2019 APL Problem Solving Competition: Phase I Problems Sample Solutions

The following are my attempts at the Phase I problems of the 2019 APL Problem Solving Competition. There are not necessarily “right answers” as personal style and taste come into play. More explanation of the code is provided here than common practice. All solutions pass all the tests specified in the official problem description.

1. Chunky Monkey

Write a function that, given a scalar or vector as the right argument and a positive (>0) integer chunk size n as the left argument, breaks the array’s items up into chunks of size n. If the number of elements in the array is not evenly divisible by n, then the last chunk will have fewer than n elements.

💡Hint: The partitioned enclose function could be helpful for this problem.


Basically, the problem is to construct an appropriate boolean left argument to. For this the reshape function ⍺⍴⍵ is apt, which repeats the items of up to length .

   9 ⍴ 1 0 0                     (9 ⍴ 1 0 0) ⊂ 'ABCDEFGHI'
1 0 0 1 0 0 1 0 0             ┌───┬───┬───┐

   11 ⍴ 1 0 0                    (11 ⍴ 1 0 0) ⊂ 'ABCDEFGHIJK'
1 0 0 1 0 0 1 0 0 1 0         ┌───┬───┬───┬──┐

2. Making the Grade

Score Range Letter Grade
0-64 F
65-69 D
70-79 C
80-89 B
90-100 A

Write a function that, given an array of integer test scores in the inclusive range 0–100, returns an identically-shaped array of the corresponding letter grades according to the table to the left.

💡Hint: You may want to investigate the interval index function.

   f2← {'FDCBA'[0 65 70 80 90⍸⍵]}

For example:

   range← 0 65 70 80 90
   score← 0 65 89 64 75 100

   range ⍸ score                      range ⍸ 2 3⍴score
1 2 4 1 3 5                        1 2 4
                                   1 3 5
   'FDCBA'[1 2 4 1 3 5]               'FDCBA'[2 3⍴1 2 4 1 3 5]
FDBFCA                             FDB
    f2 score                          f2 2 3⍴score
FDBFCA                             FDB

The examples on the right illustrate that the functionsand [] extend consistently to array arguments.

In APL, functions take array arguments, and so too indexing takes array arguments, including the indices (the “subscripts”). This property is integral to the template

   Y indexing (X index ⍵)


X   domain for looking things up
Y range where you want to end up; “aliases” corresponding to X
index a function to do the looking up, such asor
indexing   a function to do indexing into X , such as [] or or (dyadic)

3. Grade Distribution

Given a non-empty character vector of single-letter grades, produce a 3-column, 5-row, alphabetically-sorted matrix of each grade, the number of occurrences of that grade, and the percentage (rounded to 1 decimal position) of the total number of occurrences of that grade. The table should have a row for each grade even if there are no occurrences of a grade. Note: due to rounding the last column might not total 100%.

💡Hint: The key operator could be useful for this problem.


The result of f⌸ is ordered by the unique major cells in the keys. If a particular order is required, or if a particular set of keys is required (even when some keys don’t occur in the argument), the computation can be effected by prefacing keys to the argument (here ,⍨a←'ABCDF') and then applying an inverse function (here ¯1+) to the result of .

For the key operator, in particular cases, for example the letter distribution in a corpus of English text, the universe of letters and their ordering are known (A-Z); in principle, it is not possible to “know” the complete universe of keys, or their ordering.

The function f3x illustrates the complications. f3 is the same as above; extra spaces are inserted into both functions to facilitate comparison.

   f3 ← {a,   k,1⍕⍪100×k÷+⌿k←¯1+{≢⍵}⌸⍵⍪⍨a←'ABCDF'}
   f3x← {(∪⍵),k,1⍕⍪100×k÷+⌿k←   {≢⍵}⌸⍵           }

   ⊢ g1← 9 3 8 4 7/'DABFC'

   f3x g1                            f3 g1
D 9  29.0                         A 3   9.7
A 3   9.7                         B 8  25.8
B 8  25.8                         C 7  22.6
F 4  12.9                         D 9  29.0
C 7  22.6                         F 4  12.9
   ⊢ g2← ('F'≠grade)⌿grade

   f3x g2                            f3 g2
D 9  33.3                         A 3  11.1
A 3  11.1                         B 8  29.6
B 8  29.6                         C 7  25.9
C 7  25.9                         D 9  33.3
                                  F 0   0.0

4. Knight Moves

│1 1│1 2│1 3│1 4│1 5│1 6│1 7│1 8│
│2 1│2 2│2 3│2 4│2 5│2 6│2 7│2 8│
│3 1│3 2│3 3│3 4│3 5│3 6│3 7│3 8│
│4 1│4 2│4 3│4 4│4 5│4 6│4 7│4 8│
│5 1│5 2│5 3│5 4│5 5│5 6│5 7│5 8│
│6 1│6 2│6 3│6 4│6 5│6 6│6 7│6 8│
│7 1│7 2│7 3│7 4│7 5│7 6│7 7│7 8│
│8 1│8 2│8 3│8 4│8 5│8 6│8 7│8 8│
  Consider a chess board as an 8×8 matrix with square (1 1) in the upper left corner and square (8 8) in the lower right corner. For those not familiar with the game a chess, the knight, generally depicted as a horse (♞), can move 2 spaces right or left and then 1 space up or down, or 2 spaces up or down and then 1 space right or left. For example, this means that a knight on the square (5 4) can move to any of the underscored squares.

Given a 2-element vector representing the current square for a knight, return a vector of 2-element vectors representing (in any order) all the squares that the knight can move to.

💡Hint: The outer product operator ∘. could be useful for generating the coordinates.

   f4← {↓(∧/q∊⍳8)⌿q←⍵+⍤1⊢(3=+/|t)⌿t←↑,∘.,⍨¯2 ¯1 1 2}

f4 derives as follows: First, generate all 16 combinations t of moves involving 1 and 2 steps, left and right and up and down, then select move combinations which total exactly 3 squares regardless of direction.

   (3=+/|t)⌿t←↑,∘.,⍨¯2 ¯1 1 2
¯2 ¯1
¯2  1
¯1 ¯2
¯1  2
 1 ¯2
 1  2
 2 ¯1
 2  1

The resultant 8-row matrix (call this mv) is added to, the coordinates of the current square, and then pruned to discard squares which fall outside of the chess board. The following examples illustrate the computation for ⍵≡5 4 and ⍵≡1 2 :

   mv←(3=+/|t)⌿t←↑,∘.,⍨¯2 ¯1 1 2

   ⊢ q←5 4+⍤1⊢mv                             ⊢ q←1 2+⍤1⊢mv
3 3                                       ¯1 1
3 5                                       ¯1 3
4 2                                        0 0
4 6                                        0 4
6 2                                        2 0
6 6                                        2 4
7 3                                        3 1
7 5                                        3 3

   ↓(∧/q∊⍳8)⌿q                               ↓(∧/q∊⍳8)⌿q
┌───┬───┬───┬───┬───┬───┬───┬───┐         ┌───┬───┬───┐
│3 3│3 5│4 2│4 6│6 2│6 6│7 3│7 5│         │2 4│3 1│3 3│
└───┴───┴───┴───┴───┴───┴───┴───┘         └───┴───┴───┘

An alterative solution is to precomputing an 8×8 table of the possible knight moves for each chess square, and then picking from the table:

   f4i← (f4¨ ⍳8 8) ⊃⍨ ⊂

The table look-up version would be more efficient in situations (such as in the Knight’s Tour puzzle) where the knight moves are computed repeatedly.

5. Doubling Up

Given a word or a list of words, return a Boolean vector where 1 indicates a word with one or more consecutive duplicated, case-sensitive, letters. Each word will have at least one letter and will consist entirely of either uppercase (A-Z) or lowercase (a-z) letters. Words consisting of a single letter can be scalars.

💡Hint: The nest functioncould be useful.

   f5← (∨⌿2=⌿' ',⊢)¨∘⊆

A solution obtains by solving it for one word and then applying it to each word via the each operator. Since a single word argument can be a string of letters, and we don’t want to apply the single word solution to each letter, that argument must first be converted in an enclosed word with nest. Thus the overall solution is of the form f¨∘⊆.

For a single word, what is required is to detect consecutive duplicate letters, whence the operator 2=⌿⍵ is apt.

   2 =⌿ 'bookkeeper'                  2 =⌿ 'radar'
0 1 0 1 0 1 0 0 0                  0 0 0 0

   ∨⌿ 2 =⌿ 'bookkeeper'               ∨⌿ 2 =⌿ 'radar'
1                                  0

As usual, the link function {⍺⍵} can be used as a generic dyadic operand function to gain additional insight into the workings of an operator:

   2 {⍺⍵}⌿ 'bookkeeper'               2 {⍺⍵}⌿ 'radar'
┌──┬──┬──┬──┬──┬──┬──┬──┬──┐       ┌──┬──┬──┬──┐
│bo│oo│ok│kk│ke│ee│ep│pe│er│       │ra│ad│da│ar│
└──┴──┴──┴──┴──┴──┴──┴──┴──┘       └──┴──┴──┴──┘

2 f⌿⍵ signals error on single-item arguments; moreover, it is problematic to compare a single letter against itself. Both problems are finessed by first prefacing the argument with a space ' '.

In f5, the train (∨⌿2=⌿' ',⊢) can also be written as the equivalent dfn {∨⌿2=⌿' ',⍵} as a matter of personal style. The display of a train does provide more information about how it is structured than the display of a dfn.

   (∨⌿2=⌿' ',⊢)                       {∨/2=⌿' ',⍵}
┌─────┬─────────────────┐          {∨⌿2=⌿' ',⍵}
│└─┴─┘││ ││=│⌿│││ │,│⊢│││
│     ││ │└─┴─┘│└─┴─┴─┘││
│     │└─┴─────┴───────┘│

6. Telephone Names

│    │ABC│DEF │
│ 1  │ 2 │ 3  │
│ 4  │ 5 │ 6  │
│ 7  │ 8 │ 9  │
│    │   │    │
│ *  │ 0 │ #  │
  Some telephone keypads have letters of the alphabet embossed on their keytops. Some people like to remember phone numbers by converting them to an alphanumeric form using one of the letters on the corresponding key. For example, in the keypad shown, 'ALSMITH' would correspond to the number 257-6484 and '1DYALOGBEST' would correspond to 1-392-564-2378. Write an APL function that takes a character vector right argument that consists of digits and uppercase letters and returns an integer vector of the corresponding digits on the keypad.

💡Hint: Your solution might make use of the membership function .

   f6← {(⍵⍸⍨⎕d,'ADGJMPTW')-9*⍵∊⎕a}

Letters and digits alike are mapped to integer indices using the interval index function, which neatly handles the irregularly-sized intervals (see problem 2 above). The indices are then decremented by 9 for letters and by 1 for digits.

The expression 9*⍵∊⎕a illustrates a common technique in APL used to implement array logic, effecting control flow without using control structures or explicit branching. In the following, c and d are scalars (usually numbers) and is a boolean array.

c*⍵ c whereis 1 and 1 whereis 0.
c×⍵ c whereis 1 and 0 whereis 0.
c+⍵×d-c   c whereis 0 and d whereis 1.
(c,d)[1+⍵]   Same as c+⍵×d-c, but c and d can be any scalars. The 1+ is omitted if the index origin ⎕io is 0.

7. In the Center of It All

Given a right argument of a list of words (or possibly a single word) and a left argument of a width, return a character matrix that has width columns and one row per word, with each word is centered within the row. If width is smaller than the length of a word, truncate the word from the right. If there are an odd number of spaces to center within, leave the extra space on the right.

💡Hint: The mixand rotatefunctions will probably be useful here.

   f7← {(⌈¯0.5×0⌈⍺-≢¨⍵)⌽↑⍺↑¨⍵}∘⊆

As in problem 5, a prefatory application of nestconverts an argument of a single word into a more manageable standard of a list of words. Subsequently, the right argument is turned into a matrix, each row padded with spaces on the right (or truncated). Each row is then rotated so that the non-blank characters are centered. The finicky detail of an odd number of spaces is resolved by usingorin the calculation of the amounts of rotation.

8. Going the Distance

Given a vector of (X Y) points, or a single X Y point, determine the total distance covered when travelling in a straight line from the first point to the next one, and so on until the last point, then returning directly back to the start. For example, given the points

   (A B C)← (¯1.5 ¯1.5) (1.5 2.5) (1.5 ¯1.5)

the distance A to B is 5, B to C is 4 and C back to A is 3, for a total of 12.

💡Hint: The rotateand power * functions might be useful.

   f8← {+⌿ 2 {0.5*⍨+.×⍨⍺-⍵}⌿ ⍵⍪1↑⍵}

The result obtains by applying the distance function d←{0.5*⍨+.×⍨⍺-⍵} between pairs of points, taking care to return to the start.

As in problem 5, the expression 2 f⌿⍵ is just the ticket for working with consecutive items in the argument and, again, using the link function {⍺⍵} elucidates the workings of an operator:

   (A B C)← (¯1.5 ¯1.5) (1.5 2.5) (1.5 ¯1.5)

   2 {⍺⍵}⌿ A B C A
││¯1.5 ¯1.5│1.5 2.5│││1.5 2.5│1.5 ¯1.5│││1.5 ¯1.5│¯1.5 ¯1.5││
   2 d⌿ A B C A
5 4 3

   A d B              B d C              C d A
5                  4                   3

   f8 A B C

9. Area Code à la Gauss

Gauss’s area formula, also known as the shoelace formula, is an algorithm to calculate the area of a simple polygon (a polygon that does not intersect itself). It’s called the shoelace formula because of a common method using matrices to evaluate it. For example, the area of the triangle described by the vertices (2 4) (3 ¯8) (1 2) can be calculated by “walking around” the perimeter back to the first vertex, then drawing diagonals between the columns. The pattern created by the intersecting diagonals resembles shoelaces, hence the name “shoelace formula”.

💡Hint: You may want to investigate the rotate firstfunction.

First place the vertices in order above each other:
2 4
3 ¯8
1 2
2 4
Sum the products of the numbers connected by the diagonal lines going down and to the right:

2 4
3 ¯8
1 2
2 4
Next sum the products of the numbers connected by the diagonal lines going down and to the left:

2 4
3 ¯8
1 2
2 4

Finally, halve the absolute value of the difference between the two sums:

      0.5 × | ¯6 - 8
2 4
3 ¯8
1 2
2 4

Given a vector of (X Y) points, or a single X Y point, return a number indicating the area circumscribed by the points.

   f9← {0.5×|(+/×/¯1↓0 1⊖t)-+/×/1↓0 ¯1⊖t←↑(⊢,1∘↑)⊆⍵}

There is an alternative solution using the determinant function and the stencil operator  :

   )copy dfns det    ⍝ or  det← (-/)∘(×/)∘(0 1∘⊖)
   x← (2 4) (3 ¯8) (1 2)

   {det ⍵}⌺2 ↑x⍪1↑x
¯28 14 0

   2 ÷⍨| +/ {det ⍵}⌺2 ↑x⍪1↑x
   f9 x

Putting it together:

   f9a← {2÷⍨|+/ {det ⍵}⌺2 ↑⍵⍪1↑⍵}
   f9b← {2÷⍨ +/ {det ⍵}⌺2 ↑⍵⍪1↑⍵}

   f9a x
   f9b x
   f9b ⊖t

f9a computes the absolute area as specified by the problem. f9b computes the signed area by omitting the absolute value function | . Commonly, the signed area is positive if the vertices are ordered counterclockwise and is negative otherwise. See the Wikipedia article on polygons for more details.

Similar to 2 f⌿⍵ (problem 5), the workings of stencil can be elucidated by using {⊂⍵} as a generic monadic operand function:

   {⊂⍵}⌺2 ↑x⍪1↑x
│2  4│3 ¯8│1 2│
│3 ¯8│1  2│2 4│
   {det ⍵}⌺2 ↑x⍪1↑x
¯28 14 0

   det ↑ (2 4) (3 ¯8)       det ↑ (3 ¯8) (1 2)       det ↑ (1 2) (2 4)
¯28                      14                        0

10. Odds & Evens

Given a vector of words, separate the words into two vectors—one containing all the words that have an odd number of letters and the other containing all the words that have an even number of letters.

💡Hint: You may want to look into the dyadic form of the key operator.

   f10← 1 ↓¨ (1 0,2|≢¨) {⊂⍵}⌸ 1 0∘,

The solution is required to have exactly two items, words of odd lengths and words of even lengths. This required form is ensured by prefacing the left and right argument to key by 1 0, then dropping the first item from each of the resultant two parts. (See also problem 3 above.)

Editor’s Addendum: Phase II Questions

You can watch the 2019 Grand Prize Winner Jamin Wu’s Dyalog ’19 acceptance presentation and explanation of how he approached the phase II questions on Dyalog.tv.

Dyalog ’19 Videos: Week 10

The release of the final set of videos from the Dyalog ’19 user meeting in Elsinore slipped into 2020, thus providing me with a perfect opportunity to wish you all a Happy New Year from all of us at Dyalog! We are wrapping up with recordings from the Prize Ceremony for the 11th annual Problem Solving Competition and the the Young APLers’ Panel.

The young APLer’s panel. From left: Stephen Taylor, Alve Björk, Yuliia Serhiienko, James Heslip and Josh David

I can’t think of a better way to kick off the new year than watching newcomers to APL talk about how they got started! With Stephen Taylor as host, our panellists Alve Björk (Uppsala University, Sweden), James Heslip (Optima Systems Ltd, UK), Josh David (Dyalog Ltd, USA) and Yuliia Serhiienko (SimCorp, Ukraine) discuss how they first encountered APL, their perception/experience of the language and what they would like to see APL vendors and the APL community working on in the future.

Every year, the annual APL Problem Solving Competition entices students to learn APL and try to win significant cash prizes and a trip to the Dyalog user meeting. This year, Dyalog brought the entire contest “in house” rather than using an external company to host it. We developed our own interactive contest site, which allowed contestants to get immediate feedback on potential solutions to Phase 1 problems. In addition to making it more fun – and a lot easier – to submit solutions, the new site saved Dyalog a lot of time by pre-verifying Phase 1 solutions. As Brian Becker explains in his talk leading up to the prize ceremony, the project gave us an opportunity to test a lot of our own components by building a fully operational application entirely in Dyalog APL. Gitte Christensen, CEO of Dyalog Ltd, awards the prize for the best professional entrant to Torsten Grust and the grand prize to Jamin Wu.

Grand Prize winner Jamin Wu

I never cease to be amazed by the quality of presentations by winners of the contest. The youngsters of today seem able to learn to write APL code that many professionals would be proud to have written, in a few weeks – sometimes only days.

Jamin Wu is a medical student at Monash University in Australia, but also a keen programmer. His presentation on how he won the 11th annual APL Problem Solving Competition was one of the clearest and most impressive acceptance speeches by a winner of the competition that I have had the privilege to attend. In a very short amount of time, Jamin has been able to get an astonishing grip on the benefits of APL, and write some of the most elegant APL code I have ever seen. We’re sad that he won’t be joining the community as a full-time APL programmer any time soon; the good news is that the medical community in Australia will soon have a very competent young doctor, able to use computers very effectively to assist him in research and analysis of data!

Summary of this week’s videos:


That is (almost) the end of the Dyalog ’19 videos; at Tomas Gustafsson’s request, we are holding back the release of his exciting yarn about how APL was used to locate the wreck of the M/S Irma until the upcoming documentary has been aired on Finnish TV.

It is already time to think about Dyalog ’20, which will be held in Olhão, Portugal, from 11th-15th October. Follow us on social media (Facebook, Twitter, LinkedIn) to be kept informed about this and all things related to Dyalog!

Dyalog ’19 Videos: Week 9

Richard Smith asks and answers: Is it Christmas Yet?

Richard Smith asks and answers: Is it Christmas Yet?

Depending on which day you decide to watch this recording, you may get a different answer from the one that Richard did as he answered his own question (“Is It Christmas Yet?”) in the first minute of his presentation. Of course, the true purpose of the talk was to show off a potential new system function for converting between a variety of time encodings. Not just the obvious ones like the 7-element ⎕TS format timestamp and the Dyalog Date Number, which is the number of days since the 31st of December 1899, but also a variety of Julian Dates, ⎕FRDCI style timestamps, UNIX time, Excel datetimes, Stata, R and SPSS dates and more – a total of more than 20 different time formats. Richard also shows how version 18.0 will allow you to determine the time in different time zones, and ends with formatting the current time in Helsinki – in Welsh.


Roberto and students from Liceo Scientifico GB Grassi Saronno

Roberto and students from Liceo Scientifico GB Grassi Saronno

Inspired by Tetsuya Miyamoto, the inventor of the KenKen and other puzzles, Roberto Minervini avoids lecturing and prefers to present students with puzzles that they will be motivated to solve, learning new skills including mathematics and APL in the process. Pietro, Gabriele, Alessandro had their first exposure to APL in Roberto’s class at the at the Liceo Scientifico GB Grassi Saronno near Milan in Italy. Together with Roberto, they have created “MathMaze”, a platform for hosting real-time puzzle tournaments.

In this talk, they explain the unique scoring algorithm and the difficulty of creating puzzles that don’t make it clear whether you should solve them by thinking about them, by making drawings, or using the computer. A really good puzzle will requires a combination of techniques. As Alessandro explains, APL makes me think about the real mathematics behind a puzzle before I start writing the code.

Summary of this week’s videos:

(Video releases will resume in January 2020)

Dyalog ’19 Videos: Week 8

When Aaron Hsu was at Dyalog ’19 in Elsinore, he was preparing the defence of his PhD Thesis on A Data Parallel Compiler Hosted on the GPU. In his talk “Lessons for the Masses from the Trenches of Co-dfns” he looks back on some of the key lessons learned while working on the PhD and the Co-dfns compiler.

Aaron Hsu presents some of his insights from his work on the Co-dfns project

Aaron Hsu presents some of his insights from his work on the Co-dfns project

As usual, Aaron delivered a talk designed to make every one of us question the fundamental assumptions that we make about programming. Selected sound bites include:

Pointers are the refined sugar of programming.
Beauty and truth are intimately connected.
Value the human, command the machine!


Uncle Andy's back with another fireside chat

Uncle Andy’s back with another fireside chat

To bring you back down to earth, (Uncle) Andy Shiers’ fifth Fireside Talk is about little things that Andy thinks are important to anyone managing or using a Dyalog APL installation that he suspects you have forgotten about, or may have missed when reading the documentation. Some of them are things that he overheard developers talking about and suspects are not documented at all! Most of them are things that he needed himself, or used to handle a support call. Serial numbers play an important role this year; the changes we have made so that we can support the use of unregistered versions of APL for testing and demonstration purposes make it important to understand the impact of serial numbers and how to manage them.

Join us again in week 9 to hear Richard Smith explain how to compute whether it will soon be Christmas and Roberto Minervini (and students) tell us about the Art of Teaching without Teaching.

Summary of this week’s videos:

Dyalog ’19 Videos: Week 7

Week 7 features talks by two recent additions to the Dyalog team. Richard Park joined Dyalog a year ago, and his primary focus is the production of new teaching materials. Nathan Rogers is the newest member of our US consulting team and is based in Denver, Colorado.

Jupyter notebooks have recently become a very popular mechanism for publishing scientific and technical content. In addition to nicely formatted text and graphics, notebooks can contain executable expressions in a growing collection of programming languages – including Dyalog APL. In his talk at Dyalog ’19, Richard shows that it has become really easy to get started with notebooks containing executable APL code. Thanks to recent work that he has done, you can even get started without installing anything on your own machine!

Richard Park shows a new way to access Jupyter documents

Richard Park shows a new way to access Jupyter documents

Nathan Rogers presents APL2XL from the other side of the ocean

Nathan Rogers presents APL2XL from the other side of the ocean

Excel workbooks are nothing new; the first version of Microsoft Excel appeared in 1987, only 4 years after the release of Dyalog version 1.0. For decades, users have used OLE Automation to interact with Excel and create workbooks. However, this is not a suitable technology for use on servers (even Windows-based servers). Nathan could not attend Dyalog ’19 in person due to a theatre production in Denver where he was a member of a team dancing tango, so he had to present his APL2XL project via a remote connection. The goal of this open source project is to create Excel workbooks (.xlsx files) under Windows, Linux and macOS, without any external requirements other than Microsoft .NET compression libraries.

Summary of this week’s videos:

Dyalog ’19 Videos: Week 6

Claus Madsen of FinE Analytics

Scrinium is a portfolio management system that can handle a comprehensive range of financial assets, collect them into “portfolios”, and compute returns (SR, ANN, TWR), risk (Std, VaR, Duration, Convexit, Delta, Gamma, Sharpe) and relative risk (Alpha, Beta, Jensens Alpha, Tracking Error). It deals with benchmarks, and so on and so forth. However, Claus Madsen’s presentation at Dyalog ’19 doesn’t delve deeply into financial maths. Instead, his talk is mostly about the architecture of Scrinium. To allow himself to focus on all of the above-mentioned computations, Claus has organised all of his computations into classes, which he exposes as Microsoft.NET assemblies. This allows him to leave the production of user interfaces and other wrapping to “IT people”.

The other two presentations featured this week are about the statistical package TamStat. TamStat has a new graphical user interface based on the HTMLRenderer, which means that the interface is identical under Microsoft Windows, macOS and Linux.

Richard Park talks TamStat

Richard Park talks TamStat

Stephen Mansour was unable to attend the Dyalog user meeting this year as he was busy teaching statistics using TamStat at Scranton University in Pennsylvania, US. In two talks at Dyalog ’19, Richard Park and Michael Baas provide two different perspectives on the new TamStat UI. First, Richard talks about the fundamental design of the underlying statistical language and how the UI guides inexperienced users and helps construct executable TamStat statements. Michael follows up with a talk on the implementation of the “Wizards” and other features of the new UI that he has worked on during 2019 in collaboration with Dr. Mansour.

Summary of this week’s videos: