Review - TFS/VSTS - Great Product, Ideal for Small Development Shops

This is a report a short review I provided for G2 regarding TFS:

What do you like best?

If you use Visual Studio for development, TFS, or its online equivalent VSTS, you can have a fairly seamless end-to-end integration. Out of the box, it provides code management, testing, work hierarchy in agile formats, automated build, and deployment.

What do you dislike?

Branching and merging can be a bit painful, in that it needs to be planned, and is not natively part of the process. Code review also needs to be planned and only recently has it become part of the process.

Recommendations to others considering the product

My only concern regarding TFS and VSTS is that Microsoft itself recommends using Git.

What business problems are you solving with the product? What benefits have you realized?

In my current role, I've joined a shop that has application development as secondary to their role of desktop OS and app deployment/maintenance, so their code management practices are minimal.…

Complexity: A Guided Tour

Complexity: A Guided Tour by Melanie Mitchell
My rating: 4 of 5 stars

I enjoy reading in systems and complexity, and this was a nice addition to my shelf, with a slightly different take than other books. I found a few areas in the first half a bit tedious, overly long, repetitive, and not illuminating, but generally, it's a great overview of seminal work and very thought-provoking. The first half overlaps but nicely differs from other books I've read, covering things like chaos and information processing, and the latter half of the book I found more engaging, focused on models, computation, network science, and scaling. As mentioned, although I found the first half a bit of a slog at times, the second half was very engaging.

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Do Algorithms Make You a Better Developer?

Responding to a question on HashNode, Developers who practise algorithms are better at software development than people who just do development. Is it true?, I wrote the following:
My feeling is that algorithms help make one a better programmer, but that is likely true of many coding concepts. I did not have algorithms as an undergraduate, so my knowledge is acquired through reading and practice, but after reading and applying Algorithm's in a Nutshell, I felt the quality of my work improved. That said, my development work increased more after understanding Design Patterns, or after consuming books on database design.  Since many types of knowledge improve developing and architecting abilities, one has to consider how it helps and to what degree. Algorithms are coding-in-the-small, often narrowly focused solutions, but which can have a great impact at scale. For many applications, a focus on algorithms would be overkill as data sets and requirements do not require it. In this con…

Hash-based Search

An example of a hash-based search, although using dictionaries.  The code is designed to manage lists of Person objects, with unique Id's as the key value, with a rudimentary hash function to assign to various lists.

Salient Characteristic(s)
Useful for managing large unsorted listsDivides the items into smaller hash-based buckets (divide and conquer)Generally excellent performanceSensitive to the choice of hash function and data structures chosenNote
The Id key is not rigorous enough to guarantee uniqueness, and a better key might need to be selected, e.g., SSN, to prevent the same person being entered twice.Code

using System;
using System.Collections.Generic;

namespace Algorithms
    //Example object to add and find in Hash Search example
    public class Person
        private int _Id;
        public int Id 
            get { return _Id; }
            set { _Id = value; } 

        private string _LastName;
        public string LastName 
            get { retu…

Binary Search

This is the basic divide-and-conquer algorithm, requiring a sorted array. This repeatedly halves the remaining positions to search, until the value is found, or it determines that the value cannot be found. As mentioned, it requires a presorted array, or if unsorted, requires it is sorted. The benefits accrue in instances where the array is sorted once, but searched many times.

On a hypothetical array of 100 items, a linear search has an average performances of O(n/2), or a search of half the positions, 50, to find the item. By comparison, the average performance of Binary Search is O(log n), which for 100 items translates into 4.6, a radically reduced number of iterations, but with greater requirements for logic and memory.

Done in both C#, as an iterative while loop, and F#, as a recursion.

using System; namespace Algorithms { class BinarySearch { public BinarySearch() { } public int Search(int num, int[] arrayToSearch) { …

Linear Search

Because Linear Search is so simple, I thought of doing something a bit different, so this post includes code in F# as well as C#.


//linear search, but with error handling for 'value not found'
let LinearSearch num arr = 
        arr |> List.findIndex (fun x -> x = num)
        | :? System.Collections.Generic.KeyNotFoundException -> -1

//create array to use
let baseList = [3; 1; 7; 2; 9; 4; 1; 12; 25; 10; 11; 19; 22]

//two examples, one that works, and one that returns an error of -1
let resultFound = LinearSearch 12 baseList
let resultMissing = LinearSearch 23 baseList



using System;

namespace Algorithms
    class LinearSearch
        public LinearSearch()

        public int Search(int num, int[] arrayToSearch)
            //creates array
            //int[] arrayToSort = { 11, 7, 22, 2, 33, 3, 17, 44, 4, 55, 5, 66, 6, 1, 77 };

            int posFound = -1;
            for(int pos = 0; pos<arrayToSearch.Length; pos++)

Bucket Sort

The following uses the divide-and-conquer method of resolution, by dividing the problem into smaller arrays, sorting each smaller array, then reinserting the subarrays back into the original array.  This is not a pure solution, in that it uses the .NET List, rather than a linked list struct.

using System;
using System.Collections;
using System.Collections.Generic;

namespace Algorithms
    class BucketSort
        public int[] Sort()
            //creates arbitrary array
            int[] arrayToSort = { 11, 7, 22, 2, 33, 3, 17, 44, 4, 55, 5, 66, 6, 1, 77 };
            //create bucket using hash, x/10
            List<int>[] bucketList = CreateHashedArray(arrayToSort, 10);
            //sort the bucket list back into the original array
            ReorderList(bucketList, arrayToSort);
            return arrayToSort;

        private int hashFunction(int num, int buckets)
            return num / buckets;

        private List<int>[] CreateHashedA…