Project <%= project_id %>
| Number of Test Suites | Number of Test Cases | Number of Test Plans | Number of Test Runs | Number of Executions |
|---|---|---|---|---|
| <%= report['test_suites_count'] %> | <%= report['test_cases_count'] %> | <%= report['test_plans_count'] %> | <%= report['test_runs_count'] %> | <%= report['executions_count'] %> |
Executions Summary


The web service that gives you an African name
The Akan naming System is a web application that is based on a Ghananian naming culture. The Ghananian Akan naming works as follows;
Children are given their first names as a day name which corresponds to the day of the week they were born.
The application takes your birthday and gender input and tells the day of the week you were born, and then gives you an Akan name corresponding to your day of birth.
The system works in three easy steps:


November 05, 1955
November 05, 1955
November 05, 1955
This is a "Facebook" styled Card. The header is created from a Thumbnail List item, the content is from a card-body consisting of an image and paragraph text. The footer consists of a Tab Bar, icons aligned left, within the card-footer.


Mikhail Priver
mailto
<EMAIL_ADDRESS>skype
:mishkapriver
github
.com/priver
linkedin
.com/in/mpriver
twitter
.com/priver
facebook
.com/mpriver
google
.com/+MikhailPriver
vk
.com/mpriver
instagram
.com/priver
last.fm
/user/keepquiet1


Accessible through navigation panel at the top of every page, your list of currently desired items
Price history charts are another major part of dealalert. Graphs of the price variations over time are available through wishlist by clicking appropriate icon. Price and availability data is updated from Amazon constantly to ensure it is as accurate as possible, but should always be checked on Amazon before making a purchase.
The primary feature of our site is the sending of email alerts when prices change. While in wishlist page, the user simply sets a price threshold at which alerts are generated, and we email you when that condition is met.
Search is accessed via the box at the top of browse page.
If you do choose to sign up or receive email alerts, we will not sell or distribute your information to anyone without your consent.


INTERVIEW WITH THE VAMPIRE A film review by Steve Rhodes Copyright 1995 Steve Rhodes
RATING (0 TO ****): *
INTERVIEW WITH THE VAMPIRE is the screen version of Anne Rice's extremely popular book by the same name. Since she wrote the screenplay, I would assume the movie is close to the book which I have never read.
INTERVIEW WITH THE VAMPIRE starts in the present in Market Street in San Francisco with Christian Slater interviewing a vampire played by Brad Pitt. It seems a couple of hundred years ago, Pitt was willing made into a vampire by another vampire (Tom Cruise). We then switch to the past and watch Pitt's start as a vampire with Cruise teaching him the ropes.
So what is it like being a vampire you ask? Well, you get to drink gallons and gallons of blood. I can handle that so long as there is something else that makes me want to watch the screen other than the drinking of blood. I got bored silly and totally disgusted. I am not easily turned off; Pulp Fiction is one of my favorite movies this year.
INTERVIEW WITH THE VAMPIRE was way off of any scale I can imagine. You had one long scene after another where they would pierce someone's vein, pour the gushing blood into a glass, and then pass the glass around to share.  Ditto for pet dogs and for hundreds of birds.  Where are the animal rights people when you need them?
On the good side, the filming is beautiful. The colors in the movie all have a warm glow to them. The art decoration of the old plantation was well done. I applaud Cruise for taking so much risk as an actor, and I was amazed how much he was able to hide his pretty boy self.
The movie runs a painfully long 2:00. It is incorrectly rated R--this is clearly an NC-17 show full of extremely violent images. It could give anyone nightmares for a week. I recommend this show to no one and award it * only for the previously mentioned technical merit. Were it not so well crafted, I would have given this despicable show no stars at all. I hated this show and found it painful in the extreme to point my eyes to the screen. You could not pay me to sit through it again. Yes, I have many friends that I respect who loved it, but I honestly do not understand why. At any rate, my pain is over since I do not have to watch any more of it.
**** = One of the top few films of this or any year. A must see film. *** = Excellent show. Look for it. ** = Average movie. Kind of enjoyable. * = Poor show.  Totally unbearable.
REVIEWED WRITTEN ON: December 9, 1994
Opinions expressed are mine and not meant to reflect my employer's.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Increment or decrement the number stored at key by one. If the key doesnot exist or contains a value of a wrong type, set the key to thevalue of "0" before to perform the increment or decrement operation.
INCRBY and DECRBY work just like INCR and DECR but instead toincrement/decrement by 1 the increment/decrement is integer.


PML-Q is an ally of the govt and will remain so: Pervaiz Elahi | Pakistan - Geo.tv
by Web DeskISLAMABAD: Punjab Assembly Speaker Chaudhry Pervaiz Elahi said on Sunday that the Pakistan Muslim League- Quaid e Azam (PML-Q) is an ally of the government and will remain so in the future as well.
READ MORE: Maulana ended Islamabad dharna after an 'understanding' with govt, says Elahi
The former Punjab chief minister said that no one can create a misunderstanding between the party and the government. He clarified his remarks on former prime minister Nawaz Sharif.
"Whatever I said about Nawaz was for Imran Khan's own good," he said.
Elahi said that he had contacted Maulana Fazlur Rehman to save the country from descending into political chaos.
Elahi had said a few days ago during an interview that Prime Minister Imran Khan should let Nawaz fly out of the country since the former prime minister was gravely ill.
In a recent interview on Geo TV, JUI-F chief Fazl had said that Elahi had agreed to his stance when the last time the two met.
Elahi was part of the government's negotiating committee that held talks with Fazl when the JUI-F chief brought thousands of protesters to the H-9 venue in Islamabad and demanded Prime Minister Imran's resignation.
Though Defence Minister Pervaiz Khattak was heading the committee, Elahi and his cousin, Chaudhry Shujaat held talks with the JUI-F chief during the protest to present the government's demands.


This syllabus is subject to change based on specific class needs, especially the schedule. Significant deviations will be discussed in class. Individual exceptions to the policies and schedule are granted only in cases of true emergency. Please make arrangements with me if an emergency arises.
An introduction to proof-based mathematics through the study of key areas of discrete mathematics. This course serves as an introduction to higher-level mathematics and advanced coursework in math. Students will hone their mathematical reasoning skills, learning to express and work with precise mathematical definitions. A strong emphasis is placed on developing the skills necessary to communicate mathematical results.
Topics covered in this course include the the core definitions and theorems from set theory, mathematical logic, and combinatorics. In this context students will explore ideas such as mathematical induction, functions, and relations and the proof techniques of direct proof, contrapositive proof, proof by contradiction, and disproof.
The course textbook will be:
The weekly workload for this course will vary by student and by week but should be about 12 hours per week on average. The following table provides a rough estimate of the distribution of time over different course components for a 16 week semester, as well as detailing the type, amount, and relative value of all assignments.
| Category | Amount | Final Grade Weight | Time/Week (Hours) |
|---|---|---|---|
| Lectures | 41 | 10% (Participation) | 2.5 |
| Problem Sets | 35–45 | 35% | 6 |
| Reading/Study | - | - | 3.5 |
| Exams | 5–8 | 55% | - |
| 12 |
Much of the material builds on previous material; hence, exams are naturally cumulative. Each exam is weighted equally.
Your lowest 3 problem set scores will be dropped, i.e., your final problem set grade is the average of all except the two smallest. Your lowest exam score is also dropped.
Your participation grade is based on a variety of activities. During class I will often make use of the Socrative app, so you’ll need to install this on your phones. Participating in Socrative questions and with in-class group activities is required for a decent participation grade; an A includes asking questions either in class or in office hours.
An additional portion of your participation grade is based on your problem set presentations. Every day that a problem set is due, one or more students will be randomly selected to present their solution to a portion of the assignment. You will be graded based on preparation and the thoroughness of your explanations, NOT on correctness, although you should of course strive for correctness. Students taking late days will be required to leave the classroom during these presentations. You must inform me BEFORE class if you are taking late days to avoid being randomly selected to present. Otherwise, if you are randomly selected to present but have not done the assignment, you will receive a 0.
Your final grade is based on a weighted average of particular assignment categories. You can estimate your current grade based on your scores and these weights. You may always visit the instructor outside of class to discuss your current standing. Assignments and final grades use a standard grading scale shown below and will not be curved except in rare cases when deemed necessary by the instructor.
This courses uses a standard grading scale. Assignments and final grades will not be curved except in rare cases when its deemed necessary by the instructor. Percentage grades translate to letter grades as follows:
| Score | Grade |
|---|---|
| 94–100 | A |
| 90–93 | A- |
| 88–89 | B+ |
| 82–87 | B |
| 80–81 | B- |
| 78–79 | C+ |
| 72–77 | C |
| 70–71 | C- |
| 68–69 | D+ |
| 62–67 | D |
| 60–61 | D- |
| 0–59 | F |
You are always welcome to challenge a grade that you feel is unfair or calculated incorrectly. Mistakes made in your favor will never be corrected to lower your grade. Mistakes made not in your favor will be corrected. Basically, after the initial grading your score can only go up as the result of a challenge*.
You are always welcome to challenge a grade that you feel is unfair or calculated incorrectly. Mistakes made in your favor will never be corrected to lower your grade. Mistakes made not in your favor will be corrected. Basically, after the initial grading your score can only go up as the result of a challenge.
Late Assignments: You have each been allotted a total of 5 late days. You may apply these to any homework or programming assignment (NOT exams, labs, or reading assignments) you see fit and turn in your solutions with no penalty. Each late days gives you exactly 24 extra hours from the original due date and time. However, you may use at most 2 late days on any individual assignment. The whole point here is to give you some flexibility that allows for things like illnesses, long trips, and the like. I am unlikely to grant further extensions. You must notify me if you will use late days, and how many, BEFORE the assignment is due. Late assignments (beyond any applied late days) will be subject to a grade reduction at my discretion. While you should expect a reasonable penalty for late work, know that I will NEVER give you a 0 for late work as long as it is turned in before the final exam.
Academic Dishonesty: Monmouth College’s official policy on academic dishonesty can be found here. You are responsible for reading and complying with that policy.
In this course, any violation of the academic honesty policy will have varying consequences depending on the severity of the infraction as judged by the instructor. Minimally, a violation will result in an “F” or 0 points on the assignment in question. Additionally, the student’s course grade may be lowered by one letter grade. In severe cases, the student will be assigned a course grade of “F” and dismissed from the class. All cases of academic dishonesty must be reported to the Associate Dean who may decide to recommend further action to the Admissions and Academic Status Committee, including suspension or dismissal. It is assumed that students will educate themselves regarding what is considered to be academic dishonesty, so excuses or claims of ignorance will not mitigate the consequences of any violations
Collaboration: We encourage you to make use of the resources available to you – it is fine to seek help from a friend, tutor, instructor, internet, etc. However, copying of answers and any act worthy of the label of “cheating” is never permissible! It is understandable that when you work with a partner or a group that the resultant product is often extremely similar. This is acceptable but be prepared to be asked to defend your collaborations to the instructor. You should always be able to reproduce an answer on your own, and if you cannot you likely do not really know the material.
One way to collaborate effectively is to avoid taking careful notes during a collaboration session. Discuss the material and sketch out possible solutions on a whiteboard. When you have finished, take a break and then write up your solutions without any help from notes or pictures from the study session. This not only helps avoid violations of academic dishonesty, it also improves your retention of the material!
When assignments are meant to be done in groups, you will be directed to turn in one set of solutions per group. Otherwise, each student must turn in an assignment representing their own work.
Electronic Devices: Do not use your phone or other devices in class except where necessary. Any computer or tablet usage should be related to the course. If a device is not being used for Zoom or Socrative it should be put away and turned on silent. Other usage is rude and distracting to others.
General Expectations: In short, I expect you to be respectful of others and take responsibility for your own learning. You are here to learn, so work hard and be professional.
Just attending class is not sufficient to truly learn the material. Read the text, use the resources available at Monmouth College, and go beyond the material.
If you miss class, you are responsible for everything covered on that day. College is, in some sense, your job. Take pride in creating quality work. Staple your assignments, label problems, and present your answers neatly and orderly.
Your job is to convince me that you have learned the material – show your work! Even if you do not know a particular answer, guide me through your thought process.
The following tentative calendar should give you a feel for how work is distributed throughout the semester. Assignments and events are listed in the week they are due or when they occur. This calendar is subject to change based on the circumstances of the course.
Sections marked with an asterisk (*) may be skimmed.
| Date | Topic/Reading | Assignment |
|---|---|---|
| Wed 08/24 (Week 1) | Logistics, Sets (1.1) | |
| Fri 08/26 | Products (1.2), Subsets (1.3) | PS01: §1.1 (2,6,14,20,26,30,36,48) |
| Mon 08/29 (Week 2) | Set Operations I (1.4-1.5) | PS02: §1.2 (2,4,12,20), §1.3 (6,10,12,14) |
| Tue 08/30 | Presentations/Examples | |
| Wed 08/31 | Set Operations II (1.6-1.7) | PS03: §1.4 (2,8,10,14,18) §1.5 (2,4abcfg,8) |
| Fri 09/02 | Indexed Sets (1.8, 1.9*) | PS04: §1.6 (2,6), §1.7 (4,8) |
| Mon 09/05 (Week 3) | Statements, And,Or,Not (2.1-2.2) | PS05: §1.8 (2,4,6,8) |
| Tue 09/06 | Exam Review | |
| Wed 09/07 | PS06: §2.1 (4,6,8,10), §2.2 (2,4,8,10) | |
| Fri 09/09 | Exam 1 (Ch. 1) | |
| Mon 09/12 (Week 4) | Conditionals (2.3-2.4) | |
| Tue 09/13 | Exam 1 Solutions | |
| Wed 09/14 | Truth Tables, Equivalence (2.5-2.6) | PS07: §2.3 (2,4,6,10), §2.4 (2,4) |
| Fri 09/16 | Quantifiers (2.7) | PS08 |
| Mon 09/19 (Week 5) | English to Logic (2.8-2.9) | PS09: §2.7 (2,6) |
| Tue 09/20 | Exercises | |
| Wed 09/21 | Negation & Inference (2.10-2.12) | PS10: 2.9 (2,6) |
| Fri 09/23 | Multiplication Principle (3.1-3.2) | PS11: §2.10 (2,4) |
| Mon 09/26 (Week 6) | Exam Review | |
| Tue 09/27 | Exam 2 (Ch. 2) | |
| Wed 09/28 | Addition/Subtraction/Permutations (3.3-3.4) | |
| Fri 09/30 | Counting Subsets (3.5-3.6) | PS12: §3.2 (4,6,10), §3.3 (4,8), §3.4 (4,12) |
| Mon 10/03 (Week 7) | Direct Proof (4.1-4.3) | PS13: §3.5 (6,8,12), §3.6 (4,8) |
| Tue 10/04 | Exercises | |
| Wed 10/05 | Cases (4.4-4.5) | |
| Fri 10/07 | Proof by Contrapositive (5.1-5.3) | PS14: §4 (2,6,14) |
| Mon 10/10 (Week 8) | Exam Review | PS15: §5 (8,12,20) |
| Tue 10/11 | Exam 3 (Ch. 3,4,5) | |
| (Wed 10/12) | (Fall Break) | |
| (Fri 10/14) | (Fall Break) | |
| Mon 10/17 (Week 9) | Exam 3 Solutions | |
| Tue 10/18 | Proof by Contradiction (6.1) | |
| Wed 10/19 | More Proofs by Contradiction (6.2-6.4) | |
| Fri 10/21 | Proving Non-Conditional Statements (7.1-7.4) | PS16: §6 (2, 8, 10) |
| Mon 10/24 (Week 10) | Practice Exam Solutions | PS17: §7 (2, 10, 16) |
| Tue 10/25 | Exercises/Review | |
| Wed 10/26 | (No class) | |
| Fri 10/28 | Exam 4 (Ch. 6,7) | |
| Mon 10/31 (Week 11) | Exam 4 Solutions | |
| Tue 11/01 | Proofs with Sets (8.1-8.2) | |
| Wed 11/02 | 8.3-8.4 | |
| Fri 11/04 | 9.1-9.3 | PS18: §8 (4, 20, 28) |
| Mon 11/07 (Week 12) | (no class) | PS19: §9 (2, 6, 30) |
| Tue 11/08 | Review | |
| Wed 11/09 | Exam 5 (Ch. 8,9) | |
| Fri 11/11 | Induction (10.1) | |
| Mon 11/14 (Week 13) | 10.2-10.3 | PS20: §10 (2,10) |
| Tue 11/15 | Exam 5 Solutions | |
| Wed 11/16 | 10.4,10.5 | |
| Fri 11/18 | 11.1-11.2 | PS21: §10 (18, 32) |
| Mon 11/21 (Week 14) | 11.3-11.4 | |
| Tue 11/22 | Practice | PS22: §11.1 (2, 10, 14), §11.2 (2, 6, 8) |
| (Wed 11/23) | (Thanksgiving Break) | |
| (Fri 11/25) | (Thanksgiving Break) | |
| Mon 11/28 (Week 15) | 11.4 (Partitions), 11.5, 12.1 | |
| Tue 11/29 | 12.2 | PS23: §11.3 (2), §11.4 (4, 6) |
| Wed 11/30 | Review | |
| Fri 12/02 | Exam 6 (Ch. 10,11) | |
| Mon 12/05 (Week 16) | 12.4 | PS24: §12.1 (2,4,6,8), §12.2 (4,6) |
| Tue 12/06 | Exam 6 Solutions | PS25: §12.2 (10), §12.4 (4,8,10) |
| Wed 12/07 | Review | |
| Mon 12/12 8:00 AM | Exam 7 (Final) |
Mental Health and Counseling Services: Monmouth College provides cost-free, professional mental health counseling to support you and to help you manage challenges that may impact your personal and academic success. The Counseling Center is located in the uppler level of Poling Hall (rooms 204 and 216), and the hours are Monday–Friday, 8:30 AM to 5:00 PM. For an appointment call<PHONE_NUMBER>, email<EMAIL_ADDRESS><EMAIL_ADDRESS>or<EMAIL_ADDRESS>or request an appointment directly by going to titanium.monmouthcollege.edu and clicking on “request an appointment.”
The Academic Support and Accessibility Services Office offers FREE resources to assist Monmouth College students with their academic success. Programs include supplemental instruction for difficult classes, drop-in and appointment tutoring, and individual academic coaching. The office is here to help students excel academically, since everyone can work toward better grades, practice stronger study skills, and mange their time better. Please email<EMAIL_ADDRESS>for assistance.
Accessibility Services: If you have a disability and/or medical/mental health condition, or had academic accommodations in high school or another college, you may be eligible for academic accommodations at Monmouth College under the Americans with Disabilities Act (ADA). Monmouth College is committed to equal educational access. To discuss any of the services offered, please call or meet with Jennifer Sanberg, Associate Director of Academic Success and Accessibility Services. The ASAS office on the first floor of the Hewes Library, opposite Einstein Bros. Bagels. The office can be reached at<PHONE_NUMBER> or via email at<EMAIL_ADDRESS>The The Office of Student Equity Inclusion & Community can be found on the first floor of the Champion Miller Center for Student Equity Inclusion & Community. The office provides support to meet the needs of underrepresented students and international students. Services include: personal and academic advising, help with transition to Monmouth College, information on scholarships, internships, and employment opportunities with the help of other campus offices, and intercultural programming. Office Phone Number:<PHONE_NUMBER>. Email: champion@monmouthcollege.edu


The uvm_recorder class provides a policy object for recording uvm_objects. The policies determine how recording should be done.
A default recorder instance, uvm_default_recorder, is used when the uvm_object::record is called without specifying a recorder.
| uvm_recorder | ||||
| The uvm_recorder class provides a policy object for recording uvm_objects. | ||||
| Class Hierarchy | ||||
| ||||
| Class Declaration | ||||
| ||||
| Variables | ||||
| tr_handle | This is an integral handle to a transaction object. | |||
| default_radix | This is the default radix setting if record_field is called without a radix. | |||
| physical | This bit provides a filtering mechanism for fields. | |||
| abstract | This bit provides a filtering mechanism for fields. | |||
| identifier | This bit is used to specify whether or not an object’s reference should be recorded when the object is recorded. | |||
| recursion_policy | Sets the recursion policy for recording objects. | |||
| Methods | ||||
| get_type_name | Returns type name of the recorder. | |||
| record_field | Records an integral field (less than or equal to 4096 bits). | |||
| record_field_real | Records an real field. | |||
| record_object | Records an object field. | |||
| record_string | Records a string field. | |||
| record_time | Records a time value. | |||
| record_generic | Records the name-value pair, where value has been converted to a string. |
integer tr_handle = 0
This is an integral handle to a transaction object. Its use is vendor specific.
A handle of 0 indicates there is no active transaction object.
uvm_radix_enum default_radix = UVM_HEX
This is the default radix setting if record_field is called without a radix.
bit physical = 1
This bit provides a filtering mechanism for fields.
The abstract and physical settings allow an object to distinguish between two different classes of fields.
It is up to you, in the uvm_object::do_record method, to test the setting of this field if you want to use the physical trait as a filter.
bit abstract = 1
This bit provides a filtering mechanism for fields.
The abstract and physical settings allow an object to distinguish between two different classes of fields.
It is up to you, in the uvm_object::do_record method, to test the setting of this field if you want to use the abstract trait as a filter.
bit identifier = 1
This bit is used to specify whether or not an object’s reference should be recorded when the object is recorded.
uvm_recursion_policy_enum policy = UVM_DEFAULT_POLICY
Sets the recursion policy for recording objects.
The default policy is deep (which means to recurse an object).
Returns type name of the recorder. Subtypes must override this method to enable the `uvm_record_field macro.
virtual function string get_type_name()
virtual function void record_field ( string name, uvm_bitstream_t value, int size, uvm_radix_enum radix = UVM_NORADIX )
Records an integral field (less than or equal to 4096 bits). name is the name of the field.
value is the value of the field to record. size is the number of bits of the field which apply. radix is the uvm_radix_enum to use.
virtual function void record_field_real ( string name, real value )
Records an real field. value is the value of the field to record.
virtual function void record_object ( string name, uvm_object value )
Records an object field. name is the name of the recorded field.
This method uses the recursion_policy to determine whether or not to recurse into the object.
virtual function void record_string ( string name, string value )
Records a string field. name is the name of the recorded field.
virtual function void record_time ( string name, time value )
Records a time value. name is the name to record to the database.
virtual function void record_generic ( string name, string value )
Records the name-value pair, where value has been converted to a string. For example:
recorder.record_generic("myvar",$sformatf("%0d",myvar));
The uvm_object class is the base class for all UVM data and hierarchical classes.
virtual class uvm_object extends uvm_void
The uvm_recorder class provides a policy object for recording uvm_objects.
class uvm_recorder extends uvm_object
This is an integral handle to a transaction object.
integer tr_handle = 0
This is the default radix setting if record_field is called without a radix.
uvm_radix_enum default_radix = UVM_HEX
Records an integral field (less than or equal to 4096 bits).
virtual function void record_field ( string name, uvm_bitstream_t value, int size, uvm_radix_enum radix = UVM_NORADIX )
This bit provides a filtering mechanism for fields.
bit physical = 1
This bit provides a filtering mechanism for fields.
bit abstract = 1
This bit is used to specify whether or not an object’s reference should be recorded when the object is recorded.
bit identifier = 1
Sets the recursion policy for recording objects.
uvm_recursion_policy_enum policy = UVM_DEFAULT_POLICY
Records an real field.
virtual function void record_field_real ( string name, real value )
Records an object field.
virtual function void record_object ( string name, uvm_object value )
Records a string field.
virtual function void record_string ( string name, string value )
Records a time value.
virtual function void record_time ( string name, time value )
Records the name-value pair, where value has been converted to a string.
virtual function void record_generic ( string name, string value )
The default recording policy.
uvm_recorder uvm_default_recorder = new()
The record method deep-records this object’s properties according to an optional recorder policy.
function void record ( uvm_recorder recorder = null )
The do_record method is the user-definable hook called by the record method.
virtual function void do_record ( uvm_recorder recorder )


Predicate Class
Used to define a 'where' predicate for an EntityQuery. Predicates are immutable, which means that any method that would modify a Predicate actually returns a new Predicate.
Methods
<ctor> Predicate
-
property
-
operator
-
value
Predicate constructor
Parameters:
-
property
StringA property name, a nested property name or an expression involving a property name.
-
operator
FilterQueryOp | String -
value
Object- This will be treated as either a property expression or a literal depending on context. In general, if the value can be interpreted as a property expression it will be, otherwise it will be treated as a literal. In most cases this works well, but you can also force the interpretation by making the value argument itself an object with a 'value' property and an 'isLiteral' property set to either true or false. Breeze also tries to infer the dataType of any literal based on context, if this fails you can force this inference by making the value argument an object with a 'value' property and a 'dataType' property set to one of the breeze.DataType enumeration instances.
Example:
var p1 = new Predicate("CompanyName", "StartsWith", "B");
var query = new EntityQuery("Customers").where(p1);
or
var p2 = new Predicate("Region", FilterQueryOp.Equals, null);
var query = new EntityQuery("Customers").where(p2);
and
-
predicates
Creates a 'composite' Predicate by 'and'ing a set of specified Predicates together.
Parameters:
-
predicates
Multiple Predicates | Array of Predicate multipleAny null or undefined values passed in will be automatically filtered out before constructing the composite predicate.
Example:
var dt = new Date(88, 9, 12);
var p1 = Predicate.create("OrderDate", "ne", dt);
var p2 = Predicate.create("ShipCity", "startsWith", "C");
var p3 = Predicate.create("Freight", ">", 100);
var newPred = Predicate.and(p1, p2, p3);
or
var preds = [p1, p2, p3];
var newPred = Predicate.and(preds);
and
-
predicates
'And's this Predicate with one or more other Predicates and returns a new 'composite' Predicate
Parameters:
-
predicates
Multiple Predicates | Array of Predicate multipleAny null or undefined values passed in will be automatically filtered out before constructing the composite predicate.
Example:
var dt = new Date(88, 9, 12);
var p1 = Predicate.create("OrderDate", "ne", dt);
var p2 = Predicate.create("ShipCity", "startsWith", "C");
var p3 = Predicate.create("Freight", ">", 100);
var newPred = p1.and(p2, p3);
or
var preds = [p2, p3];
var newPred = p1.and(preds);
The 'and' method is also used to write "fluent" expressions
var p4 = Predicate.create("ShipCity", "startswith", "F")
.and("Size", "gt", 2000);
create
-
property
-
operator
-
value
Same as using the ctor.
Parameters:
-
property
StringA property name, a nested property name or an expression involving a property name.
-
operator
FilterQueryOp | String -
value
Object- This will be treated as either a property expression or a literal depending on context. In general, if the value can be interpreted as a property expression it will be, otherwise it will be treated as a literal. In most cases this works well, but you can also force the interpretation by making the value argument itself an object with a 'value' property and an 'isLiteral' property set to either true or false. Breeze also tries to infer the dataType of any literal based on context, if this fails you can force this inference by making the value argument an object with a 'value' property and a 'dataType' property set to one of the breeze.DataType enumeration instances.
Example:
// so
var p = Predicate.create(a, b, c);
// is the same as
var p = new Predicate(a, b, c);
not
-
predicate
Creates a 'composite' Predicate by 'negating' a specified predicate.
Parameters:
-
predicate
Predicate
Example:
var p1 = Predicate.create("Freight", "gt", 100);
var not_p1 = Predicate.not(p1);
This can also be accomplished using the 'instance' version of the 'not' method
var not_p1 = p1.not();
Both of which would be the same as
var not_p1 = Predicate.create("Freight", "le", 100);
not
()
Returns the 'negated' version of this Predicate
Example:
var p1 = Predicate.create("Freight", "gt", 100);
var not_p1 = p1.not();
This can also be accomplished using the 'static' version of the 'not' method
var p1 = Predicate.create("Freight", "gt", 100);
var not_p1 = Predicate.not(p1);
which would be the same as
var not_p1 = Predicate.create("Freight", "le", 100);
or
-
predicates
Creates a 'composite' Predicate by 'or'ing a set of specified Predicates together.
Parameters:
-
predicates
Multiple Predicates | Array of Predicate multipleAny null or undefined values passed in will be automatically filtered out before constructing the composite predicate.
Example:
var dt = new Date(88, 9, 12);
var p1 = Predicate.create("OrderDate", "ne", dt);
var p2 = Predicate.create("ShipCity", "startsWith", "C");
var p3 = Predicate.create("Freight", ">", 100);
var newPred = Predicate.or(p1, p2, p3);
or
var preds = [p1, p2, p3];
var newPred = Predicate.or(preds);
or
-
predicates
'Or's this Predicate with one or more other Predicates and returns a new 'composite' Predicate
Parameters:
-
predicates
Multiple Predicates | Array of Predicate multipleAny null or undefined values passed in will be automatically filtered out before constructing the composite predicate.
Example:
var dt = new Date(88, 9, 12);
var p1 = Predicate.create("OrderDate", "ne", dt);
var p2 = Predicate.create("ShipCity", "startsWith", "C");
var p3 = Predicate.create("Freight", ">", 100);
var newPred = p1.or(p2, p3);
or
var preds = [p2, p3];
var newPred = p1.or(preds);
The 'or' method is also used to write "fluent" expressions
var p4 = Predicate.create("ShipCity", "startswith", "F")
.or("Size", "gt", 2000);


Which Simpsons Character Are You?
What's your favorite hobby?
Playing saxophone
Skateboarding
Beating Up Other Kids
How do you feel about school?
Where else am I going to pull my pranks?
Love it!
What's school?
What's your favorite food?
Whatever I can steal from the nerds
Slushies
Salad
What's your catch phrase?
If anyone wants me, I'll be in my room.
Eat my shorts!
Ha Ha!
Show my results!


Work Day Scheduler
a simple calendar app for scheduling your work day
-PAST-
-PRESENT-
-FUTURE-
9AM
10AM
11AM
12PM
1PM
2PM
3PM
4PM
5PM


| Property |
Description |
Data Type |
Required/Optional |
| manifest_id |
Filename of the manifest used to ship this sample. Example: E4412_PBMC.
|
<string>
|
optional
|
| request |
Assigns a request identifier (mandatory or optional) for the assay.
|
<string>
|
required
|
| assay_priority |
Priority of the assay as it appears on the intake form.
|
<string>
- Assay-1
- Assay-2
- Assay-3
- Assay-4
- Assay-5
- Assay-6
- Assay-7
- Assay-8
- Assay-9
- Assay-10
- Assay-11
- Assay-12
- Assay-13
- Assay-14
- Assay-15
- Other
|
optional
|
| assay_type |
Assay and sample type used. Example: Green-top tube - Plasma (Olink).
|
<string>
|
optional
|
| batch_number |
The number corresponding to the batch sent for this assay.
|
<integer>
|
optional
|
| box_number |
Box identifier for samples, if sample shipment container includes multiple boxes for each sample/assay type.
|
<integer>
|
optional
|
| assay_run_number |
Assay run number for samples received.
|
<integer>
|
optional
|
| courier |
Courier utilized for shipment.
|
<string>
|
optional
|
| tracking_number |
Air bill number assigned to shipment. Example:<PHONE_NUMBER>.
|
<string>
|
optional
|
| account_number |
Courier account number to pay for shipping if avaialable. Example: 45465732.
|
<string>
|
optional
|
| shipping_condition |
Type of shippment made.
|
<string>
- Frozen (Dry Ice)
- Frozen (Dry Shipper)
- Ambient (Ice Pack)
- Ambient
- Other
|
optional
|
| date_shipped |
Date of shipment.
|
<string> date
|
optional
|
| num_of_samples_shipped |
Count of specimens distributed by site.
|
<integer>
|
optional
|
| num_of_samples_good |
Number of Samples Received in Good Condition.
|
<integer>
|
optional
|
| num_of_path_report |
Number if pathology report received.
|
<integer>
|
optional
|
| ship_from |
Shipping from [free text: person or organization, address, phone number, email address.]
|
<string>
|
optional
|
| ship_to |
Shipping to [free text: person or organization, address, phone number, email address.]
|
<string>
|
optional
|


REVIEW: John Carpenter's Vampires By Luke Buckmaster<EMAIL_ADDRESS>Cast: James Woods, Daniel Baldwin, Sheryl Lee, Thomas Ian Griffith, Tim Guinee, Maximilian Schell Director: John Carpenter Producer: Sandy King Screenplay: Don Jakoby based on the novel "Vampire$" by John Steakley
Australian theatrical release: December 10, 1998
On the Buckmaster scale of 0 stars (bomb), to 5 stars (a masterpiece): 2 and a half stars
The most astonishing thing about John Carpenter's Vampires isn't that it gives a new spin on the classic legend, nor that its special effects are particularly glamorous or its acting well performed. It is how Village Roadshow managed to produce a twenty-eight-page press kit that amazes me. Full of juicy tidbits of information -- including the production crew's opinions on the sex life of vampires, and how none of the cast "were particularly crazy about being burned alive" -- the press kit provides just as many laughs as the movie. But are we laughing for the right reasons?
Probably not, given the nature of director John Carpenter's material - vampires. But in the cosmos of this film, garlic and crosses are futile against the blood-sucking enemy. The easiest way for slayer Jack Crow (James Woods) and his team to murder the undead is to drag 'em out into the sunlight. So you can imagine how they feel when they learn of the legendary Valek (Thomas Ian Griffith) - the first vampire in recorded history - and his plan to give vampires the power to walk in daylight. This plan involves the use of a mysterious religious artifact named the Berziers Cross, and an eerie ritual using the blood of a slayer.
If you're expecting a tale as entertaining as, say, From Dusk Till Dawn, or a story board as darkly comic as Blade, think again. Vampires is a "real" slayer flick, with only one intention: to showcase as many vampire hunts as possible, whilst still remaining within the borders of a basic narrative.
Trouble is, John Carpenter seems to forget that even horror films need well constructed action scenes. Even greater a problem is that killing vampires just doesn't seem enough of an idea to warrant a film, even though the screenplay was adapted from the novel Vampire$, by John Steakley. Valek's quest to give the vampires ultimate power is not much more than one of the screenplay's many plot props; a set up which deliberately helps builds up to a heroic climax.
In some ways, James Woods seems perfect for his role. His western macho man portrayal is simplistic and one dimensional, but strangely compelling. You get the feeling that this is the type of role that could have gone to Kurt Russel, or Clint Eastwood a couple of decades ago. Another interesting screen persona is played by Sheryl Lee, who is a hooker that gets bitten by Valek, and is irresistible to watch as her transformation from human to vampire takes place.
Even if Vampires is nothing more than an average genre flick, at least John Carpenter has been smart enough not to take himself too seriously. The gothic western setting never seems entirely believable, nor totally unimaginable. It's just a place that suits Crow's belt and jacket, and serves as a modern surrounding to an old fashioned, often-hilarious tale. But are we laughing for the right reasons?
Email<EMAIL_ADDRESS>to subscribe to my newsletter (unless, of course, you already have) or<EMAIL_ADDRESS>for any inquiries or feedback
Read more of my reviews at Alphalink Movies: http://moviezone.alphalink.com.au
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Newsletters
Here's a list of our newsletters detailing our Section's activities in the previous years. Click on each link to know about the respective session.
Newsletter for 2015-16
Newsletter for 2014-15
Newsletter for 2013-14


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351_jw5865.py
class Solution:
def longestDiverseString(self, a: int, b: int, c: int) -> str:
heap = []
if a != 0:
heapq.heappush(heap, (-1*a, 'a'))
if b != 0:
heapq.heappush(heap, (-1*b, 'b'))
if c != 0:
heapq.heappush(heap, (-1*c, 'c'))
ans = ''
wait = collections.defaultdict(lambda: [])
t = 0
while len(heap) != 0 or t in wait:
for w in wait[t]:
heapq.heappush(heap, w)
x, y = heapq.heappop(heap)
x = -1 * x
ans += y
if x - 1 == 0:
t += 1
continue
if len(ans) >= 2 and ans[-2] == y:
wait[t+2].append((-1*(x-1), y))
else:
heapq.heappush(heap, (-1*(x-1), y))
t += 1
return ans


'Chair girl' back in court as lawyer says case is close to resolution
by Kayla Goodfield, Multi-Platform Writer, CTV News TorontoThe case of a woman accused of throwing a chair off a downtown Toronto high-rise balcony is expected to return to court this morning.
The February incident, which was caught on camera and shared widely online, led to 19-year-old Marcella Zoia being charged with mischief endangering life, mischief endangering property under $5,000 and common nuisance.
The video showed a young woman launch a chair off a balcony over a busy highway.
Following the mass-circulation of the video, Toronto police urged the woman to come forward and identify herself.
Zoia turned herself in to officials a few days later.
Last month, the woman’s lawyer Gregory Leslie said the case was close to a resolution.
Zoia is expected to appear in a downtown Toronto courtroom at 10 a.m.


Sarah Jessica-Parker confirms original cast on board for ‘Hocus Pocus’ sequel
The original Sanderson sisters are set to put a spell on you once more
Sarah Jessica-Parker appears to have confirmed that the original cast of 1993 cult comedy Hocus Pocus – Bette Midler, Kathy Najimy and herself – have all agreed to star in the proposed sequel.
The former Sex and the City star posted a picture of the trio from the original film on Instagram on Friday (November 1). One fan asked the actor in the comments: ‘any chance of a sequel?!’
Jessica-Parker replied: ‘we have all said yes. Now we wait. X’
The news will come as a relief to fans of the original story, as there was previously some doubt as to whether Midler, Jessica-Parker and Najimy would appear in the new Hocus Pocus film – prompting a slew of unimpressed reactions on social media.
Based on a story by Mick Garris and David Kirschner, the original film followed a comedic trio of witches who are inadvertently resurrected by a boy struggling to fit in at his new hometown of Salem.
Speaking to Entertainment Tonight, Bette Midler joked about waiting to be asked to reprise the role, expected to appear on streaming service Disney+. “I hope they get to me before I’m a corpse,” she quipped.
“We wanna fly again. I hope Disney+ is a big success and I hope we get to do it, because she is one of my favourite characters… I can’t wait to read the script. We’re gonna see what happens,” Midler said in the interview.
Najimy, who played Mary Sanderson in the original Hocus Pocus, said she hoped to at least do a cameo in the new project. “Here’s the honest answer: Sarah and Bette and I all have a million projects and things that we’re into, so I don’t know if they’re gonna offer us [roles]. I don’t know if the worlds are going to collide so that we could all three do it at the same time.
“But I’m happy that it’s happening, because the fans are really rabid and they really want it. If we’re not all available to star in it, I think it would be so great to do a cameo. I think that’d be really fun,” the actor added.


Leaflet Control Layers extended for group of layers and icons legend. Other useful stuff for Web Mapping...


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Installing the new version will not make it available for use. After installation, you can configure and test the new version and start using it when ready.
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Abstract: Joy is a functional programming language which is not based on the application of functions to arguments but on the composition of functions. The language makes extensive use of combinators which perform the role of higher order functions. The algebra of Joy programs can be used to express formal properties of many first and second order functions without using variables ranging over values or over functions. Some of these properties are idempotency, inverses, converses, commutativity, symmetry, associativity, homomorphisms and distribution. The paper also gives several analogues of concepts from category theory.
Keywords: functional programming, function composition, algebra of programs, monoids, categories, functors, natural transformations, monads.
Q1
and Q2
are programs which denote the same function and P
and R
are other programs, then the two
concatenations P Q1 R
and P Q2 R
also
denote the same function. In other words, programs Q1
and Q2
can replace each other in concatenations. This
can serve as a rule of inference for rewriting.
As premises one needs axioms such as in the first three lines below, and definitions such as in the fourth line:
(+) 2 3 + == 5 (dup) 5 dup == 5 5 (*) 5 5 * == 25 (def square) square == dup *A derivation using the above axioms and the definition looks like this:
2 3 + square == 5 square (+) == 5 dup * (def square) == 5 5 * (dup) == 25 (*)The comments in the right margin explain how a line was obtained from the previous line. The derivation shows that the expressions in the first line and the last line denote the same function, or that the function in the first line is identical with the function in the last line.
Consider the following equations in infix notation: The first says
that multiplying a number x
by 2 gives the same result as
adding it to itself. The second says that the size of a
reversed list is the same as the size
of the
original list.
2 * x = x + x size(reverse(x)) = size(x)In Joy the same equations would be written, without variables, like this:
2 * == dup + reverse size == size
Other equivalences express algebraic properties of various operations.
For example, the predecessor pred of the successor
succ of a number is just the number itself. The
conjunction and of a truth value with itself gives just the
truth value. The less than relation <
is the converse of
the greater than relation >
. Inserting a number with
cons into a list of numbers and then taking the
sum of that gives the same result as first taking the sum
of the list and then adding the other number.
In conventional notation these are expressed by
pred(succ(x)) = x x and x = x x <y = y > x sum(cons(x,y)) = x + sum(y)In Joy these are expressed without variables
succ pred == id dup and == id < == swap > cons sum == sum +Some properties of operations have to be expressed by combinators. One of these is the dip combinator which expects a program on top of the stack and below that another value. It saves the value, executes the program on the remainder of the stack and then restores the saved value.
In the first example below, the dip
combinator is used to
express the associativity of addition. Another combinator is the
app2 combinator which expects a program on top of the stack
and below that two values. It applies the program to the two values.
In the second example below it expresses one of the De Morgan laws.
In the third example it expresses that the size
of two
lists concatenated is the sum of the size
s of
the two concatenands. The last example uses both combinators to
express that multiplication distributes (from the right) over
addition. (Note that the program parameter for app2
is
first constructed from the multiplicand and *
.)
[+] dip + == + + and not == [not] app2 or concat size == [size] app2 + [+] dip * == [*] cons app2 +
The remainder of this paper is organised as follows: The next five sections give detailed examples of algebraic laws which Joy operators satisfy. All of these laws are well known when expressed in familiar notation, what is new here is that they can be expressed in Joy notation without the use of implicitly or explicitly universally quantified variables. Then follow three sections using concepts from category theory, but no previous knowledge is assumed.
f(x)
is said to be idempotent
if applying it once is "as good as" applying it twice. In
conventional notation this means that for all x
f(f(x)) = f(x)For example, the function abs which returns the absolute value of a number is idempotent. Another one is the function defined on lists or strings which returns a sorted version - sorting an already sorted sequence makes no difference.
abs(abs(n)) = abs(n) sort(sort(s)) = sort(s)Composition can be used to express that stack operations are idempotent. The following express the idempotency of abs and sort:
abs abs == abs sort sort == sortAnother idempotent Joy function, one which has no counterpart in conventional notation, is the newstack function, it throws away anything that is on the stack. Doing it twice in succession gives the same result as doing it once:
newstack newstack == newstack
The remainder of this section illustrates the use of the identity
function in Joy algebra. This function is denoted by the symbol
id. It has the property that for all programs
P
,
id P == P == P id
Let f(x)
be a unary function. Another unary function
g(x)
is said to be its inverse if for all
x
g(f(x)) = xFor example, the predecessor function on integers is the inverse of the successor function on integers: for all integers
x
pred(succ(x)) = xIt may or may not be that if one function is the inverse of a second then the second is the inverse of the first. This is true of the predecessor and successor functions when defined on integers, but not when defined on natural numbers. The identity function can be used to express that one function is the inverse of another and that certain values are unit elements.
The atomic program succ denotes a function which takes a
stack as argument and yields a stack as value. The argument stack has
to have an integer (or a character) on top. The value stack is like
the argument stack except that the integer (or character) has been
incremented by 1. The semantics for pred is analogous, it
decrements the integer (or character). The following express that the
functions denoted by the symbols succ
and
pred
are inverses of each other:
pred succ == id succ pred == id
The cons function expects a list on top of the argument stack. Below that it expects another value. The value that is returned is another stack which is like the argument stack except that the two top elements of the argument stack have been replaced by a new list which has the value inserted into it at the front. The uncons function undoes this. It expects a non-empty list and leaves the first and the rest of the list. The two functions are inverses of each other:
cons uncons == id uncons cons == idIt is worth pointing out this cannot be expressed in conventional notation because there the
uncons
operation makes no
sense. Actually, both functions are polymorphic in that instead of
lists they can operate on strings or on sets The two equations still
hold applied to strings. Only the right equation holds for sets.
The symbols pairlist, pairstring and
pairset denote functions which expect two potential members
of lists, strings or sets on top of the stack. They return a new
stack with the two members replaced by a single list, string or set.
The polymorphic unpair function is their inverse, but not
vice versa. Since unpair
leaves two results, the
following have no counterpart in conventional notation.
pairlist unpair == id pairstring unpair == id pairset unpair == id
Some functions are inverses of themselves. Examples of
self-inverse functions are the Boolean negation function and
the list reversal function: for all Boolean values b
and
for all lists l
not(not(b)) = b reverse(reverse(l)) = lIn Joy the two unary operators not and reverse are polymorphic. The
not
operator expects a truth value
or a set on top of the stack and returns a stack which has the
complementary truth value or set on top of the stack. The
reverse
operator expects a list or a string on top of the
stack and returns a stack which has the reversal the list or string on
top of the stack. The two functions are self-inverses, and this is
expressed by
not not == id reverse reverse == id
Let f(x,y)
be a binary function. A constant
c
is called a left or right unit element if the
first or the second equation holds for all x
f(c,x) = x f(x,c) = xLeft and right unit elements often coincide, and then they are just called unit elements. In particular, this is true for the unit elements of commutative functions. For example, 0 is the unit element for addition, and 1 is the unit element for multiplication. In conventional infix notation:
n + 0 = n = 0 + n n * 1 = n = 1 * n
The identity function can also be used to express that certain
literals are right unit elements for binary operations: 0 for
addition, 1 for multiplication, the empty string
""
or the empty list []
for
concatenation, the truth value false and the empty
set {}
for logical disjunction and set union, and
the truth value true for logical conjunction.
0 + == id 1 * == id "" concat == id [] concat == id false or == id {} or == id true and == id
dup
and pop
operators in Joy algebra. The Joy operator dup expects one
value on top of the stack and pushes a duplicate on top. For example,
42 dup == 42 42Both sides of the equation denote compositions of two functions. On the left the first function pushes a number and the second makes a duplicate of the top element. On the right the two functions are the same, each pushes a number. The equation says that the function on the left is identical to the one on the right. Both functions are defined for all stacks, and both return a stack which is like the argument stack except that two copies of the number 42 have been pushed.
A binary function f(x,y)
is called idempotent if
for all x
f(x,x) = xTwo examples are the Boolean conjunction and disjunction operations: for all
b
b and b = b b or b = bIn Joy the
dup
operator can express idempotency of the
Boolean operations and and or which are defined
for truth values and for sets. It can also express the idempotency of
the numeric binary min and max operators:
dup and == id dup or == id dup min == id dip max == id
The Joy operator pop expects one value on top of the stack and removes it. For example
17 42 pop == 17On the left the composition of three functions first pushes two numbers and then pops the second. On the right the function just pushes the first number. The two functions are identical since for all argument stacks they have the same result stack.
Let f(x,y)
be a binary function. A constant
c
is called a left or right zero element of
f(x,y)
if the first or second equation holds for all
x
:
f(c,x) = c f(x,c) = cFor example, the number zero is a left and right zero element for multiplication, and in conventional infix notation the laws looks like this:
0 * n = 0 n * 0 = 0The
pop
operator can also be used to express that
particular values are zero elements for binary operations: 0 for
multiplication, false
and the empty set {}
for logical conjunction and set intersection, and true
for
logical disjunction.
0 * == pop 0 false and == pop false {} and == pop {} true or == pop true
The two operators dup
and pop
are related by
the identity
dup pop == idThe
pop
operator can also be used to express the
arity of a function, the number of parameters which it
expects. For example, numbers are nullary, the successor function is
unary, and addition is binary. There is no way to express this in
conventional notation. In Joy it is expressed by:
42 pop == id succ pop == pop + pop == pop popSimilar laws express that some operators return two results on the stack:
uncons pop pop == pop dup pop pop == pop
swap
operator in
Joy algebra. The Joy operator swap expects two values of
any type on top of the stack; its effect is to interchange them. The
operator is its own inverse:
swap swap == id
Let f(x,y)
be a binary function. Another binary function
g(x,y)
is its converse if for all x
and y
f(x,y) = g(y,x)For example, the numeric comparison relation
<
has as its
converse the relation >
:
(i <j) = (j > i)In Joy notation the
swap
operator can express that
comparison predicates <
and <=
have as their
converses the predicates >
and >=
by the
laws
swap > == < swap >= == <=The operator swons is similar to
cons
, it
expects an aggregate and a new value on top of the stack. It leaves a
new aggregate with the value inserted. But whereas cons
expects the aggregate on top and the value below, swons
expects them in the opposite order, the value on top and the aggregate
below. It follows that swons
is the converse of
cons
. In the same way, a binary string or list operation
swoncat is defined to be the converse of
concat
.
swap cons == swons swap concat == swoncat
One function is the converse of a second function if and only if the
second is the converse of the first. This says that converseness is a
symmetric relation. In Joy it is expressed by the following: for all
programs P
and Q
swap P == Q if and only if swap Q == PFrom this rule and the previous equalities it follows that
swap < == > swap <= == >= swap swons == cons swap swoncat == concat
A binary function f(x,y)
is commutative if it is
its own converse - if for all x
and y
f(x,y) = f(y,x)For example, addition of numbers is commutative, for all integers
x
and y
i + j = j + iIn Joy the
swap
operator can express that a function is
commutative.
swap + == + swap * == * swap and == and swap or == or swap max == max swap min == minTwo sorted sequences can be combined with the merge operator to form one new sorted sequence. Unlike concatenation, merging is commutative:
swap merge == merge
A function which yields a truth value is often called a
predicate. Commutative predicates are often called
symmetric. For example, the identity relation
=
, a binary predicate, is commutative or symmetric.
Another is the equal predicate which tests lists for
identity, including sublists and their sublists. In conventional
notation, for all integers or lists x
and y
(i = j) = (j = i) equal(x,y) = equal(y,x)Turning these concepts on themselves, the converse relation is symmetric: for all functions
f
and g
(g is the converse of f) = (f is the converse of g)The same is not true for the inverse relation. The
swap
operator can express that a binary predicate is symmetric.
The following express that =
and equal
are
symmetric:
swap = == = swap equal == equalWith
swap
one can express that elements are left
unit elements for binary operations. In the case of operations
such as addition and the Boolean operations this already follows from
their commutativity. On the other hand, concatenation of strings or
lists is not commutative, but the empty string and the empty list are
both right and left unit elements for concatenation. They are also
both right unit elements for merge.
0 swap + == id 1 swap * == id false swap or == id {} swap or == id true swap and == id "" swap concat == id [] swap concat == id "" swap merge == id [] swap merge == id
Some operators leave two elements on top of the stack, and two such
operator may be related in the sense that they just leave the elements
in a different order. This can also be expressed by
swap
:
uncons swap == unswons unswons swap == unconsThere is even one operator which is related to itself in this way, and that is
dup
:
dup swap == dup
Two operators related to swap
are rollup and
rolldown. The rollup
operator moves the third
and second element on the stack into second and first position, and it
moves the original first element into third position. The
rolldown
operator moves the second and first element on
the stack into third and second position, and it moves the original
third element into first position. They can express laws such as
rolldown concat concat == concat swoncat rollup swoncat concat == swoncat swoncat rollup merge merge == merge mergeTheir arities are expressed by
swap pop pop == pop pop rollup pop pop pop == pop pop pop rolldown pop pop pop == pop pop pop
This section illustrates the use of the dip
combinator in
Joy algebra.
The three previous sections have shown how a few Joy operations can express a variety of well-known laws. In the sections to follow more difficult Joy concepts will be needed. These resemble higher order functions, but like everything else in Joy they really are just functions from stacks to stacks. They differ from what are called the operators in that they expect on top of the stack not just a passive datum, but a quoted program which they execute. In accordance with an older terminology they are here called combinators.
One of these is the dip combinator. It expects a quoted program on the top of the stack, and below at least one value of any type. During execution it removes the program and the value from the stack and saves them. Then it executes the program on the remainder of the stack. Finally it restores the saved value to the top of the stack. In most applications the program will be pushed just before the combinator is to be applied. The combinator is useful for doing something to the stack without disturbing the top value.
Here is an example:
1 2 3 4 + * 5 == 1 14 5 1 2 3 4 5 [+ *] dip == 1 14 5In the first line on the left the 3 and the 4 are immediately added, the result is multiplied by the 2 to give 14, and then the 5 is pushed on top. In the second line the 5 is pushed immediately after the 4, and consequently it is not possible to add the 3 and 4 without popping the 5 first. So, the program
[+ *]
is pushed and then
executed by dip
. The results are the same as those in
the two (identical) right sides.
A binary function f(x,y)
is said to be
associative if the result of applying it twice to three
values is independent of the order of application:
f(x,f(y,z)) = f(f(x,y),z)For example, addition of numbers is associative:
i + (j + k) = (i + j) + kIf
g(x,y)
is the converse of an associative
f(x,y)
, then g(x,y)
is also associative.
In Joy the dip
combinator can be used to express
associativity:
[+] dip + == + + [*] dip * == * * [and] dip and == and and [or] dip or == or or [max] dip max == max max [min] dip min == min min [concat] dip concat == concat concat [swoncat] dip swoncat == swoncat swoncat [merge] dip merge == merge merge
The following law expresses that the dip
combinator
leaves one value unchanged:
dip pop == [pop] dip i
app2
combinator
in Joy algebra.
The app2 combinator expects a quoted program on top of the stack, and below that two data parameters. As with all combinators, the program will be executed, in this case twice. In case the program computes a unary function, the effect is to replace the two data parameters by two corresponding values of that function. The two evaluations could be done in parallel. The more general case where the program does not denote a unary function is described further down.
Let f(x1,x2)
be a binary function defined on a type
X
, and let g(y1,y2)
be a binary function
defined on a type Y
. Let h(x)
be a function
from X
to Y
. Then h(x)
is a
homomorphism from X
and its binary function to
Y
and its binary function when the following holds for
all x1
and x2
:
h(f(x1,x2) = g(h(x1),h(x2))One example is the logarithm function which maps logarithms of products onto sums of logarithms. Two other examples are the doubling function which maps integers with addition into even integers with addition, and the squaring function which maps naturals with multiplication into square naturals with multiplication and the size (or length) of string function which maps the size of concatenations onto sums of sizes. The De Morgan laws are another example.
log(x * y) = log(x) + log(y) double(x + y) = double(x) + double(y) square(x * y) = square(x) * square(y) size(concat(x,y)) = size(x) + size(y) not(p and q) = not p or not q not(p or q) = not p and not q
In Joy the app2
combinator can be used to express
homomorphism laws, and these all take the form:
f h == [h] app2 gSome such laws are
+ double == [double] app2 + * square == [square] app2 * max succ == [succ] app2 max concat size == [size] app2 + concat sum == [sum] app2 + concat product == [product] app2 * concat charset == [charset] app2 orIn the above, charset transforms a string of characters into a set of characters, and the
or
operator computes
set union in this case. Another homomorphism is the sort
operator which maps unordered lists under concatenation onto ordered
lists under a binary merge operator which preseves
ordering:
concat sort == [sort] app2 merge
The app2
combinator can also be used to express the
familiar De Morgan laws for Boolean algebra and a (perhaps surprising)
isomorphic pair of laws for strings or lists:
and not == [not] app2 or or not == [not] app2 and concat reverse == [reverse] app2 swoncat swoncat reverse == [reverse] app2 concat
Laws like the above generalise to distribution laws. In these the unary function is replaced by a new binary function, and for each element in the domain a unary function can be defined from the new binary function by letting one parameter be the given element. It is useful to distinguish right distribution and left distribution.
A binary function f(x,y)
distributes from the right over
another binary function g(x,y)
if the following holds:
f(g(x,y),z) = g(f(x,z),f(y,z))In arithmetic we have the familiar example of multiplication distributing from the right over addition. In Boolean algebra the conjunction and disjunction operators distribute from the right over each other. Here is the arithmetic law:
(i + j) * k = (i * k) + (j * k)
The app2
combinator can also express right
distribution laws. In each case there are three data parameters
on the stack, and the two ways of applying two functions are
equivalent. The one way is to apply the one function to the second
and third parameters (using the dip
combinator) and then
to apply the distributing function to the result and the first
parameters. The other way is to use the first parameter and the
distributing function to make a constructed program that
computes a unary function, use app2
to compute its values
for the second and third data parameters and to combine the two values
with the other function.
[+] dip * == [*] cons app2 + [and] dip or == [or] cons app2 and [or] dip and == [and] cons app2 or
A binary function f(x,y)
distributes from the left over
another binary function g(x,y)
if the following holds:
f(x,g(y,z)) = g(f(x,z),f(y,z))In arithmetic multiplication also distributes from the left over addition:
i * (j + k) = i * j + i * kThe
app2
combinator can also be applied to a quoted
program which does not compute a unary function, but accesses data
elements further down in the stack. In the examples below, these
elements have to be explicitly deleted later on, by [pop]
dip
. It can be used to express left distribution
laws.
+ * == [*] app2 + [pop] dip or and == [and] app2 or [pop] dip and or == [or] app2 and [pop] dip
Apart from app2
there are similar combinators
app1 and app3. Each expects a program
[P]
on top of the stack and below that 1, 2 or 3 further
parameters and produces 1, 2 or 3 values. Some pertinent laws are
[succ] app1 == succ [not] app1 == not [pop] dip app1 == app2 pop [swap] dip app2 == app2 swap [dup] dip app2 == app1 dupThe arities of these combinators are expressed by
app1 pop == pop pop app2 pop pop == pop pop pop app3 pop pop pop == pop pop pop pop
There is a sense in which one might say that an integer has two parts: a sign and an absolute value. When the two parts are multiplied, the result is the same as the original. In the same way, a non-empty list has two parts, its first and its rest. When the first is consed into the rest, the result is the same as the original list. In conventional notation this might be expressed as
sign(x) * abs(x) = x cons(first(x),rest(x)) = xThe same may be expressed in Joy notation using the
dip
combinator:
dup [sign] dip abs * == id dup [first] dip rest cons == id
The laws look somewhat cleaner when expressed in terms of another combinator. The cleave combinator expects two programs and below that another item. It applies both programs to produce two results, for example
5 [pred] [dup *] cleave == 4 25The earlier laws about parts and wholes can then be expressed like this:
[sign] [abs] cleave * == id [first] [rest] cleave cons == id
The combinator split applied to a list and a test predicate produces two lists, those members of the original list which pass the test and those with fail. For any predicate, a list will have two parts which can be merged to reconstitute the original list. In Joy notation:
[sort] dip split merge == pop sortThe law cannot be expressed in conventional notation because
split
produces two results.
A category consists of a collection of objects and for any two objects a collection of morphisms, each having the one object as their source and the other object as their target. In many categories the objects are just sets, or they are sets with structure - algebras. Then the morphisms are unary functions from sets to sets, or they are homomorphisms from algebras to algebras. For any object the morphisms must include an identity morphism with that object as source and target. Often there will be other morphisms with that object as source and target. For any object and two morphisms having a given object as target and source respectively, there must be a composite morphism having as source the source of the one component and as target the target of the other.
This composition of morphisms must be associative, with identity morphisms as left and right unit elements. These requirements are satisfied for categories of sets and functions and for categories of algebras and homomorphisms. But there are many categories that are quite different. One kind of example are monoids: an associative binary operation over a set which includes a left and right unit element. Here the category consists of just one object (which is of no interest), but many morphisms, the elements of the monoid. There are many other kinds of categories which are different again.
Categories deal with two sorts of things, objects and morphisms. So
they are two-sorted algebras. Between categories there are morphisms
called functors. These take objects and morphims of one
category into objects and morphisms of another category. In computer
science the most familiar functors are the type constructors.
They take integers, characters, truth values and so on into
LIST
s of integers, LIST
s of characters,
SET
s of integers and so on. The functors must
also take integer functions such as squaring into corresponding
functions on LIST
s or SET
s of integers.
In computing circles the corresponding functions are usually written
map(square,L)
, for a list L
. In category
theory the same symbol is used for objects and morphisms, so the
examples are written LIST(integer)
and
LIST(square)
. In Joy there is no explicit type notation
at all, and map is just one of many combinators. Programs
to compute the list of squares of a given list can be written in
either of these two ways:
[square] map [dup *] map
Between any two functors F
and G
there can
be functions called natural transformations. These take as
arguments the values of F
and G
at their
objects. A function n
is natural if for all morhisms
m
in the domains of F
and G
the
following holds for all x
:
n(F(m)(x)) = G(m)(n(x))Initially we shall only be concerned with the case where
F
and G
are the same functor
LIST
. Then an example of a natural transformation from
lists to lists is the reverse function: for all functions
f
and lists L
reverse(LIST(f)(L) = LIST(f)(reverse(L))or in conventional notation
reverse(map(f,L)) = map(f,reverse(L))In Joy algebra the naturality of
reverse
is expressed by
[reverse] dip map == map reverse
In computer science natural transformations are often called polymorphic functions, in the case of lists they are independent of the type of the elements of the lists. Four other naturality laws, expressed in conventional notation:
map(f,rest(L)) = rest(map(f,L)) f(first(L)) = first(map(f,L)) map(f,concat(L1,L2)) = concat(map(f,L1),map(f,L2)) map(f,cons(x,[])) = cons(f(x),[]) map(f,unitlist(x)) = unitlist(f(x))The last two laws of course say the same thing. In Joy these would be expressed by
[rest] dip map == map rest [first] dip i == map first [concat] dip map == [map] cons app2 concat [[] cons] dip map == i [] cons [unitlist] dip map == i unitlistNote that in the third equation on the right the
app2
combinator has to use a constructed program. The last two
laws again say the same thing.
Somewhat more difficult is the naturality of cons. In conventional notation this is expressed by
map(f,cons(x,L)) = cons(f(x),map(f,L))and in Joy notation by
[cons] dip map == dup [dip] dip map consThis is so complex that a step-by-step verification is called for. Let
L
and x
be the list and the additional
member. Let [F]
be a program which computes the function
f
. Let x'
be the result of applying
f
to x
, and let L'
be the
result of applying f
to all members of L
.
The proof of the equivalence of the LHS and the RHS consists in
showing that both reduce to the same program. For the LHS we have:
x L [F] [cons] dip map LHS == x L cons [F] map (dip) == [x L] [F] map (cons) == [x' L'] (map)For the RHS:
x L [F] dup [dip] dip map cons RHS == x L [F] [F] [dip] dip map cons (dup) == x L [F] dip [F] map cons (dip) == x' L [F] map cons (dip) == x' L' cons (map) == [x' L'] (cons)The two sides reduce to the same program, so they denote the same function.
A similar equation is the following:
map == [uncons] dip dup [dip] dip map consBut note that this is not suitable as a definition, since the RHS only applies to non-empty lists. The following is a suitable recursive definition:
map == [ pop null ] [ pop ] [ [uncons] dip dup [dip] dip map cons ] ifte
The fact that map
does not change the number of elements
in a list is expressed in conventional notation by
size(map(f,L)) = size(L)and in Joy notation by
map size == pop size
An important combinator for any aggregate is filter, which
expects an aggregate and below that a quotation which implememnts a
predicate. It returns an aggregate of the same type as the parameter
containing only those members for which the predicate yielded
true
. Given two aggregates, it does not matter whether
they are first combined and then filtered, or first filtered
separately and then combined. For sequences the law is this:
[concat] dip filter == [filter] cons app2 concatFor sets the combining operator has to be
or
instead of
concat
.
Another law concerns passing an aggregate first through one filter and then passing the result through another filter. Passing the aggregate through the conjunction of these filters produces the same result. The conjoin operator takes two quoted predicates and returns one quoted predicate which is their conjunction.
[filter] dip filter == conjoin filter
The following laws concern the sum
s and
product
s of lists of integers:
cons sum == sum + sum == uncons sum + cons product == product * product == uncons product *(Only the equations on the left could be expressed in conventional notation.)
This holds:
P == uncons Q iff cons P == Q
LIST
there are other functors such as SET
. So there is the
type SET(integer)
, the function SET(square)
which maps a set of integers into the set of their squares, and
similarly for other integer functions. Much of what was said about
lists and their natural transformations has counterparts for sets and
their natural transformations. In Joy there are several
implementations of set types. The simplest is in terms of
bitstrings with potential elements 0
.. 31
,
such sets are written in curly braces, as in {1 3 5}
.
Values of this type can be manipulated by the combinator
map
and the operators first
,
rest
and cons
. Instead of the operator
concat
the set union operator or applies. The
naturality of these operators is expressed by
[rest] dip map == map rest [first] dip map == map first [or] dip map == [map] cons app2 or [{} cons] dip map == i {} cons [cons] dip map == dup [dip] dip map cons
Now we have two functors, LIST
and SET
.
Lists have order and may have repetitions, sets have neither. A
useful function from lists to sets is the function elements
which removes order and repetitions. For example, in Joy notation
[ 3 1 5 1 ] elements == { 1 3 5 }It makes no difference whether the set of elements of a list is taken first and then the set is mapped through a function, or whether the list is first mapped through the same function and then the set of elements is taken. This is the naturality of the
elements
function, expressed by
[elements] dip map == map elementsFor example:
[ 3 1 5 1 ] [dup *] [elements] dip map == [ 3 1 5 1 ] elements [dup *] map == { 1 3 5 } [dup *] map == { 1 9 25 }and
[ 3 1 5 1 ] [dup *] map elements == [ 9 1 25 1 ] elements == { 1 9 25 }
Halfway between lists and sets are multisets or bags; these
have no order but may have repetitions. A BAG
functor
would be similar to LIST
and SET
, and there
would be natural transformations from bags to bags, from lists to
bags, and from bags to sets. Currently Joy does not have an
implementation of bags.
A list can have as its members other lists, for example lists of
integers. Formally these are of type
LIST(LIST(integer))
. This uses the LIST
functor composed with itself: LIST
°
LIST
. Such a list can be mapped through a function by
mapping each sublist, for example
[[1 2 3][4 5]] [[dup *] map] map == [[1 4 9][16 25]]Here the second
map
is applied to the whole list, the
first or inner map
is applied to the sublists.
Alternatively a combinator mmap can be defined by
mmap == [map] cons mapand then one can write
[[1 2 3][4 5]] [dup *] mmap == [[1 4 9][16 25]]
Whereas a list is one-dimensional, a matrix is two-dimensional. Matrices can be implemented as lists of lists, and the sublists can be interpreted either as the rows or the columns. One important operation on matrices is the interchange of rows and columns. The transpose operator does just that:
[[1 2][3 4]] transpose == [[1 3][2 4]]Transposition is another polymorphic function or natural transformation for matrices. It does not matter whether a matric is first transposed and then mapped elementwise through a function, or whether it is first mapped and then transposed.
[transpose] dip mmap == mmap transpose
The operator zip will transform two lists of the same length into a list of pairs, for example
[1 2 3] [4 5 6] zip == [[1 4][2 5][3 6]]The
zip
operator can be defined by
zip == [] cons cons transposeThe
zip
function is natural, zip
ping the two
lists and then mmap
ing has the same effect as
map
ping and then zip
ping:
[zip] dip mmap == [map] app2 zip
A similar naturality law holds for the cartproduct operator which produces the cartesian product of two aggregates which do not have to be of the same type:
[cartproduct] dip mmap == [map] app2 cartproduct
Another useful datatype is that of trees, also called
recursive lists. A tree of integers is either an integer or
a list of trees of integer. A proper tree is a list of
trees. The type gives rise to a functor TREE
, with the
data type TREE(integer)
and mapping functions such as
TREE(square)
. In Joy the combinator for tree mapping is
treemap. Most of the operations on lists also apply to
proper trees. Reversal can be done by reverse
just at
the top level, or by treereverse all the way down into all
sublists. Some naturality laws are:
[reverse] dip treemap == treemap reverse [treereverse] dip treemap == treemap treereverse [rest] dip treemap == treemap rest [first] dip i == treemap first [[] cons] dip treemap == treemap [] cons
Proper trees can be treeflattened to form a one-level list. For example
[ [1 [2 3] [] 4] [5] ] treeflatten == [ 1 2 3 4 5 ]The
treeflatten
ing function is a natural transformation
between the TREE
and LIST
functors, the
order of treeflattening and mapping does not matter:
[treeflatten] dip map == treemap treeflattenThe following also holds:
treereverse treeflatten == treeflatten reverse
A bare tree is either the empty list []
or it is
a list of bare trees. Formally there is a functor
BARETREE
, and for (degenerate) functions which can only
take []
as parameters BARETREE(f)
maps bare
trees with contained []
into trees. Proper trees can
also be stripped of their leaves to form a bare tree:
[ [1 [2 3] [] 4] [5] ] strip == [ [ [] [] ] [] ]The
strip
function commutes with reverse
and
treereverse
:
reverse strip == strip reverse treereverse strip == strip treereverseOnce stripped, there is nothing for
treemap
to do:
[strip] dip treemap == treemap strip == pop strip
A monad M
over a category consists of a functor
from the category to itself, and two natural transformations. The
first transformation joinM
takes as argument an object in
the target of the square of the functor and gives as value an object
in the target of the functor. The second transformation
unitM
takes as argument an object in the category and
gives as value an object in the target of the functor. The two
transformations must satisfy two laws which are expressed in terms of
two variants obtained by applying the functor to the two
transformations:
From the first transformation one can define a variant by applying the functor to it. This variant is again a natural transformation, it takes as argument an object in the target of the cube of the functor and gives as value an object in the target of the square of the functor. The first transformation or its variant may be composed with the first transformation. The two compositions are again natural transformations, they take as argument an object in the cube of the functor and give as value an object in the target of the functor. The first defining law for monads is that these two compositions must be identical.
Similarly, from the second transformation one can define a variant by applying the functor to it. This variant is again a natural transformation, it takes as argument and value objects in the target of the functor. The second transformation or its variant may be composed with the first transformation. The two compositions take as argument an value objects in the target of the functor. The second defining law for monads is that these two compositions must both be equal to the identity function.
The above will now be illustrated with the LIST monad. Its
functor is the LIST
functor. Its first natural
transformation is usually called flatten, which
concatenates a two-level list to produce a single-level list. Its
second natural transformation is the unary unitlist
operation which takes any argument to produce its singleton list.
Here are two examples:
[[1 2 3] [peter paul]] flatten == [1 2 3 peter paul] [[1 2 3] [peter paul]] unitlist == [[[1 2 3] [peter paul]]]The two required variants are obtained by applying the
LIST
functor, as map
.
The variant of the flatten
operator is the polymorphic
operator
[flatten] mapwhich takes a list of (lists of lists) as argument and concatenates the (list of lists) but leaves the outer level list structure intact. This is an example:
[[[1 2] [3]] [[a] [b]]] [flatten] map == [[1 2 3] [a b]]The first monad law can now be written in Joy notation. It says that there are two equivalent ways of flattening a list of lists of lists to produce a list:
[flatten] map flatten == flatten flatten
The variant of unitlist
is the polymorphic operator
[unitlist] mapwhich takes a list of elements and produces the list of their unitlists. An example is
[1 2 [3 4]] [unitlist] map == [[1] [2] [[3 4]]]The second monad law can now be written in Joy as
[unitlist] map flatten == id == unitlist flatten
As natural transformations both flatten
and
unitlist
interact with the LIST
functor
operating (as map
) on arbitrary functions. There are two
further laws that arise. Because these two laws are more general than
the preceding ones, they are also more useful:
A list of lists can be mapped at the second level through an arbitrary
function using the mmap
combinator, producing another
list of lists. That can then be flatten
ed to produce a
single level list. The same original list of list can first be
flatten
ed to produce a single level list which can then
be mapped at the top level using map
. The two results
are the same, and in Joy this is expressed as
mmap flatten == [flatten] dip map
A function may be applied to an argument of any type, and then the
unitlist
can be taken. Alternatively the
unitlist
can be taken first and then the result can be
map
ped through the function. That the results are the
same can be written in Joy as
i unitlist == [unitlist] dip map
{Wadler92} shows that in any monad it is possible to define another
natural transformation, monadic composition which
simultaneously resembles function application and function
composition. For the LIST
monad it takes as one of its
arguments a list and as the other argument a function which yields a
list as value. The result is again a list. In Joy it might be
defined by
bind == map flattenIt satisfies the following laws:
[unitlist] dip bind == i [unitlist] bind == id [K [H] bind] bind == [K] bind [H] bindThe first two laws say that
unitlist
is a left and right
identity for bind
, the third says that bind
is associative. The third law is here expressed with program
variables K
and H
. Alternatively it is
expressed by
[bind] cons concat bind == [bind] dip bindWadler makes extensive use of many
bind
-like functions
for monads other than the LIST
monad.
A very general theory of lists, without the use of category theory, is
given in {Bird86}. A very readable introduction to the
LIST
functor can be found in {Spivey89}. The theory of
lists is generalised by {Malcolm89} to what have been called rose
trees. {Meijer-etal91} give a comprehensive collection of laws of
functional programming using very general functional forms for lists
and other data types. {Bird-deMoor92} use categories, homomorphisms
and algebraic techniques to solve sophisticated optimisation problems
in functional programming. It appears that most, and perhaps even
all, of the contributions in the above papers can be translated into
Joy notation.


Being able to ask a meaningful, specific question is essential to getting a meaningful, specific answer. Everyone on forums (whether you know them personally or not) is strapped for time. People are often skimming and/or scrollling through a page very quickly.
Does your question have a title?
If you hadn't been really reading the post, you definitely skimmed down and saw the bolded text. Your question needs to have a short and specific title that illustrates exactly what you need from an answer.
A bad question:
JavaScript Problm: error trying string reverse
A better question:
How can I reverse the letters of a string in Javascript?
console.log("money".reverse())
/file.js:6
"money".reverse()
^
TypeError: Object money has no method 'reverse'
A couple things to keep in mind as to why this is a better question:


|
Little Heroes
|
Property binding lets you bind two fields or properties so that changing one will update the other. More...
Public Member Functions | |
| void | UpdateTarget () |
| Immediately update the bound data. More... | |
Public Attributes | |
| PropertyReference | source |
| First property reference. More... | |
| PropertyReference | target |
| Second property reference. More... | |
| Direction | direction = Direction.SourceUpdatesTarget |
| Direction of updates. More... | |
| UpdateCondition | update = UpdateCondition.OnUpdate |
| When the property update will occur. More... | |
| bool | editMode = true |
| Whether the values will update while in edit mode. More... | |
Property binding lets you bind two fields or properties so that changing one will update the other.
| void PropertyBinding.UpdateTarget | ( | ) |
Immediately update the bound data.
| Direction PropertyBinding.direction = Direction.SourceUpdatesTarget |
Direction of updates.
| bool PropertyBinding.editMode = true |
Whether the values will update while in edit mode.
| PropertyReference PropertyBinding.source |
First property reference.
| PropertyReference PropertyBinding.target |
Second property reference.
| UpdateCondition PropertyBinding.update = UpdateCondition.OnUpdate |
When the property update will occur.


The judge information to be sent to each player.
See Also: Inherited members from object.
|
|
JudgeToSend
()
|
Initializes a new instance of this class. |
|
|
Initializes a new instance of this class equivalent to the instance of Judge given. |
|
|
ToJudge
()Returns an instance of Judge class equivalent to this. |
Initializes a new instance of this class.Syntax
public JudgeToSend ()Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>
Initializes a new instance of this class equivalent to the instance of Judge given.Syntax
public JudgeToSend (AIWolf.Common.Data.Judge judge)Parameters
- judge
- The instance of Judge given.
Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>
The index number of the agent who judged.Syntax
[System.Runtime.Serialization.DataMember(Name="agent")]
public int Agent { get; set; }Value
The index number of the agent who judged.Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>
The day of this judge.Syntax
[System.Runtime.Serialization.DataMember(Name="day")]
public int Day { get; set; }Value
The day of this judge.Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>
The result of this judge in string.Syntax
[System.Runtime.Serialization.DataMember(Name="result")]
public string Result { get; set; }Value
"HUMAN" or "WEREWOLF".Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>
The index nunmber of the judged agent.Syntax
[System.Runtime.Serialization.DataMember(Name="target")]
public int Target { get; set; }Value
The index number of the judged agent.Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>
Returns an instance of Judge class equivalent to this.Syntax
public AIWolf.Common.Data.Judge ToJudge ()Returns
An instance of Judge equivalent to this.Remarks
Requirements
Namespace: AIWolf.Common.Net
Assembly: AIWolfLibCommon (in AIWolfLibCommon.dll)
Assembly Versions: <IP_ADDRESS>


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