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My Clean Code Experience No. 1 (with before and after code examples)

Public Code Review Robert C. Martin was kind enough to review the code in this post at on his new blog Clean Coder. Be sure to read his review when you finish reading this post. Introduction After expressing an interest in reading Robert C Martin‘s books, one of my Twitter followers was kind enough to give me a copy of Uncle Bob’s book Clean Code as a gift*. This post is about my first refactoring experience after reading it and the code resulting from my first Clean Code refactor. Sample code The code used in this post is based on the data access layer (DAL) used in a side project I’m currently working on. Specifically, my sample project is based on a refactor on the DAL classes for comment data. The CommentData class and surrounding code was simplified for the example, in order to focus on the DAL’s refactoring, rather than the comment functionality. Of course; the comment class could be anything. Download the my clean code refactor sample project (VS2008) Please notice: 1. The database can be generated from the script in the SQL folder 2. This code will probably make the most sense if you step through it 3. This blog post is about 1,700 words, so if you aren’t into reading, you will still get the jist of what I’m saying just from examining the source code. What Clean Code isn’t about Before starting, I want to point out that Clean Code is not about formatting style. While we all have our curly brace positioning preferences, it really is irrelevant. Clean Code strikes at a much deeper level, and although your ‘style’ will be affected tremendously, you won’t find much about formatting style. My original code My original comment DAL class is in the folder called Dirty.Dal, and contains one file called CommentDal.cs containing the CommentDal class. This class is very typical of how I wrote code before reading this book**. The original CommentDal class is 295 lines of code all together and has a handful of well named methods. Now, 295 lines of code is hardly awful, it doesn’t seem very complex relatively speaking, and really, we’ve all seen (and coded) worse. Although the class interface does seem pretty simple, the simplicity of its class diagram hides its code complexity. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25... read more

What’s wrong with the noun/adjective/verb object oriented design strategy

The programming course I took way back in 1993 was basically a 1 year intro to C. And like any good student, as I learned the language, I also started learning about code reuse and experienced a delightful satisfaction every time I realized 2 different functions had similar code which could be moved into a new function. Eventually, I noticed a pattern, in that I would write a bit of functionality until it worked, then I would refactor it into a more elegant solution with as little repeated code as possible. My code evolved quite nicely. Then I learned C++, object oriented programming, and was introduced to the holy grail of object oriented design advice, which went something like this: Take your requirements and circle all the nouns, those are your classes. Then underline all the adjectives, those are your properties. Then highlight all your verbs, those are your methods This Noun / Adjective / Verb design strategy seemed like the most ingenious piece of programming wisdom ever spoken … but it’s led us down a misguided path. It’s the verb that’s misunderstood. The verb should be another class, not a method. It should be a process class. As a programming concept, a process is just as much a ‘thing’ as any real world object. The verb should be a class, which accepts the noun as an input to be processed. But there’s also another problem; Up until this little shortcut was articulated, code was structured based on the implemented code, with similar functionality refactored into its own reusable units, but once noun/adjective/verb idea became widespread, code was suddenly structured according to domain. For example, the domain focus was really evident in the way we structured our ‘is-a’ relationships, with inheritance being based more on the real world domain, than the implementation code. Inheritance should be based on most efficient code reuse, not the domain, because as anybody who has heard the square is not a rectangle* example can attest, sometimes the domain ‘is-a’ relationship just doesn’t work. * With regards to the square is not a rectangle example, please be aware the solution outlined does not resolve the problem, as described in Uncle Bobs comment. The 1996(?) magazine article, The Liskov Substitution Principle is available, which contains the example as originally described. I didn’t post this url, since it’s not focused exclusively on the square / rectangle issue. Copyright © John MacIntyre 2010, All rights... read more

An Abstract Data Model

This is post 3 from a 7 part series entitled Technical Achievements in my Last Project. Overview Normally, when I build a new system, I design the new data model based on the requirements, and build my business objects and data access, based primarily on a that data model*. The remainder of the application is built on the components beneath it, so when you change something at the bottom, like the data model, changes ripple throughout the application. The data model serves as the foundation of my application. Now as far as this project goes, one of the important requirements was to deliver the new system incrementally, while leaving the older system to run in parallel until completely replaced. Parallel Data Models This presented a bit of a dilemma for me since the current database was … well … lacking, and I was planning to refactor it enough to make it a very unstable foundation for the old system. I wanted to refactor it for a number of reasons including; missing primary keys, no foreign keys, no constraints, data fields which were required but not there, data fields which were there but not used, data fields containing 2 or more pieces of information, and tables which should have been multiple tables. Not to mention the desire to achieve a consistent naming convention without the insane column names using characters like ‘/’ and ‘?’ … seriously. However the parallel systems requirement caused a bit of a dilemma. I mean, how do you manage parallel systems, one of which needs a stable foundation, and the other is so temperamental that you don’t want to touch it. My options as I saw them were something like: Scrap the data model refactoring. This really didn’t get much thought. Well it did, but the thought was, is this the best route for the client? And if so, should I offer to help them find my replacement or just leave? I definitely wasn’t up for replacing one unmaintainable piece of junk for another. New data model and re-factor the existing app. The existing application was a total nightmare built in classic Access spaghetti code fashion. Just touching that looked like going down a rabbit hole of certain doom. New application on the old data model and refactor the data model later. This would have caused a real disconnect between the data model and the application. I’m not sure if the data model and application ever... read more

How to enforce a foreign key constraint against multiple tables

I am building a web app with Ben Alabaster, and one of the requirements is for the user to be able to flag items for moderators. So the user can flag entity A, entity B, entity C, etc… So I created a single flag table. Which I then tried to tie it to the entity tables, hoping for something like Where all the foreign key relationships were from [flag].[entity_id] to [EntityX].[id] Then when I wanted the top 10 flags from a particular entity (B in this case), I could run a query like select top 20 e.[name], count(*) "count" from entityB as e    left join flag as f     on f.entity_id = e.id where f.entity_type='B' group by e.[name] order by count(*) desc Unfortunately, if you were to create the above table relationship, and run the following inserts insert into EntityA( id, name) values (1, 'EntityA'); insert into EntityB( id, name) values (2, 'EntityB'); insert into EntityC( id, name) values (3, 'EntityC'); insert into EntityD( id, name) values (4, 'EntityD'); The following statement insert into flag(entity_id, flag_reason) values(5, 'Testing without a valid FK value.'); would fail as expected, as expected, with the following error. “The INSERT statement conflicted with the FOREIGN KEY constraint “FK_flag_EntityA”. The conflict occurred in database “test”, table “dbo.EntityA”, column ‘id’.” But insert into flag(entity_id, flag_reason) values(1, 'Testing the FK to entity A.'); would also fail, which was undesired, with the following error: “The INSERT statement conflicted with the FOREIGN KEY constraint “FK_flag_EntityB”. The conflict occurred in database “test”, table “dbo.EntityB”, column ‘id’.” + So, my options with regards to referential integrity are : Ditch the referential integrity, which I am vehemently opposed to. ++ Create multiple flag tables, each with the exact same schema, but a different Foreign Key relationship, which just seems wrong. Managing referential integrity via triggers. While I’m not a big fan of triggers, the ‘Managing referential integrity via triggers.’ option seems like the only tolerable one. So I added the [entity_type] column to my flag table. Removed the relationships And wrote the following trigger to manage the foreign key relationship. -- ============================================= -- Description: maintain referential integrity on -- a column which is a FK for different tables -- ============================================= CREATE TRIGGER flag_entity_id_fk ON flag AFTER INSERT,UPDATE AS BEGIN declare @entity_type char(1); declare @entity_id int; declare @cnt int;  -- SET NOCOUNT ON added to prevent extra result sets from  -- interfering with SELECT statements.  SET NOCOUNT ON;  -- get info  select @entity_type=entity_type,    @entity_id=entity_id,... read more

How to eliminate analysis paralysis

Over the first decade of my programming career, one trend became very obvious to me. I noticed that I could always increase my efficiency dramatically in the 11th hour before a deadline. It took about a long time to see (a decade), but I finally saw the truth…

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