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kietnv / VireaderMachine Reading Comprehension has attracted significant interest in research on natural language understanding, and large-scale datasets and neural network-based methods have been developed for this task. However, most developments of resources and methods in machine reading comprehension have been investigated using two resource-rich languages, English and Chinese. This article proposes a system called ViReader for open-domain machine reading comprehension in Vietnamese by using Wikipedia as the textual knowledge source, where the answer to any particular question is a textual span derived directly from texts on Vietnamese Wikipedia. Our system combines a sentence retriever component, based on techniques of information retrieval to extract the relevant sentences, with a transfer learning-based answer extractor trained to predict answers based on Wikipedia texts. Experiments on multiple datasets for machine reading comprehension in Vietnamese and other languages demonstrate that (1) our ViReader system is highly competitive with prevalent machine learning-based systems, and (2) multi-task learning by using a combination consisting of the sentence retriever and answer extractor is an end-to-end reading comprehension system. The sentence retriever component of our proposed system retrieves the sentences that are most likely to provide the answer response to the given question. The transfer learning-based answer extractor then reads the document from which the sentences have been retrieved, predicts the answer, and returns it to the user. The ViReader system achieves new state-of-the-art performances, with values of 70.83% EM (exact match) and 89.54% F1, outperforming the BERT-based system by 11.55% and 9.54%, respectively. It also obtains state-of-the-art performance on UIT-ViNewsQA (another Vietnamese dataset consisting of online health-domain news) and BiPaR (a bilingual dataset on English and Chinese novel texts). Compared with the BERT-based system, our system achieves significant improvements (in terms of F1) with 7.65% for English and 6.13% for Chinese on the BiPaR dataset. Furthermore, we build a ViReader application programming interface that programmers can employ in Artificial Intelligence applications.
fazeelkhalid / Graph Real Time ProblemsPoints: 100 Topics: Graphs, topological sort, freedom to decide how to represent data and organize code (while still reading in a graph and performing topological sort) PLAGIARISM/COLLUSION: You should not read any code (solution) that directly solves this problem (e.g. implements DFS, topological sorting or other component needed for the homework). The graph representation provided on the Code page (which you are allowed to use in your solution) and the pseudocode and algorithm discussed in class provide all the information needed. If anything is unclear in the provided materials check with us. You can read materials on how to read from a file, or read a Unix file or how to tokenize a line of code, BUT not in a sample code that deals with graphs or this specific problem. E.g. you can read tutorials about these topics, but not a solution to this problem (or a problem very similar to it). You should not share your code with any classmate or read another classmate's code. Part 1: Main program requirements (100 pts) Given a list of courses and their prerequisites, compute the order in which courses must be taken so that when taking a courses, all its prerequisites have already been taken. All the files that the program would read from are in Unix format (they have the Unix EOL). Provided files: ● Grading Criteria ● cycle0.txt ● data0.txt ● data0_rev.txt ● data1.txt - like data0.txt but the order of the prerequisite courses is modified on line 2. ● slides.txt (graph image) - courses given in such a way that they produce the same graph as in the image. (The last digit in the course number is the same as the vertex corresponding to it in the drawn graph. You can also see this in the vertex-to-course name correspondence in the sample run for this file.) ● run.html● data0_easy.txt - If you cannot handle the above file format, this is an easier file format that you can use, but there will be 15 points lost in this case. More details about this situation are given in Part 3. ● Unix.zip - zipped folder with all data files. ● For your reference: EOL_Mac_Unix_Windows.png - EOL symbols for Unix/Mac/Windows Specifications: 1. You can use structs, macros, typedef. 2. All the code must be in C (not C++, or any other language) 3. Global or static variables are NOT allowed. The exception is using macros to define constants for the size limits (e.g. instead of using 30 for the max course name size). E.g. #define MAX_ARRAY_LENGTH 20 4. You can use static memory (on the frame stack) or dynamic memory. (Do not confuse static memory with static variables.) 5. The program must read from the user a filename. The filename (as given by the user) will include the extension, but NOT the path. E.g.: data0.txt 6. You can open and close the file however many times you want. 7. File format: 1. Unix file. It will have the Unix EOL (end-of-line). 2. Size limits: 1. The file name will be at most 30 characters. 2. A course name will be at most 30 characters 3. A line in the file will be at most 1000 characters. 3. The file ends with an empty new line. 4. Each line (except for the last empty line) has one or more course names. 5. Each course name is a single word (without any spaces). E.g. CSE1310 (with no space between CSE and 1310). 6. There is no empty space at the end of the line. 7. There is exactly one empty space between any two consecutive courses on the same line. (You do not need to worry about having tabs or more than one empty space between 2 courses.) The first course name on each line is the course being described and the following courses are the prerequisites for it. E.g. CSE2315 CSE1310 MATH1426 ENGL13018. The first line describes course CSE2315 and it indicates that CSE2315 has 2 prerequisite courses, namely: CSE1310 and MATH1426. The second line describes course ENG1301 and it indicates that ENG1301 has no prerequisites. 9. You can assume that there is exactly one line for every course, even for those that do not have prerequisites (see ENGL1301 above). Therefore you can count the number of lines in the file to get the total number of courses. 10.The courses are not given in any specific order in the file. 8. You must create a directed graph corresponding to the data in the file. 1. The graph will have as many vertices as different courses listed in the file. 2. You can represent the vertices and edges however you want. 3. You do NOT have to use a graph struct. If you can do all the work with just the 2D table (the adjacency matrix) that is fine. You HAVE TO implement the topological sorting covered in class (as this assignment is on Graphs), but you can organize, represent and store the data however you want. 4. For the edges, you can use either the adjacency matrix representation or the adjacency list. If you use the adjacency list, keep the nodes in the list sorted in increasing order. 5. For each course that has prerequisites, there is an edge, from each prerequisite to that course. Thus the direction of the edge indicates the dependency. The actual edge will be between the vertices in the graph corresponding to these courses. E.g. file data0.txt has: c100 c300 c200 c100 c200 c100 Meaning: c100-----> c200 \ | \ | \ | \ | \ | \ | V V c300(The above drawing is provided here to give a picture of how the data in the file should be interpreted and the graph that represents this data. Your program should *NOT* print this drawing. See the sample run for expected program output.) From this data you should create the correspondence: vertex 0 - c100 vertex 1 - c300 vertex 2 - c200 and you can represent the graph using adjacency matrix (the row and column indexes are provided for convenience): | 0 1 2 ----------------- 0| 0 1 1 1| 0 0 0 2| 0 1 0 e.g. E[0][1] is 1 because vertex 0 corresponds to c100 and vertex 1 corresponds to c300 and c300 has c100 as a prerequisite. Notice that E[1][0] is not 1. If you use the adjacency list representation, then you can print the adjacency list. The list must be sorted in increasing order (e.g. see the list for 0). It should show the corresponding node numbers. E.g. for the above example the adjacency list will be: 0: 1, 2, 1: 2: 1, 6. 7. In order for the output to look the same for everyone, use the correspondence given here: vertex 0 for the course on the first line, vertex 1 for the course on the second line, etc. 1. Print the courses in topological sorted order. This should be done using the DFS (Depth First Search) algorithm that we covered in class and the topological sorting based on DFS discussed in class. There is no topological order if there is a cycle in the graph; in this case print an error message. If in DFV-visit when looking at the (u,v) edge, if the color of v is GRAY then there is a cycle in the graph (and therefore topological sorting is not possible). See the Lecture on topological sorting (You can find the date based on the table on the Scans page and then watch the video from that day. I have also updated the pseudocodein the slides to show that. Refresh the slides and check the date on the first page. If it is 11/26/2020, then you have the most recent version.) 8. (6 points) create and submit 1 test file. It must cover a special case. Indicate what special case you are covering (e.g. no course has any prerequisite). At the top of the file indicate what makes it a special case. Save this file as special.txt. It should be in Unix EOL format. Part 2: Suggestions for improvements (not for grade) 1. CSE Advisors also are mindful and point out to students the "longest path through the degree". That is longest chain of course prerequisites (e.g. CSE1310 ---> CSE1320 --> CSE3318 -->...) as this gives a lower bound on the number of semesters needed until graduation. Can you calculate for each course the LONGEST chain ending with it? E.g. in the above example, there are 2 chains ending with c300 (size 2: just c100-->c300, size 3: c100-->c200-->c300) and you want to show longest path 3 for c300. Can you calculate this number for each course? 2. Allow the user the enter a list of courses taken so far (from the user or from file) and print a list of the courses they can take (they have all the prerequisites for). 3. Ask the user to enter a desired number of courses per semester and suggest a schedule (by semester). Part 3: Implementation suggestions 1. Reading from file: (15 points) For each line in the file, the code can extract the first course and the prerequisites for it. If you cannot process each line in the file correctly, you can use a modified input file that shows on each line, the number of courses, but you would lose the 15 points dedicated to line processing. If your program works with the "easy files", in order to make it easy for the TAs to know which file to provide, please name your C program courses_graph_easy.c. Here is the modification shown for a new example. Instead of c100 c300 c200 c100 c200 the file would have: 1 c1003 c300 c200 c100 1 c200 1. that way the first data on each line is a number that tells how many courses (strings) follow after it on that line. Everything is separated by exactly one space. All the other specifications are the same as for the original file (empty line at the end, no space at the end of any line, length of words, etc). Here is data0_easy.txt Make a direct correspondence between vertex numbers and course names. E.g. the **first** course name on the first line corresponds to vertex 0, the **first** course name on the second line corresponds to vertex 1, etc... 2. 3. The vertex numbers are used to refer to vertices. 4. In order to add an edge in the graph you will need to find the vertex number corresponding to a given course name. E.g. find that c300 corresponds to vertex 1 and c200 corresponds to vertex 2. Now you can set E[2][1] to be 1. (With the adjacency list, add node 1 in the adjacency list for 2 keeping the list sorted.) To help with this, write a function that takes as arguments the list/array of [unique] course names and one course name and returns the index of that course in the list. You can use that index as the vertex number. (This is similar to the indexOf method in Java.) 5. To see all the non-printable characters that may be in a file, find an editor that shows them. E.g. in Notepad++ : open the file, go to View -> Show symbol -> Show all characters. YOU SHOULD TRY THIS! In general, not necessarily for this homework, if you make the text editor show the white spaces, you will know if what you see as 4 empty spaces comes from 4 spaces or from one tab or show other hidden characters. This can help when you tokenize. E.g. here I am using Notepad++ to see the EOL for files saved with Unix/Mac/Windows EOL (see the CR/LF/CRLF at the end of each line): EOL_Mac_Unix_Windows.png How to submit Submit courses_graph.c (or courses_graph_easy.c) and special.txt (the special test case you created) in Canvas . (For courses_graph_easy.c you can submit the "easy" files that you created.)Your program should be named courses_graph.c if it reads from the normal/original files. If instead it reads from the 'easy' files, name it courses_graph_easy.c As stated on the course syllabus, programs must be in C, and must run on omega.uta.edu or the VM. IMPORTANT: Pay close attention to all specifications on this page, including file names and submission format. Even in cases where your answers are correct, points will be taken off liberally for non-compliance with the instructions given on this page (such as wrong file names, wrong compression format for the submitted code, and so on). The reason is that non-compliance with the instructions makes the grading process significantly (and unnecessarily) more time consuming. Contact the instructor or TA if you have any questions
noahjonesx / MarkovModelMarkov Text Generation Problem Description The Infinite Monkey Theorem1 (IFT) says that if a monkey hits keys at random on a typewriter it will almost surely, given an infinite amount of time, produce a chosen text (like the Declaration of Independence, Hamlet, or a script for ... Planet of the Apes). The probability of this actually happening is, of course, very small but the IFT claims that it is still possible. Some people have tested this hypotheis in software and, after billions and billions of simulated years, one virtual monkey was able to type out a sequence of 19 letters that can be found in Shakespeare’s The Two Gentlemen of Verona. (See the April 9, 2007 edition of The New Yorker if you’re interested; but, hypothesis testing with real monkeys2 is far more entertaining.) The IFT might lead to some interesting conversations with Rust Cohle, but the practical applications are few. It does, however, bring up the idea of automated text generation, and there the ideas and applications are not only interesting but also important. Claude Shannon essentially founded the field of information theory with the publication of his landmark paper A Mathematical Theory of Computation3 in 1948. Shannon described a method for using Markov chains to produce a reasonable imitation of a known text with sometimes startling results. For example, here is a sample of text generated from a Markov model of the script for the 1967 movie Planet of the Apes. "PLANET OF THE APES" Screenplay by Michael Wilson Based on Novel By Pierre Boulle DISSOLVE TO: 138 EXT. GROVE OF FRUIT TREES - ESTABLISHING SHOT - DAY Zira run back to the front of Taylor. The President, I believe the prosecutor's charge of this man. ZIRA Well, whoever owned them was in pretty bad shape. He picks up two of the strain. You got what you wanted, kid. How does it taste? Silence. Taylor and cuffs him. Over this we HEAR from a distance is a crude horse-drawn wagon is silhouetted-against the trunks and branches of great trees and bushes on the horse's rump. Taylor lifts his right arm to ward off the blow, and the room and lands at the feet of Cornelius and Lucius are sorting out equipment falls to his knees, buries his head silently at the Ranch). DISSOLVE TO: 197 INT. CAGES - CLOSE SHOT - FEATURING LANDON - FROM TAYLOR'S VOICE (o.s.) I've got a fine veternary surgeons under my direction? ZIRA Taylor! ZIRA There is a small lake, looking like a politician. TAYLOR Dodge takes a pen and notebook from the half-open door of a guard room. Taylor bursts suddenly confronted by his 1https://en.wikipedia.org/wiki/Infinite_monkey_theorem2https://web.archive.org/web/20130120215600/http://www.vivaria.net/experiments/notes/publication/NOTES_ EN.pdf3http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6773024 1 original pursuer (the dismounted cop coming up with a cigar butt and places it in the drawer beside them. TAYLOR What's the best there is a. loud RAP at the doll was found beside the building. Zira waits at the third table. TAYLOR Good question. Is he a man? CORNELIUS (impatiently. DODGE Blessed are the vegetation. These SHOTS are INTERCUT with: 94 WHAT THE ASTRONAUTS They examine the remnants of the cage. ZIRA (plunging on) Their speech organs are adequate. The flaw lies not in anatomy but in the back of his left sleeve. TAYLOR (taking off his shirt. 80 DODGE AND LANDON You don't sound happy in your work. GALEN (defensively) Gorilla hunter stands over a dead man, one fo Besides a few spelling errors and some rather odd things that make you wonder about the author, this passage is surprisingly human-like. This is a simple example of natural language generation, a sub-area of natural language processing—a very active area of research in computer science. The particular approach we’re using in this assignment was famously implemented as the fictitious Mark V. Shaney4 and the Emacs command Disassociated Press5. Approach So, here’s the basic idea: Imagine taking a book (say, Tom Sawyer) and determining the probability with which each character occurs. You would probably find that spaces are the most common, that the character ‘e’ is fairly common, and that the character ‘q’ is rather uncommon. After completing this “level 0” analysis, you would be able to produce random Tom Sawyer text based on character probabilities. It wouldn’t have much in common with the real thing, but at least the characters would tend to occur in the proper propor- tion. In fact, here’s an example of what you might produce: Level 0 rla bsht eS ststofo hhfosdsdewno oe wee h .mr ae irii ela iad o r te u t mnyto onmalysnce, ifu en c fDwn oee iteo Now imagine doing a slightly more sophisticated level 1 analysis by determining the probability with which each character follows every other character. You would probably discover that ‘h’ follows ‘t’ more frequently than ‘x’ does, and you would probably discover that a space follows ‘.’ more frequently than ‘,’ does. You could now produce some randomly generated Tom Sawyer text by picking a character to begin with and then always choosing the next character based on the previous one and the probabilities revealed by the analysis. Here’s an example: Level 1 "Shand tucthiney m?" le ollds mind Theybooure He, he s whit Pereg lenigabo Jodind alllld ashanthe ainofevids tre lin-p asto oun theanthadomoere Now imagine doing a level k analysis by determining the probability with which each character follows every possible sequence of characters of length k (kgrams). A level 5 analysis of Tom Sawyer for example, would reveal that ‘r’ follows “Sawye” more frequently than any other character. After a level k analysis, you would be able to produce random Tom Sawyer by always choosing the next character based on the previous k characters (a kgram) and the probabilities revealed by the analysis. 4https://en.wikipedia.org/wiki/Mark_V._Shaney5https://en.wikipedia.org/wiki/Dissociated_press Page 2 of 5 At only a moderate level of analysis (say, levels 5-7), the randomly generated text begins to take on many of the characteristics of the source text. It probably won’t make complete sense, but you’ll be able to tell that it was derived from Tom Sawyer as opposed to, say, The Sound and the Fury. Here are some more examples of text that is generated from increasing levels of analysis of Tom Sawyer. (These “levels of analysis” are called order K Markov models.) K = 2 "Yess been." for gothin, Tome oso; ing, in to weliss of an’te cle - armit. Papper a comeasione, and smomenty, fropeck hinticer, sid, a was Tom, be suck tied. He sis tred a youck to themen K = 4 en themself, Mr. Welshman, but him awoke, the balmy shore. I’ll give him that he couple overy because in the slated snufflindeed structure’s kind was rath. She said that the wound the door a fever eyes that WITH him. K = 6 people had eaten, leaving. Come - didn’t stand it better judgment; His hands and bury it again, tramped herself! She’d never would be. He found her spite of anything the one was a prime feature sunset, and hit upon that of the forever. K = 8 look-a-here - I told you before, Joe. I’ve heard a pin drop. The stillness was complete, how- ever, this is awful crime, beyond the village was sufficient. He would be a good enough to get that night, Tom and Becky. K = 10 you understanding that they don’t come around in the cave should get the word "beauteous" was over-fondled, and that together" and decided that he might as we used to do - it’s nobby fun. I’ll learn you." To create an order K Markov model of a given source text, you would need to identify all kgrams in the source text and associate with each kgram all the individual characters that follow it. This association or mapping must also capture the frequency with which a given character follows a given kgram. For example, suppose that k = 2 and the sample text is: agggcagcgggcg The Markov model would have to represent all the character strings of length two (2-grams) in the source text, and associate with them the characters that follow them, and in the correct proportion. The following table shows one way of representing this information. kgram Characters that follow ag gc gg gcgc gc agg ca g cg g Once you have created an order K Markov model of a given source text, you can generate new text based on this model as follows. Page 3 of 5 1. Randomly pick k consecutive characters that appear in the sample text and use them as the initial kgram. 2. Append the kgram to the output text being generated. 3. Repeat the following steps until the output text is sufficiently long. (a) Select a character c that appears in the sample text based on the probability of that character following the current kgram. (b) Append this character to the output text. (c) Update the kgram by removing its first character and adding the character just chosen (c) as its last character. If this process encounters a situation in which there are no characters to choose from (which can happen if the only occurrence of the current kgram is at the exact end of the source), simply pick a new kgram at random and continue. As an example, suppose that k = 2 and the sample text is that from above: agggcagcgggcg Here are four different output text strings of length 10 that could have been the result of the process described above, using the first two characters (’ag’) as the initial kgram. agcggcagcg aggcaggcgg agggcaggcg agcggcggca For another example, suppose that k = 2 and the sample text is: the three pirates charted that course the other day Here is how the first three characters of new text might be generated: •A two-character sequence is chosen at random to become the initial kgram. Let’s suppose that “th” is chosen. So, kgram = th and output = th. •The first character must be chosen based on the probability that it follows the kgram (currently “th”) in the source. The source contains five occurrences of “th”. Three times it is followed by ’e’, once it is followed by ’r’, and once it is followed by ’a’. Thus, the next character must be chosen so that there is a 3/5 chance that an ’e’ will be chosen, a 1/5 chance that an ’r’ will be chosen, and a 1/5 chance that an ’a’ will be chosen. Let’s suppose that we choose an ’e’ this time. So, kgram = he and output = the. •The next character must be chosen based on the probability that it follows the kgram (currently “he”) in the source. The source contains three occurrences of “he”. Twice it is followed by a space and once it is followed by ’r’. Thus, the next character must be chosen so that there is a 2/3 chance that a space will be chosen and a 1/3 chance that an ’r’ will be chosen. Let’s suppose that we choose an ’r’ this time. So, kgram = er and output = ther. •The next character must be chosen based on the probability that it follows the kgram (currently “er”) in the source. The source contains only one occurrence of “er”, and it is followed by a space. Thus, the next character must be a space. So, kgram = r_ and output = ther_, where ’_’ represents a blank space. Page 4 of 5 Implementation Details You are provided with two Java files that you must use to develop your solution: MarkovModel.java and TextGenerator.java. The constructors of MarkovModel build the order-k model of the source text. You are required to represent the model with the provided HashMap field. The main method of TextGenerator must process the following three command line arguments (in the args array): •A non-negative integer k •A non-negative integer length. •The name of an input file source that contains more than k characters. Your program must validate the command line arguments by making sure that k and length are non- negative and that source contains at least k characters and can be opened for reading. If any of the command line arguments are invalid, your program must write an informative error message to System.out and terminate. If there are not enough command line arguments, your program must write an informative error message to System.out and terminate. With valid command line arguments, your program must use the methods of the MarkovModel class to create an order k Markov model of the sample text, select the initial kgram, and make each character selection. You must implement the MarkovModel methods according to description of the Markov modeling process in the section above. A few sample texts have been provided, but Project Gutenberg (http://www.gutenberg.org) maintains a large collection of public domain literary works that you can use as source texts for fun and practice. Acknowledgments This assignment is based on the ideas of many people, Jon Bentley and Owen Astrachan in particular.
whl1729 / Notenotes of reading, programming, thinking and etc.
ASPP / ASPP Dataviz 2016Material for the Advanced Scientific Python Programming course, University of Reading, 2016
FirTech / FatioA program for reading and writing FAT32/EXFAT file systems.
certichain / Plv NusNUS Programming Language & Verification Reading Club
Yadav106 / LoxThis is a new programming language built while reading the book Crafting Interpreters
jarmoza / Twic Close ReadingTWiC Close Reading is a program that produces interactive HTML files of texts topic-modeled by MALLET
mak-alex / MopdsFree program for Linux operating systems, designed to quickly create an electronic OPDS-catalog books. OPDS (Open Publication Distribution System) catalog allows you to access Your library via the Internet from most devices for reading electronic books, tablets, smartphones, etc.
namaggarwal / Ycsb Autograph GeneratorThis python program automatically generates the graph by reading logs generated by YCSB.
jbagg / IntelhexA library for reading Intel HEX files specifically for programming micro controllers
olixu / CBDictThis program monitors the clipboard of the system and translate the word from English to Chinese by YouDao api, especially designed for Students who are working under linux environment where there is no simple translater when you reading papers.
aig-upf / SoplexSoPlex is an optimization package for solving linear programming problems (LPs) based on an advanced implementation of the primal and dual revised simplex algorithm. It provides special support for the exact solution of LPs with rational input data. It can be used as a standalone solver reading MPS or LP format files via a command line interface as well as embedded into other programs via a C++ class library.
pnguenda / Pandas Challenge# Pandas Homework - Pandas, Pandas, Pandas ## Background The data dive continues! Now, it's time to take what you've learned about Python Pandas and apply it to new situations. For this assignment, you'll need to complete **one of two** (not both) Data Challenges. Once again, which challenge you take on is your choice. Just be sure to give it your all -- as the skills you hone will become powerful tools in your data analytics tool belt. ### Before You Begin 1. Create a new repository for this project called `pandas-challenge`. **Do not add this homework to an existing repository**. 2. Clone the new repository to your computer. 3. Inside your local git repository, create a directory for the Pandas Challenge you choose. Use folder names corresponding to the challenges: **HeroesOfPymoli** or **PyCitySchools**. 4. Add your Jupyter notebook to this folder. This will be the main script to run for analysis. 5. Push the above changes to GitHub or GitLab. ## Option 1: Heroes of Pymoli  Congratulations! After a lot of hard work in the data munging mines, you've landed a job as Lead Analyst for an independent gaming company. You've been assigned the task of analyzing the data for their most recent fantasy game Heroes of Pymoli. Like many others in its genre, the game is free-to-play, but players are encouraged to purchase optional items that enhance their playing experience. As a first task, the company would like you to generate a report that breaks down the game's purchasing data into meaningful insights. Your final report should include each of the following: ### Player Count * Total Number of Players ### Purchasing Analysis (Total) * Number of Unique Items * Average Purchase Price * Total Number of Purchases * Total Revenue ### Gender Demographics * Percentage and Count of Male Players * Percentage and Count of Female Players * Percentage and Count of Other / Non-Disclosed ### Purchasing Analysis (Gender) * The below each broken by gender * Purchase Count * Average Purchase Price * Total Purchase Value * Average Purchase Total per Person by Gender ### Age Demographics * The below each broken into bins of 4 years (i.e. <10, 10-14, 15-19, etc.) * Purchase Count * Average Purchase Price * Total Purchase Value * Average Purchase Total per Person by Age Group ### Top Spenders * Identify the the top 5 spenders in the game by total purchase value, then list (in a table): * SN * Purchase Count * Average Purchase Price * Total Purchase Value ### Most Popular Items * Identify the 5 most popular items by purchase count, then list (in a table): * Item ID * Item Name * Purchase Count * Item Price * Total Purchase Value ### Most Profitable Items * Identify the 5 most profitable items by total purchase value, then list (in a table): * Item ID * Item Name * Purchase Count * Item Price * Total Purchase Value As final considerations: * You must use the Pandas Library and the Jupyter Notebook. * You must submit a link to your Jupyter Notebook with the viewable Data Frames. * You must include a written description of three observable trends based on the data. * See [Example Solution](HeroesOfPymoli/HeroesOfPymoli_starter.ipynb) for a reference on expected format. ## Option 2: PyCitySchools  Well done! Having spent years analyzing financial records for big banks, you've finally scratched your idealistic itch and joined the education sector. In your latest role, you've become the Chief Data Scientist for your city's school district. In this capacity, you'll be helping the school board and mayor make strategic decisions regarding future school budgets and priorities. As a first task, you've been asked to analyze the district-wide standardized test results. You'll be given access to every student's math and reading scores, as well as various information on the schools they attend. Your responsibility is to aggregate the data to and showcase obvious trends in school performance. Your final report should include each of the following: ### District Summary * Create a high level snapshot (in table form) of the district's key metrics, including: * Total Schools * Total Students * Total Budget * Average Math Score * Average Reading Score * % Passing Math (The percentage of students that passed math.) * % Passing Reading (The percentage of students that passed reading.) * % Overall Passing (The percentage of students that passed math **and** reading.) ### School Summary * Create an overview table that summarizes key metrics about each school, including: * School Name * School Type * Total Students * Total School Budget * Per Student Budget * Average Math Score * Average Reading Score * % Passing Math (The percentage of students that passed math.) * % Passing Reading (The percentage of students that passed reading.) * % Overall Passing (The percentage of students that passed math **and** reading.) ### Top Performing Schools (By % Overall Passing) * Create a table that highlights the top 5 performing schools based on % Overall Passing. Include: * School Name * School Type * Total Students * Total School Budget * Per Student Budget * Average Math Score * Average Reading Score * % Passing Math (The percentage of students that passed math.) * % Passing Reading (The percentage of students that passed reading.) * % Overall Passing (The percentage of students that passed math **and** reading.) ### Bottom Performing Schools (By % Overall Passing) * Create a table that highlights the bottom 5 performing schools based on % Overall Passing. Include all of the same metrics as above. ### Math Scores by Grade\*\* * Create a table that lists the average Math Score for students of each grade level (9th, 10th, 11th, 12th) at each school. ### Reading Scores by Grade * Create a table that lists the average Reading Score for students of each grade level (9th, 10th, 11th, 12th) at each school. ### Scores by School Spending * Create a table that breaks down school performances based on average Spending Ranges (Per Student). Use 4 reasonable bins to group school spending. Include in the table each of the following: * Average Math Score * Average Reading Score * % Passing Math (The percentage of students that passed math.) * % Passing Reading (The percentage of students that passed reading.) * % Overall Passing (The percentage of students that passed math **and** reading.) ### Scores by School Size * Repeat the above breakdown, but this time group schools based on a reasonable approximation of school size (Small, Medium, Large). ### Scores by School Type * Repeat the above breakdown, but this time group schools based on school type (Charter vs. District). As final considerations: * Use the pandas library and Jupyter Notebook. * You must submit a link to your Jupyter Notebook with the viewable Data Frames. * You must include a written description of at least two observable trends based on the data. * See [Example Solution](PyCitySchools/PyCitySchools_starter.ipynb) for a reference on the expected format. ## Hints and Considerations * These are challenging activities for a number of reasons. For one, these activities will require you to analyze thousands of records. Hacking through the data to look for obvious trends in Excel is just not a feasible option. The size of the data may seem daunting, but pandas will allow you to efficiently parse through it. * Second, these activities will also challenge you by requiring you to learn on your feet. Don't fool yourself into thinking: "I need to study pandas more closely before diving in." Get the basic gist of the library and then _immediately_ get to work. When facing a daunting task, it's easy to think: "I'm just not ready to tackle it yet." But that's the surest way to never succeed. Learning to program requires one to constantly tinker, experiment, and learn on the fly. You are doing exactly the _right_ thing, if you find yourself constantly practicing Google-Fu and diving into documentation. There is just no way (or reason) to try and memorize it all. Online references are available for you to use when you need them. So use them! * Take each of these tasks one at a time. Begin your work, answering the basic questions: "How do I import the data?" "How do I convert the data into a DataFrame?" "How do I build the first table?" Don't get intimidated by the number of asks. Many of them are repetitive in nature with just a few tweaks. Be persistent and creative! * Expect these exercises to take time! Don't get discouraged if you find yourself spending hours initially with little progress. Force yourself to deal with the discomfort of not knowing and forge ahead. Consider these hours an investment in your future! * As always, feel encouraged to work in groups and get help from your TAs and Instructor. Just remember, true success comes from mastery and _not_ a completed homework assignment. So challenge yourself to truly succeed! ### Copyright Trilogy Education Services © 2019. All Rights Reserved.
rabestro / Jetbrains Academy Readability ScoreEveryone has their own personal reading history, and as we grow up, we are able to comprehend more and more complicated texts. But how do you estimate the level of difficulty of a given text, and how do you teach a computer to do that? In this project, you will find it out: write a program that determines how difficult the text is and for which age it is most suitable.
VENKATESAN18 / Cryptocurrency Public LedgerA cryptocurrency public ledger is a record-keeping system. It maintains participants' identities anonymously, their respective cryptocurrency balances, and record all the genuine transactions executed between network participants. Cryptocurrency is an encrypted decentralized digital currency. SQL is not the proper database to store the information of transactions because cryptocurrency is encrypted and decentralized. This project is to make the ledger (Similar to Bank Management System). We can make Transactions of tokens (as a user), create an account, delete it, view the public ledger ( details of sender and receiver (only address of the wallet and tokens transacted)). Scaling and security concerns are one the challenge. Future advancements are shifting to the blockchain database. SQL (Structured Query Language) is a standardized programming language that's used to manage relational databases and perform various operations on the data in them. Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. The transaction's details in the bank's records can be queried and verified by the two parties between whom the transaction took place. Public ledgers work the same way as bank records, although with a few differences. Similar to the bank records, the transaction details on a cryptocurrency public ledger can be verified and queried by the two transacting participants. However, no central authority or network participants can know the identity of the participants. Transactions are allowed and recorded only after suitable verification of the sender’s liquidity; otherwise, they are discarded. The objective of this project is to let the students apply the programming knowledge to a real-world situation/problem and exposed the students to how programming skills help in developing good software. This is also to educate the students on future technologies and make them aware of what's happening in the technological world. Students will demonstrate a breadth of knowledge in computer science, as exemplified in the areas of systems, theory and software development. Students will demonstrate the ability to conduct research or applied Computer Science projects, requiring writing and presentation skills that exemplify scholarly style in computer science. Students will learn about the basic principle, how cryptocurrency works and will develop a curiosity to dive deep into readings blogs (computer science research papers).
Umair444 / Smart MeterTrend in the IoT based smart devices is tremendously increasing day by day. By time more people are becoming aware of smart technology and its convenience in control and management of daily things seizes their attention. Smart energy meters (SEM) plays one role in this world of smart devices, to progress towards making the whole power system interconnected. In past three decades people had done much work on making power systems smart and thus there are plenty of published papers on smart meters. This project specifically uses different approach with additional functional development and better accuracy. Briefly, SEM is a remote monitoring and control device that automatically transmit data to utility, limits load to minimize load shedding trend, use operation techniques for generating stations for demand estimation and provide different options to consumers to manage their budget, like individual appliance power usage and cumulative plots. Transmitting data enables the utility computers to monitor the meter readings regularly to avert electricity theft. With the use of a programmable unit we can operate the meter to continuously monitors and records the readings in its permanent (nonvolatile) memory location in most feasible way. Whole world is connected through internet, and thus it is the most appropriate and common way of communication for a smart device. With internet there is need for additional security protocols and encrypted channels; but with this complexity meter can lead in many other ways that’s not possible through other channels. WIFI adapter connected with router sends data sample to internet after planted sample time. This data will then send towards consumer mobile application and towards utility, where computer will statistically analyze the data and show the results. As, the period end this adapter will receive bill from utility and controller will cut the supply off if payment time limit exceeds. So, with this bidirectional communication technique utility can send ads and other deals to some specific meter by time; and consumer can access direct support from utility.
DSCfuo / FuocribsFUOcribs is an open source web project aimed at helping university students find roommates and available accomodation. The overall idea behind this program is to help develop coding and real-world problem-solving skills. This project is beginner friendly because no framework would be used and would be built from scratch so we encourage every contributor to give this rpoject their best shot and also __write down good comments in your codes to help another person reading your code learn and understand fast.__ ## Languages required * HTML5 * CSS3 * JAVASCRIPT * PHP * MYSQL ## Tools needed * Web browser * Text editor * You can use any text editor of your choice. Recommended text editors: [Atom](https://atom.io), [Brackets](https://brackets.io), [Vscode](https://code.visualstudio.com/download) * Offline server ([xampp](https://www.apachefriends.org/download.html) or [wamp](http://www.wampserver.com/en/)) ## Workflow This section describes the workflow we are going to follow when working in a new feature or fixing a bug. If you want to contribute, please follow these steps: #### Fork this project Clone the forked project to your local environment, for example: ```git clone https://github.com/DSCfuo/fuocribs.git ``` (Make sure to replace the URL to your own repository). Add the original project as a remote, for this example the name is upstream, feel free to use whatever name you want. git remote add upstream ```https://github.com/DSCfuo/fuocribs.git ``` Forking the project will create a copy of that project in your own GitHub account, you will commit your work against your own repository. #### Updating your local In order to update your local environment to the latest version on master, you will have to pull the changes using the upstream repository, for example: git pull upstream master. This will pull all the new commits from the origin repository to your local environment. #### Features/Bugs When working on a new feature, create a new branch feature/something from the master branch, for example feature/login-form. Commit your work against this new branch and push everything to your forked project. Once everything is completed, you should create a pull request to the original project. Make sure to add a description about your work and a link to the trello task. When fixing a bug, create a new branch fix/something from the master branch, for example fix/css-btn-issues. When completed, push your commits to your forked repository and create a pull request from there. Please make sure to describe what was the problem and how did you fix it. #### Updating your local branch Let's say you've been working on a feature for a couple days, most likely there are new changes in master and your branch is behind. In order to update it to the latest (You might not need/want to do this) you need to pull the latest changes to develop and then rebase your current branch. $ git checkout master $ git pull upstream master $ git checkout feature/something-awesome $ git rebase master After this, your commits will be on top of the master commits. From here you can push to your origin repository and create a pull request. You might have some conflicts while rebasing, try to resolve the conflicts for each individual commit. Rebasing is intimidating at the beginning, if you need help don't be afraid to reach out in slack. #### Pull requests In order to merge a pull request, there should be a couple of approval reviews. Once is approved, we should merge to the master branch using the Squash button in github. When using squash, all the commits will be squashed into one. The idea is to merge features/fixes as oppose of merging each individual commit. This helps when looking back in time for changes in the code base, and if the pull request has a great comment, it's easier to know why that code was introduced.
thehuy2000 / CS344 OSI Assignment 3 Small ShellIn this assignment you will write smallsh your own shell in C. smallsh will implement a subset of features of well-known shells, such as bash. Your program will Provide a prompt for running commands Handle blank lines and comments, which are lines beginning with the # character Provide expansion for the variable $$ Execute 3 commands exit, cd, and status via code built into the shell Execute other commands by creating new processes using a function from the exec family of functions Support input and output redirection Support running commands in foreground and background processes Implement custom handlers for 2 signals, SIGINT and SIGTSTP Learning Outcomes After successful completion of this assignment, you should be able to do the following Describe the Unix process API (Module 4, MLO 2) Write programs using the Unix process API (Module 4, MLO 3) Explain the concept of signals and their uses (Module 5, MLO 2) Write programs using the Unix API for signal handling (Module 5, MLO 3) Explain I/O redirection and write programs that can employ I/O redirection (Module 5, MLO 4) Program Functionality 1. The Command Prompt Use the colon : symbol as a prompt for each command line. The general syntax of a command line is: command [arg1 arg2 ...] [< input_file] [> output_file] [&] …where items in square brackets are optional. You can assume that a command is made up of words separated by spaces. The special symbols <, > and & are recognized, but they must be surrounded by spaces like other words. If the command is to be executed in the background, the last word must be &. If the & character appears anywhere else, just treat it as normal text. If standard input or output is to be redirected, the > or < words followed by a filename word must appear after all the arguments. Input redirection can appear before or after output redirection. Your shell does not need to support any quoting; so arguments with spaces inside them are not possible. We are also not implementing the pipe "|" operator. Your shell must support command lines with a maximum length of 2048 characters, and a maximum of 512 arguments. You do not need to do any error checking on the syntax of the command line. 2. Comments & Blank Lines Your shell should allow blank lines and comments. Any line that begins with the # character is a comment line and should be ignored. Mid-line comments, such as the C-style //, will not be supported. A blank line (one without any commands) should also do nothing. Your shell should just re-prompt for another command when it receives either a blank line or a comment line. 3. Expansion of Variable $$ Your program must expand any instance of "$$" in a command into the process ID of the smallsh itself. Your shell does not otherwise perform variable expansion. 4. Built-in Commands Your shell will support three built-in commands: exit, cd, and status. These three built-in commands are the only ones that your shell will handle itself - all others are simply passed on to a member of the exec() family of functions. You do not have to support input/output redirection for these built in commands These commands do not have to set any exit status. If the user tries to run one of these built-in commands in the background with the & option, ignore that option and run the command in the foreground anyway (i.e. don't display an error, just run the command in the foreground). exit The exit command exits your shell. It takes no arguments. When this command is run, your shell must kill any other processes or jobs that your shell has started before it terminates itself. cd The cd command changes the working directory of smallsh. By itself - with no arguments - it changes to the directory specified in the HOME environment variable This is typically not the location where smallsh was executed from, unless your shell executable is located in the HOME directory, in which case these are the same. This command can also take one argument: the path of a directory to change to. Your cd command should support both absolute and relative paths. status The status command prints out either the exit status or the terminating signal of the last foreground process ran by your shell. If this command is run before any foreground command is run, then it should simply return the exit status 0. The three built-in shell commands do not count as foreground processes for the purposes of this built-in command - i.e., status should ignore built-in commands. 5. Executing Other Commands Your shell will execute any commands other than the 3 built-in command by using fork(), exec() and waitpid() Whenever a non-built in command is received, the parent (i.e., smallsh) will fork off a child. The child will use a function from the exec() family of functions to run the command. Your shell should use the PATH variable to look for non-built in commands, and it should allow shell scripts to be executed If a command fails because the shell could not find the command to run, then the shell will print an error message and set the exit status to 1 A child process must terminate after running a command (whether the command is successful or it fails). 6. Input & Output Redirection You must do any input and/or output redirection using dup2(). The redirection must be done before using exec() to run the command. An input file redirected via stdin should be opened for reading only; if your shell cannot open the file for reading, it should print an error message and set the exit status to 1 (but don't exit the shell). Similarly, an output file redirected via stdout should be opened for writing only; it should be truncated if it already exists or created if it does not exist. If your shell cannot open the output file it should print an error message and set the exit status to 1 (but don't exit the shell). Both stdin and stdout for a command can be redirected at the same time (see example below). 7. Executing Commands in Foreground & Background Foreground Commands Any command without an & at the end must be run as a foreground command and the shell must wait for the completion of the command before prompting for the next command. For such commands, the parent shell does NOT return command line access and control to the user until the child terminates. Background Commands Any non built-in command with an & at the end must be run as a background command and the shell must not wait for such a command to complete. For such commands, the parent must return command line access and control to the user immediately after forking off the child. The shell will print the process id of a background process when it begins. When a background process terminates, a message showing the process id and exit status will be printed. This message must be printed just before the prompt for a new command is displayed. If the user doesn't redirect the standard input for a background command, then standard input should be redirected to /dev/null If the user doesn't redirect the standard output for a background command, then standard output should be redirected to /dev/null 8. Signals SIGINT & SIGTSTP SIGINT A CTRL-C command from the keyboard sends a SIGINT signal to the parent process and all children at the same time (this is a built-in part of Linux). Your shell, i.e., the parent process, must ignore SIGINT Any children running as background processes must ignore SIGINT A child running as a foreground process must terminate itself when it receives SIGINT The parent must not attempt to terminate the foreground child process; instead the foreground child (if any) must terminate itself on receipt of this signal. If a child foreground process is killed by a signal, the parent must immediately print out the number of the signal that killed it's foreground child process (see the example) before prompting the user for the next command. SIGTSTP A CTRL-Z command from the keyboard sends a SIGTSTP signal to your parent shell process and all children at the same time (this is a built-in part of Linux). A child, if any, running as a foreground process must ignore SIGTSTP. Any children running as background process must ignore SIGTSTP. When the parent process running the shell receives SIGTSTP The shell must display an informative message (see below) immediately if it's sitting at the prompt, or immediately after any currently running foreground process has terminated The shell then enters a state where subsequent commands can no longer be run in the background. In this state, the & operator should simply be ignored, i.e., all such commands are run as if they were foreground processes. If the user sends SIGTSTP again, then your shell will Display another informative message (see below) immediately after any currently running foreground process terminates The shell then returns back to the normal condition where the & operator is once again honored for subsequent commands, allowing them to be executed in the background. See the example below for usage and the exact syntax which you must use for these two informative messages. Sample Program Execution Here is an example run using smallsh. Note that CTRL-C has no effect towards the bottom of the example, when it's used while sitting at the command prompt: $ smallsh : ls junk smallsh smallsh.c : ls > junk : status exit value 0 : cat junk junk smallsh smallsh.c : wc < junk > junk2 : wc < junk 3 3 23 : test -f badfile : status exit value 1 : wc < badfile cannot open badfile for input : status exit value 1 : badfile badfile: no such file or directory : sleep 5 ^Cterminated by signal 2 : status & terminated by signal 2 : sleep 15 & background pid is 4923 : ps PID TTY TIME CMD 4923 pts/0 00:00:00 sleep 4564 pts/0 00:00:03 bash 4867 pts/0 00:01:32 smallsh 4927 pts/0 00:00:00 ps : : # that was a blank command line, this is a comment line : background pid 4923 is done: exit value 0 : # the background sleep finally finished : sleep 30 & background pid is 4941 : kill -15 4941 background pid 4941 is done: terminated by signal 15 : pwd /nfs/stak/users/chaudhrn/CS344/prog3 : cd : pwd /nfs/stak/users/chaudhrn : cd CS344 : pwd /nfs/stak/users/chaudhrn/CS344 : echo 4867 4867 : echo $$ 4867 : ^C^Z Entering foreground-only mode (& is now ignored) : date Mon Jan 2 11:24:33 PST 2017 : sleep 5 & : date Mon Jan 2 11:24:38 PST 2017 : ^Z Exiting foreground-only mode : date Mon Jan 2 11:24:39 PST 2017 : sleep 5 & background pid is 4963 : date Mon Jan 2 11:24:39 PST 2017 : exit $ Hints & Resources 1. The Command Prompt Be sure you flush out the output buffers each time you print, as the text that you're outputting may not reach the screen until you do in this kind of interactive program. To do this, call fflush() immediately after each and every time you output text. Consider defining a struct in which you can store all the different elements included in a command. Then as you parse a command, you can set the value of members of a variable of this struct type. 2. Comments & Blank Lines This should be simple. 3. Expansion of Variable $$ Here are examples to illustrate the required behavior. Suppose the process ID of smallsh is 179. Then The string foo$$$$ in the command is converted to foo179179 The string foo$$$ in the command is converted to foo179$ 4. Built-in Commands It is recommended that you program the built-in commands first, before tackling the commands that require fork(), exec() and waitpid(). The built-in commands don't set the value of status. This means that however you are keeping track of the status, don't change it after the execution of a built-in command. A process can use chdir() (Links to an external site.) to change its directory. To test the implementation of the cd command in smallsh, don't use getenv("PWD") because it will not give you the correct result. Instead, you can use the function getcwd() (Links to an external site.). Here is why getenv("PWD") doesn't give you the correct result: PWD is an environment variable. As discussed in Module 4, Exploration: Environment "When a parent process forks a child process, the child process inherits the environment of its parent process." When you run smallsh from a bash shell, smallsh inherits the environment of this bash shell The value of PWD in the bash shell is set to the directory in which you are when you run the command to start smallsh smallsh inherits this value of PWD. When you change the directory in smallsh, it doesn't update the value of the environment variable PWD 5. Executing Other Commands Note that if exec() is told to execute something that it cannot do, like run a program that doesn't exist, it will fail, and return the reason why. In this case, your shell should indicate to the user that a command could not be executed (which you know because exec() returned an error), and set the value retrieved by the built-in status command to 1. Make sure that the child process that has had an exec() call fail terminates itself, or else it often loops back up to the top and tries to become a parent shell. This is easy to spot: if the output of the grading script seems to be repeating itself, then you've likely got a child process that didn't terminate after a failed exec(). You can choose any function in the exec() family. However, we suggest that using either execlp() or execvp() will be simplest because of the following reasons smallsh doesn't need to pass a new environment to the program. So the additional functionality provided by the exec() functions with names ending in e is not required. One example of a command that smallsh needs to run is ls (the graders will try this command at the start of the testing). Running this command will be a lot easier using the exec() functions that search the PATH environment variable. 6. Input & Output Redirection We recommend that the needed input/output redirection should be done in the child process. Note that after using dup2() to set up the redirection, the redirection symbol and redirection destination/source are NOT passed into the exec command For example, if the command given is ls > junk, then you handle the redirection to "junk" with dup2() and then simply pass ls into exec(). 7. Executing Commands in Foreground & Background Foreground Commands For a foreground command, it is recommend to have the parent simply call waitpid() on the child, while it waits. Background Commands The shell should respect the input and output redirection operators for a command regardless of whether the command is to be run in the foreground or the background. This means that a background command should use /dev/null for input only when input redirection is not specified in the command. Similarly a background command should use /dev/null for output only when output redirection is not specified in the command. Your parent shell will need to periodically check for the background child processes to complete, so that they can be cleaned up, as the shell continues to run and process commands. Consider storing the PIDs of non-completed background processes in an array. Then every time BEFORE returning access to the command line to the user, you can check the status of these processes using waitpid(...NOHANG...). Alternatively, you may use a signal handler to immediately wait() for child processes that terminate, as opposed to periodically checking a list of started background processes The time to print out when these background processes have completed is just BEFORE command line access and control are returned to the user, every time that happens. 8. Signals SIGINT & SIGTSTP Reentrancy is important when we consider that signal handlers cause jumps in execution that cause problems with certain functions. Note that the printf() family of functions is NOT reentrant. In your signal handlers, when outputting text, you must use other output functions! What to turn in? You can only use C for coding this assignment and you must use the gcc compiler. You can use C99 or GNU99 standard or the default standard used by the gcc installation on os1. Your assignment will be graded on os1. Submit a single zip file with all your code, which can be in as many different files as you want. This zip file must be named youronid_program3.zip where youronid should be replaced by your own ONID. E.g., if chaudhrn was submitting the assignment, the file must be named chaudhrn_program3.zip. In the zip file, you must include a text file called README.txt that contains instructions on how to compile your code using gcc to create an executable file that must be named smallsh. Your zip file should not contain any extraneous files. In particular, make sure not to zip up the __MACOSX directories. When you resubmit a file in Canvas, Canvas can attach a suffix to the file, e.g., the file name may become chaudhrn_program3-1.zip. Don't worry about this name change as no points will be deducted because of this. Caution During the development of this program, take extra care to only do your work on os1, our class server, as your software will likely negatively impact whatever machine it runs on, especially before it is finished. If you cause trouble on one of the non-class, public servers, it could hurt your grade! If you are having trouble logging in to any of our EECS servers because of runaway processes, please use this page to kill off any programs running on your account that might be blocking your access: T.E.A.C.H. - The Engineering Accounts and Classes HomepageLinks to an external site. Grading Criteria This assignment is worth 20% of your grade and there are 180 points available for it. 170 points are available in the test script, while the final 10 points will be based on your style, readability, and commenting. Comment well, often, and verbosely: we want to see that you are telling us WHY you are doing things, in addition to telling us WHAT you are doing. Once the program is compiled, according to your specifications given in README.txt, your shell will be executed to run a few sample commands against (ls, status, exit, in that order). If the program does not successfully work on those commands, it will receive a zero. If it works, then the grading script will be run against it (as detailed below) for final grading. Points will be assigned according to the grading script running on our class server only. Grading Method Here is the grading script p3testscript. It is a bash script that starts the smallsh program and runs commands on smallsh's command line. Most of the commands run by the grading script are very similar to the commands shown in the section Sample Program Execution. You can open the script in a text editor. The comments in the script will show you the points for individual items. Use the script to prepare for your grade, as this is how it's being earned. To run the script, place it in the same directory as your compiled shell, chmod it (chmod +x ./p3testscript) and run this command from a bash prompt: $ ./p3testscript 2>&1 or $ ./p3testscript 2>&1 | more or $ ./p3testscript > mytestresults 2>&1 Do not worry if the spacing, indentation, or look of the output of the script is different than when you run it interactively: that won’t affect your grade. The script may add extra colons at the beginning of lines or do other weird things, like put output about terminating processes further down the script than you intended. If your program does not work with the grading script, and you instead request that we grade your script by hand, we will apply a 15% reduction to your final score. So from the very beginning, make sure that you work with the grading script on our class server!
