ...Codemotion
In beginning there was the "rule based" machine translation, like Babelfish, that didn't work at all. Then came the Statistical Machine translation, powering the like of Google Translate, and all was good. Nowadays, it's all about Deep Learning and the Neural Machine Translation is the state of the art, with unmatched translation fluency. Let's dive into the internals of a Neural Machine Translation system, explaining the principles and the advantages over the past.
Presentation given at RSDA 2014, Naples, November 3 2014, co-located with ISSRE 2014. The full paper is at
http://www.researchgate.net/publication/265596185_Avoiding_Hardware_Aliasing_Verifying_RISC_Machine_and_Assembly_Code_for_Encrypted_Computing .
The document provides an introduction and tutorial to the Python programming language. It covers 13 chapters that introduce very basic Python concepts up to more advanced topics like classes and CGI programming. The chapters include variables, data types, operators, conditionals, functions, iteration, strings, collection data types, exception handling, modules, files, documentation, and classes. The document also notes several sources that were used to create the tutorial and provides example code snippets throughout to demonstrate the concepts discussed.
The document describes 7 homework problems involving recursion and trees:
1) Write a recursive method to print a number's binary representation.
2) Write a recursive method to print a number's representation in a given base.
3) Determine the order of traversing a sample tree in pre-order, post-order, and level-order.
4) Repeat problem 3 but with a different root node.
5) Calculate the maximum number of nodes in a 5-ary tree of a given height.
6) Determine the maximum and minimum height of a 5-ary tree with a given number of nodes.
7) Write a recursive method to list all links in a tree by recursively printing each node and
- The document discusses concurrent and parallel programming in Haskell, including the use of threads, MVars, and software transactional memory (STM).
- STM provides atomic execution of blocks of code, allowing failed transactions to automatically retry without race conditions or data corruption.
- Strategies can be used to evaluate expressions in parallel using different evaluation models like head normal form or weak head normal form.
- While functional programs may seem to have inherent parallelism, in practice extracting parallelism can be difficult due to data dependencies and irregular patterns of computation.
Study of the Subtyping Machine of Nominal Subtyping with VarianceOriRoth
This is a study of the computing power of the subtyping machine behind Kennedy and Pierce’s nominal subtyping with variance. We depict the lattice of fragments of Kennedy and Pierce’s type system and characterize their computing power in terms of regular, context-free, deterministic, and non-deterministic tree languages. Based on the theory, we present Treetop—a generator of C#implementations of subtyping machines. The software artifact constitutes the first feasible (yet POC) fluent API generator to support context-free API protocols in a decidable type system fragment.
- C is a commonly used language for embedded systems due to its portability, efficiency, and conciseness. It was developed in the late 1960s and early 1970s alongside Unix.
- C was designed for systems programming tasks like operating systems and compilers. It was influenced by its predecessors BCPL and B and is well-suited for direct hardware manipulation.
- C uses expressions, conditional and iterative statements, functions, and other constructs to provide a structured and portable way to write low-level systems code while avoiding the complexity of assembly.
This document discusses lexical analysis in compilers. It begins with an outline of the topics to be covered, including lexical analysis, regular expressions, finite state automata, and the process of converting regular expressions to deterministic finite automata (DFAs). It then provides more details on each phase of a compiler and the role of lexical analysis. Key aspects of lexical analysis like tokenizing source code and classifying tokens are explained. The document also covers implementation of regular expressions using non-deterministic finite automata (NFAs) and their conversion to equivalent DFAs using techniques like epsilon-closure and transition tables.
Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. The algorithm is simple to implement, and has the potential for very high throughput in hardware implementations.
It is the algorithm of the widely used Unix file compression utility compress, and is used in the GIF image format.
The document describes the LZ77 data compression algorithm. It uses a sliding window approach where the text is searched for matches within a search buffer. When a match is found, it is encoded as an offset and length rather than encoding the full text. This allows duplication or repetition within the text to be replaced with smaller and more efficient offset/length codes. An example is provided to demonstrate how the text "sir sid eastman easily teases sea sick seals" would be encoded using this approach.
The document describes implementing a rational number library (rational) that allows for exact computation with rational numbers. It provides a Rational class interface with functions like addition, subtraction, multiplication, and division of rational numbers. It also gives sample code and test cases to test the library functions. Students are tasked with completing the implementation of the Rational class and its member functions in the provided header and source code files.
This document discusses UNIX and shell programming concepts including here documents, built-in variables, if/else statements, while loops, and associative arrays. A here document uses I/O redirection to pass a command list to an interactive program. Built-in variables include FS, OFS, NF, and FILENAME. The if statement and while loop can be used for control flow. Associative arrays in awk use key-value pairs rather than treating indexes as integers.
The internet Business: Success stories, Business Models etc. - A talk at IIMARohit Varma
Talk by Rohit Varma, PGP '83 (IIMA alumnus) and founder & CEO, Interskale Digital Marketing and Consulting Pvt. Ltd. to 1st year PGP & ABM students of IIMA Ahmedabad on December 17th, 2015.
Ten things that i have learnt in my marketing career_Talk at AICAR Business S...Rohit Varma
The title pretty much describes it all. Marketing is a discipline with tremendous potential and its pursuit as a career very fulfilling i.e. rewarding. This talk at AICAR B-School draws on anecdotes from my two decades plus as a marketer.
LZW is a lossless data compression algorithm that replaces repeated strings of characters with codes. It works by starting with a dictionary of single characters and building the dictionary as more data is encoded. Strings are replaced with codes which are output, and new strings are added to the dictionary. For decompression, the same dictionary is rebuilt from the codes to reconstruct the original data losslessly. LZW is particularly effective for text compression and was used widely in GIF images due to its good compression ratio and efficiency.
Pointers and arrays in memory.
Memory is just a long string of bytes addressed by locations. Variables are represented by their addresses. Programs can also deal with addresses via pointers. Pointers contain the address of the data they point to. Arrays are blocks of contiguous memory that can be accessed using indexes that calculate the address from the starting point. Functions use stack frames to manage local variables that are destroyed when the function exits.
The document discusses different data compression techniques, focusing on lossless dictionary-based compression algorithms like Lempel-Ziv (LZ). It explains how LZ algorithms like LZW work by building an adaptive dictionary during compression and decompression. The LZW algorithm is described through examples. Advantages of LZW include no need to explicitly transfer the dictionary and fast encoding/decoding through table lookups. Problems like running out of dictionary space are also addressed.
This document summarizes research on optimizing the LZ77 data compression algorithm. The researchers present a method to improve LZ77 compression by using variable triplet sizes instead of fixed sizes. Specifically, when the offset is equal to the match length, they represent it with a "doublet" of just length and next symbol, saving bits compared to the standard triplet representation. They show this optimization achieves higher compression ratios than the conventional LZ77 algorithm in experiments. The decoding process is made slightly more complex to identify doublets versus triplets but still allows decompressing the encoded data back to the original.
The document describes the LZW data compression algorithm. It begins with an introduction to data compression and the lossless LZW algorithm. It then explains the basic LZ78 algorithm and how LZW compression works using a dictionary-based approach to encode repeated data sequences. The encoding and decoding processes are described through examples. Applications and implementations of LZW are also discussed.
Deep Learning for Machine Translation: a paradigm shift - Alberto Massidda - ...Codemotion
In beginning there was the "rule based" machine translation, like Babelfish, that didn't work at all. Then came the Statistical Machine translation, powering the like of Google Translate, and all was good. Nowadays, it's all about Deep Learning and the Neural Machine Translation is the state of the art, with unmatched translation fluency. Let's dive into the internals of a Neural Machine Translation system, explaining the principles and the advantages over the past.
Presentation given at RSDA 2014, Naples, November 3 2014, co-located with ISSRE 2014. The full paper is at
http://www.researchgate.net/publication/265596185_Avoiding_Hardware_Aliasing_Verifying_RISC_Machine_and_Assembly_Code_for_Encrypted_Computing .
The document provides an introduction and tutorial to the Python programming language. It covers 13 chapters that introduce very basic Python concepts up to more advanced topics like classes and CGI programming. The chapters include variables, data types, operators, conditionals, functions, iteration, strings, collection data types, exception handling, modules, files, documentation, and classes. The document also notes several sources that were used to create the tutorial and provides example code snippets throughout to demonstrate the concepts discussed.
The document describes 7 homework problems involving recursion and trees:
1) Write a recursive method to print a number's binary representation.
2) Write a recursive method to print a number's representation in a given base.
3) Determine the order of traversing a sample tree in pre-order, post-order, and level-order.
4) Repeat problem 3 but with a different root node.
5) Calculate the maximum number of nodes in a 5-ary tree of a given height.
6) Determine the maximum and minimum height of a 5-ary tree with a given number of nodes.
7) Write a recursive method to list all links in a tree by recursively printing each node and
- The document discusses concurrent and parallel programming in Haskell, including the use of threads, MVars, and software transactional memory (STM).
- STM provides atomic execution of blocks of code, allowing failed transactions to automatically retry without race conditions or data corruption.
- Strategies can be used to evaluate expressions in parallel using different evaluation models like head normal form or weak head normal form.
- While functional programs may seem to have inherent parallelism, in practice extracting parallelism can be difficult due to data dependencies and irregular patterns of computation.
Study of the Subtyping Machine of Nominal Subtyping with VarianceOriRoth
This is a study of the computing power of the subtyping machine behind Kennedy and Pierce’s nominal subtyping with variance. We depict the lattice of fragments of Kennedy and Pierce’s type system and characterize their computing power in terms of regular, context-free, deterministic, and non-deterministic tree languages. Based on the theory, we present Treetop—a generator of C#implementations of subtyping machines. The software artifact constitutes the first feasible (yet POC) fluent API generator to support context-free API protocols in a decidable type system fragment.
- C is a commonly used language for embedded systems due to its portability, efficiency, and conciseness. It was developed in the late 1960s and early 1970s alongside Unix.
- C was designed for systems programming tasks like operating systems and compilers. It was influenced by its predecessors BCPL and B and is well-suited for direct hardware manipulation.
- C uses expressions, conditional and iterative statements, functions, and other constructs to provide a structured and portable way to write low-level systems code while avoiding the complexity of assembly.
This document discusses lexical analysis in compilers. It begins with an outline of the topics to be covered, including lexical analysis, regular expressions, finite state automata, and the process of converting regular expressions to deterministic finite automata (DFAs). It then provides more details on each phase of a compiler and the role of lexical analysis. Key aspects of lexical analysis like tokenizing source code and classifying tokens are explained. The document also covers implementation of regular expressions using non-deterministic finite automata (NFAs) and their conversion to equivalent DFAs using techniques like epsilon-closure and transition tables.
Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. The algorithm is simple to implement, and has the potential for very high throughput in hardware implementations.
It is the algorithm of the widely used Unix file compression utility compress, and is used in the GIF image format.
The document describes the LZ77 data compression algorithm. It uses a sliding window approach where the text is searched for matches within a search buffer. When a match is found, it is encoded as an offset and length rather than encoding the full text. This allows duplication or repetition within the text to be replaced with smaller and more efficient offset/length codes. An example is provided to demonstrate how the text "sir sid eastman easily teases sea sick seals" would be encoded using this approach.
The document describes implementing a rational number library (rational) that allows for exact computation with rational numbers. It provides a Rational class interface with functions like addition, subtraction, multiplication, and division of rational numbers. It also gives sample code and test cases to test the library functions. Students are tasked with completing the implementation of the Rational class and its member functions in the provided header and source code files.
This document discusses UNIX and shell programming concepts including here documents, built-in variables, if/else statements, while loops, and associative arrays. A here document uses I/O redirection to pass a command list to an interactive program. Built-in variables include FS, OFS, NF, and FILENAME. The if statement and while loop can be used for control flow. Associative arrays in awk use key-value pairs rather than treating indexes as integers.
The internet Business: Success stories, Business Models etc. - A talk at IIMARohit Varma
Talk by Rohit Varma, PGP '83 (IIMA alumnus) and founder & CEO, Interskale Digital Marketing and Consulting Pvt. Ltd. to 1st year PGP & ABM students of IIMA Ahmedabad on December 17th, 2015.
Ten things that i have learnt in my marketing career_Talk at AICAR Business S...Rohit Varma
The title pretty much describes it all. Marketing is a discipline with tremendous potential and its pursuit as a career very fulfilling i.e. rewarding. This talk at AICAR B-School draws on anecdotes from my two decades plus as a marketer.
The Guide provides Series 1 TiVos
and other PVR devices with TV
guide data for both FTA and Pay TV
stations. The content is created and
maintained by the community.
Better branding is a function of uncovering and executing what really matters.What really matters are features that result in both a relevant and differentiated brand.
Learnings from handling social media products for the indian market an intern...Rohit Varma
Rohit Varma discusses lessons learned from handling social media products for the Indian market. He outlines that to succeed with social media, brands must achieve trust (T), reach (R) among an interested audience, encourage content contribution (C), and possibly leverage mobile apps (K). Specifically, Varma notes that restricted access built trust for networks like Orkut; reaching existing customers is key; and making content creation simple can boost user participation in India.
This document discusses the reconstruction of the earliest versions of the UNIX operating system from 1971. It describes how researchers were able to restore the source code and get a version of the 1st Edition UNIX kernel running on a simulated PDP-11/20 computer by fixing errors and gaps in the original documentation and source code. It also discusses the challenges involved in software restoration when documentation is incomplete or the environment is missing and important lessons learned for preserving old software systems.
The evolution of the Internet and it's impact on print and other media_IDC_II...Rohit Varma
A talk to the Masters in Design students at IIT Bombay. The brief was to sensitize these students on the impact the Internet is making on print and traditional media. Made in 2009.
Ten things that are happening around us and ten ways India's students batch o...Rohit Varma
This fun, 'moonshot' talk takes a 30,000 feet view of where the world is headed and an MBA student's place in it. Talk delivered to 2nd year students at AICAR Business School, Neral, near Mumbai, in 2009.
Steven Marks has over 30 years of experience in semiconductor and solar cell manufacturing. He has a strong background in process engineering and statistical process control. Some of his key strengths include problem solving, teamwork, communication skills, and a proven work ethic. He is seeking a position that allows him to utilize his extensive experience in manufacturing and process integration.
Social networking learnings & opportunities web innovation conference, bangal...Rohit Varma
A presentation I made at The Web Innovation conference in 2007. Based largely on my experience as CEO of Indian social networking startup Yo4ya.com. I take a shot at describing what sorts of social networks can succeed.
This document outlines the 3GPP specifications process for developing new mobile network systems and features. It follows a three stage process:
Stage 1 defines service requirements. Stage 2 defines the network architecture, elements, and high-level flows. Stage 3 defines protocols, state machines, and messages.
This process was applied to developing LTE, where Stage 1 documents defined requirements like throughput rates and latency. Stage 2 documents described the overall LTE system architecture. Numerous Stage 3 specifications then defined the protocols that enable LTE.
LTE uses symmetric key cryptography with algorithms like AES and Snow 3G for encryption and integrity protection. During attachment, the UE and MME perform mutual authentication using the AKA protocol and derive session keys from which encryption and integrity keys are obtained for NAS and AS security. The UE and eNB then negotiate the specific algorithms to use for ciphering and integrity protection of signaling and user data.
The document discusses the differences between strcpy and memcpy functions in C. Strcpy copies bytes from a source string to a destination string until it reaches the null terminator, while memcpy copies a specified number of bytes between any types of data. It also provides examples of removing trailing spaces from a string and using switch statements instead of multiple else-if statements.
This document discusses parsing methods and techniques for high performance computing. It covers the following key points in 3 sentences:
The document outlines the various phases of compiler design including lexical analysis, syntax analysis, semantic analysis, code generation, and optimization. It then discusses parsing in more detail, describing lexical analysis as the first phase that interacts with source code to generate tokens, and syntax analysis/parsing as taking tokens to build parse trees according to grammar rules. The document also covers different parsing techniques like top-down and bottom-up parsing, and issues around implementing parallel parsing such as dividing code, synchronization, processor allocation, threading, task distribution, and context switching.
The document contains interview questions and answers related to the C programming language. It discusses topics such as what C language is, the printf and malloc functions, static and dynamic memory allocation, pointers, arrays, and modular programming. The document provides detailed explanations of concepts in C and is intended to help prepare for a C language interview.
The document contains interview questions and answers related to the C programming language. It discusses the definition of C language and its uses. It also provides explanations and comparisons of common C functions like printf(), malloc(), calloc(), sprintf(), and static variables. Additional questions cover topics such as reducing executable size, checking for circular linked lists, the union data type, differences between strings and character arrays, hashing, and determining memory allocation size.
The document contains interview questions and answers related to the C programming language. It discusses topics such as what C language is, the printf and malloc functions, static and dynamic memory allocation, pointers, arrays, and modular programming. The document provides detailed explanations of concepts in C and is intended to help prepare for a C language interview.
Like most imperative languages in the ALGOL tradition, C has facilities for structured programming and allows lexical variable scope and recursion, while a static type system prevents many unintended operations. In C, all executable code is contained within subroutines, which are called "functions" (although not in the strict sense of functional programming). Function parameters are always passed by value. Pass-by-reference is simulated in C by explicitly passing pointer values. C program source text is free-format, using the semicolon as a statement terminator and curly braces for grouping blocks of statements.
Counting and sorting are basic tasks that distributed systems rely on. The document discusses different approaches for distributed counting and sorting, including software combining trees, counting networks, and sorting networks. Counting networks like bitonic and periodic networks have depth of O(log2w) where w is the network width. Sorting networks can sort in the same time complexity by exploiting an isomorphism between counting and sorting networks. Sample sorting is also discussed as a way to sort large datasets across multiple threads.
This document discusses regular expressions (regexes) in Perl programming. It provides three examples that demonstrate extracting date values from a string using different regex techniques. It then discusses some key regex concepts like quantifiers, grouping, anchors, character classes and more. Code examples are provided to illustrate each concept. The goal is to help readers better understand how to leverage the powerful regex engine in Perl to perform complex text matching and manipulation tasks.
"Clone detection in Python": Slides presented at EuroPython 2012
Clone Detection in Python highlights the topic of code duplication detection using Machine Learning techniques.
Some examples on Python code duplications and C-Python implementation duplications are reported as well.
Faster persistent data structures through hashingJohan Tibell
This document discusses using hashing to create faster persistent data structures. It summarizes an implementation of persistent hash maps in Haskell using Patricia trees and sparse arrays. Benchmark results show this approach is faster than traditional size balanced trees for string keys. The document also explores a Haskell implementation of Clojure's hash-array mapped tries, which provide even better performance than the hash map approach. Several ideas for further optimization are presented.
Regular expressions are a powerful tool for searching, matching, and parsing text patterns. They allow complex text patterns to be matched with a standardized syntax. All modern programming languages include regular expression libraries. Regular expressions can be used to search strings, replace parts of strings, split strings, and find all occurrences of a pattern in a string. They are useful for tasks like validating formats, parsing text, and finding/replacing text. This document provides examples of common regular expression patterns and methods for using regular expressions in Python.
This document discusses syntax analysis and parsing. It introduces context-free grammars and how they are used to specify the syntax of programming languages. There are two main types of parsing: top-down parsing which builds the parse tree from the root going down, and bottom-up parsing which builds up the tree from the leaves to the root. Specific parsing algorithms like recursive descent and LR parsing are also introduced.
The document discusses block ciphers and the Data Encryption Standard (DES). It begins by explaining the differences between block ciphers and stream ciphers. It then covers the principles of Feistel ciphers and their structure, using DES as a specific example. DES encryption, decryption, and key scheduling are described. The document also discusses attacks on DES like differential and linear cryptanalysis. It concludes by covering modern block cipher design principles.
Block ciphers like DES encrypt data in blocks and are based on the Feistel cipher structure. DES encrypts 64-bit blocks using a 56-bit key and 16 rounds of encryption. Modern cryptanalysis techniques like differential and linear cryptanalysis use statistical analysis to reveal weaknesses in block ciphers, though DES remains relatively secure against these attacks. Careful design of block ciphers, including aspects like non-linear substitution boxes and complex key scheduling, aims to provide security against cryptanalysis.
These slides contain an introduction to Symbolic execution and an introduction to KLEE.
I made this for a small demo/intro for my research group's meeting.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
ADAM is an open source platform for scalable genomic analysis that defines a data schema, Scala API, and command line interface. It uses Apache Spark for efficient parallel and distributed processing of large genomic datasets stored in Parquet format. Key features of ADAM include its ability to perform iterative analysis on whole genome datasets while minimizing data movement through Spark. The document also describes using ADAM and PacMin for long read assembly through techniques like minhashing for fast read overlapping and building consensus sequences on read graphs.
This document provides an overview of Huffman codes, which are a type of variable-length encoding that assigns binary codewords to characters based on their frequency. It explains that Huffman codes are constructed by building a binary tree from the character frequencies, with the most frequent at the top and least at the bottom. The codewords are then generated by tracing a path from the root to each leaf node. This allows more frequent characters to have shorter codewords, compressing the data size. An example of constructing a Huffman code tree from character counts in a sample text is also given.
In this talk I will discuss how to deduplicate large amounts of source code using the source{d} stack, and more specifically the Apollo project. The 3 steps of the process used in Apollo will be detailed, ie: - the feature extraction step; - the hashing step; - the connected component and community detection step; I'll then go on describing some of the results found from applying Apollo to Public Git Archive, as well as the issues I faced and how these issues could have been somewhat avoided. The talk will be concluded by discussing Gemini, the production-ready sibling project to Apollo, and imagining applications that could extract value from Apollo.
After a quick introduction on the motivation behind Apollo, as said in the abstract I'll describe each step of Apollo's process. As a rule of thumb I'll first describe it formally, then go into how we did it in practice.
Feature extraction: I'll describe code representation, specifically as UASTs, then from there detail the features used. This will allow me to differentiate Apollo from it's inspiration, DejaVu, and talk about code clones taxonomy a bit. TF-IDF will also be touched upon. Hashing: I'll describe the basic Minhashing algorithm, then the improvements Sergey Ioffe's variant brought. I'll justify it's use in our case simultaneously. Connected components/Community detection: I'll describe the connected components and community notion's first (as in in graphs), then talk about the different ways we can extract them from the similarity graph.
After this I'll talk about the issues I had applying Apollo to PGA due to the amount of data, and how I went around the major issued faced. Then I'll go on talking about the results, show some of the communities, and explain in light of these results how issues could have been avoided, and the whole process improved. Finally I'll talk about Gemini, and outline some of the applications that could be imagined to Source code Deduplication.
The document defines different phases of a compiler and describes Lexical Analysis in detail. It discusses:
1) A compiler converts a high-level language to machine language through front-end and back-end phases including Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization and Code Generation.
2) Lexical Analysis scans the source code and groups characters into tokens by removing whitespace and comments. It identifies tokens like identifiers, keywords, operators etc.
3) A lexical analyzer generator like Lex takes a program written in the Lex language and produces a C program that acts as a lexical analyzer.
Similar to Ctcompare: Comparing Multiple Code Trees for Similarity (20)
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Overview
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12. Jupyter Notebooks with Code Examples
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Ctcompare: Comparing Multiple Code Trees for Similarity
1. Ctcompare:
Comparing Multiple Code
Trees for Similarity
Warren Toomey
School of IT, Bond University
Using lexical analysis with
techniques borrowed from DNA
sequencing, multiple code trees can
be quickly compared to find any
code similarities
2. Why Write a Code
Comparison Tool?
To detect student plagiarism
●
To determine if your codebase is
●
`infected' by proprietary code from
elsewhere, or by open-source code
covered by a license like the GPL
To trace code genealogy between trees
●
separated by time (e.g. versions), useful
for the new field of computing history
3. Code Comparison Issues
Can rearrangement of code be
●
detected?
- per line? per sub-line?
● Can “munging of code” be detected?
- variable/function/struct renaming?
● What if one or both codebases are
proprietary? How can third parties verify
any comparison?
● Can a timely comparison be done?
● What is the rate of false positives?
- of missed matches?
4. Lexical Comparison
First version: break the source code
●
from each tree into lexical tokens, then
compare runs of tokens between trees.
● This removes all the code's semantics,
but does deal with code rearrangement
(but not code “munging”).
5. Performance of Lexical
Approach
Performance was O(M*N), when M and N
●
the # of tokens in each code tree
Basically: slow, and exponential
●
I also wanted to compare multiple code
●
trees, and also find duplicated code
within a tree
6. When is Copying
Significant?
Common code fragments not significant:
●
13 tokens
for (i=0; i< val; i++)
10 tokens
if (x > max) max=x;
err= stat(file, &sb); if (err) 14 tokens
Axiom: runs of < 16 tokens insignificant
●
Idea: use a run of 16 tokens as a lookup
●
key to find other trees with the same run
of tokens
7. Approach in Second
Version
Take all 16-tokens runs in a code tree
●
● Use each as a key, and insert the runs
into a database along with position of
the run in the source tree
● Keys (i.e. runs of 16 tokens) with
multiple values indicate possible code
copying of at least 16 tokens
● For these keys, we can evaluate all code
trees from this point on to find any real
code similarity
9. Algorithm
for each key in the database with multiple record nodes {
obtain the set of record nodes from the database;
for each combination of node pairs Na and Nb {
if (performing a cross-tree comparison)
skip this combination if Na and Nb in the same tree;
if (performing a code clone comparison)
skip this combination if Na and Nb in the same file;
perform a full token comparison beginning at Na and Nb to
determine the full extent of the code similarity, i.e. determine
the actual number of tokens in common;
add the matching token sequence to a list of quot;potential runsquot;;
}
}
walk the list of potential runs to merge overlapping runs, and
remove runs which are subsets of larger runs;
output the details of the actual matching token runs found.
10. Hashing Identifiers and
Literals in Each Code Tree
Simply comparing tokens yields false
●
positives, e.g
if (xx > yy) { aa = 2 * bb + cc; }
if (ab > bc) {ab = 5 * ab + bc; }
I hash each identifier and literal down to
●
a 16-bit value
This obfuscates the original values while
●
minimising the amount of false positives
11. Isomorphic Comparison
Hashing identifiers helps to ensure code
●
similarities are found
● Does not help if variables have been
renamed
● This can be solved with isomorphic
comparison: keep a 2-way variable
isomorphism table
● Code is isomorphic when variable
names are isomorphic across a long run
of code
12. Isomorphic Example
int maxofthree(int x, int y, int z)
{
if ((x>y) && (x>z)) return(x);
if (y>z) return(y);
return(z);
}
int bigtriple(int b, int a, int c)
{
if ((b>a) && (b>c)) return(b);
if (a>c) return(a);
return(c);
}
13. Bottlenecks
In the second version, main bottleneck
●
is the merging of overlapping code
fragments which have been found to
match between two trees
● Similar to the problem with DNA
sequencing when genes are split up into
multiple fragments before sequencing
● Use of AVL trees here has helped to
reduce the cost of merging immensely
● Other more mundane optimisations
such as mmap() have also helped
14. Current Performance
54 seconds to compare 14 trees of code
●
totalling 1 million lines of C code
15. Results
Many lines of code written at UNSW in
●
late 1970s still present in System V, and
in Open Solaris
● Thousands of lines of replicated code
inside Linux kernel
● AT&T vs BSDi lawsuit in early 1990s:
- expert witness found 56 common lines
in 230K lines between BSD and Unix
- my tool find roughly same lines, plus
100+ more isomorphic similarities