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Episode 211: Continuous Delivery on Windows with Rachel Laycock and Max Lincoln

Johannes talks with Rachel Laycock and Max Lincoln from ThoughtWorks about continuous delivery on Windows. The outline includes: introduction to continuous delivery; continuous integration; DevOps and ChatOps; decisions to be taken when implementing continuous delivery on windows; build tools on windows; packaging and deploy on windows; infrastructure automation and infrastructure as code with chef, puppet […]
Categories: Programming

Just Enough

Software Requirements Blog - Seilevel.com - Tue, 09/30/2014 - 17:00
One concept you’ll hear tossed about in an Agile discussion is that of “just enough.” You want just enough documentation, just enough development and testing, just enough time for meetings, just enough grooming, and so on. The idea is that doing more than is needed means you have throwaway work when you need to make […]
Categories: Requirements

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Categories: Architecture

What Can Lean Learn From Systems Engineering?

Herding Cats - Glen Alleman - Tue, 09/30/2014 - 16:33

The Lean Aerospace Initiative and the Lean Aerospace Initiative Consortium define processes applicable in many domains for applying lean. At first glance there is no natural connection between Lean and System Engineering. The ideas below are from a paper Igave at a Lean conference.

Key Takeaways

  • Lean and Systems engineering are cousins.
  • All but trivial projects are systems and many are systems of systems. Thinking like a systems engineer is the basis of implementing Lean processes. Thinking in the absence of systems, does little to add sustaining value to any process improvement.
  • Product development is a value stream process, but how the components interact at the technical, business, financial, and operational levels is a systems engineering process. Lean itself does not possess the vocabulary to speak to these systems complexity issues [1]

Core Concepts of Systems Engineering

  1. Capture and understand the requirements in terms of Capabilities assessed through Measures of Effectiveness (MOE) and Measures of Performance (MOP).
  2. Ensure requirements are consistent with what is predicted to be possible in a solution in these MOEs and MOPs.
  3. Treat goals as desired characteristics for what may not be possible.
  4. Define the MOE, MOP, goals, and solutions for the whole lifecycle of the project in units meaningful to the buyer.
  5. Maintain the distinction between the statement of the problem and the description of the solution.
  6. Baseline each statement of the problem and the statement of the solution.
  7. Identify descriptions of alternative solutions.
  8. Develop descriptions of the solution.
  9. Except for simple problems, develop a logical  solution description.
  10. Be prepared to iterate in design to drive up effectiveness.
  11. Base the solution of the evaluation of its effectiveness, in units of measure meaningful to the buyer.
  12. Independently verify all work products.
  13. Validate all work products from the perspective of the stakeholders.
  14. Some management is needed to plan and implement effective and efficient transformation of requirements and goals into a description of the solution.

Typical System Engineering Activities

  1. Technical management
  2. System design
  3. Product realization
  4. Technical analysis and evaluation
  5. Product control
  6. Process control
  7. Post implementation support

Steps to Lean Thinking [2]

  1. Specify value
  2. Identify value stream
  3. Make value flow continuously
  4. Let customers pull value
  5. Pursue perfection

Differences and Similarities between Lean and Systems Engineering

  1. Both emerged from practice. Only later were the principles and theories codified.
  2. Both have focused on different phases of the product lifecycle. SE is generally on product development. SE is more focused on planning. Lean generally on product production. While Lean is more focused on empirical action.
  3. Unlike Lean, SE has less focus on quality, except for Integrated Product and Product Development (IPPD).

Despite these differences and similarities both Lean and Systems Engineering are focused on the same objectives – delivering products or lifecycle value to the stakeholders.

It is the lifecycle value that drives both paradigms and must drive any other process paradigm associated with Lean and Systems Engineering. Paradigm like software development, the management of any form of a project and the very notion of agile. A critical understanding often missed is that Lifecycle Value includes the cost of delivering that value.

Value can't be determined in the absence of knowing the cost. ROI and Microeconomics of decision making require both variables to be used to make decisions.

What do we mean by lifecycle?

Generally lifecycle is a combination of product performance, quality, cost and fulfillment of the buyers needed capabilities.[3]

Lean and Systems Engineering share this common goal. The more complex the system, the more contribution there from Lean and SE.

Putting Lean and Systems Engineering Together on Real Projects

First some success factors on complex projects [4]

  1. Dedicated and stable interdisciplinary teams
  2. Use of prototypes and models to generate tradeoffs
  3. Prioritizing product features
  4. Engagement with senior management and customers at every point in the project
  5. Some form of high performing front end decision process that reduces instability of key inputs and improve the flow of work throughout the product lifecycle.

This last success factor is core to any complex environment, no matter what the process is called. In the absence of stability of requirements and funding, improvements to the flow of work is constrained.

The notion of adapting to changing requirements is not the same as having the requirements – and the associated funding – be unstable.

Mapping of the Value Stream to the work process requires some level of stability. It is the search for this stability where Systems Engineering – as a paradigm – adds measureable value to any Lean initiative.

The standardization and commonality of processes across complex systems is the basis for this value. [5]

Conclusions

  1. Lean and SE are two side of the same coin regarding the objective of creating value for the stakeholder
  2. Lean and SE complement each other during different phases of the project – ideation, product trades for SE and production waste removal for Lean anchor both ends of the spectrum of improvement opportunities.
  3. Value stream thinking makes visible the paths to be taken in transitioning to a Lean paradigm while maintaining the principles of systems engineering. [6]
  4. The result is the combination of Speed and Robustness – systems are easily adaptable to change while maintaining fewer surprises, using leading indicators to make decisions and decreasing sensitivity to production and use variables.

[1] “The Lean Enterprise – A Management Philosophy at Lockheed Martin,” Joyce and Schechter, Defense Acquisition Review Journal, 2004.

[2] Lean Thinking, Womack and Jones, Simon and Schuster, 1996

[3] Lean Enterprise Value: Insights from MIT’s Lean Aerospace Initiative, Murman, et al, Palgrave 2002.

[4] “Lean Systems Engineering: Research Initiatives in Support of a New Paradigm,” Rebentisch, Rhodes, and Murman, Conference on Systems Engineering, April 2004.

[5] LM21 Best Practices, Jack Hugus, National Security Studies, Louis A. Bantle Symposium, Syracuse University Maxwell School, October 1999

[6] “Enterprise Transition to Lean Roadmap,” MIT Lean Aerospace Initiative, 2004 Plenary Conference.

 

Related articles Why Projects Fail, No Matter the Domain When We Say Risk What Do We Really Mean? How to Deal With Complexity In Software Projects? Big Systems Acquisitions - Lessons for ACA Web Site
Categories: Project Management

Handling Requests for Unnecessary Artifacts

Mike Cohn's Blog - Tue, 09/30/2014 - 15:00

The following was originally published in Mike Cohn's monthly newsletter. If you like what you're reading, sign up to have this content delivered to your inbox weeks before it's posted on the blog, here.

“Working software over comprehensive documentation.” You’ve certainly seen that statement on the Agile Manifesto. It is perhaps the most important of the Manifesto’s four value statements—working software is, after all, the reason a team has undertaken a software development effort.

It is also one of the most misused parts of the Manifesto. This is the quote people cite when trying to get out of all documentation, which is not what the Manifesto says we should value.

Some documentation on a project can be great. But most non-agile teams write too much and talk too little. Some agile teams go to the opposite extreme, but many seem to find a good balance.

Occasionally, though, a team and product owner may disagree on the necessity of a document—usually with the product owner wanting a document and the team saying it’s not necessary. I’ve found two guidelines helpful in determining how to handle requests for various artifacts, especially documentation, on an agile project.

Guideline No. 1: If a team would produce an artifact while in the process of creating working software, that artifact is just naturally produced.

This guideline covers essentially everything a team would want to produce while on the way to building a system or product. It includes, for example, source code. It also includes any design documents, user guides and other items that the team wants to produce for the benefit of the current team, future teams maintaining the software or end users.

Guideline No. 2: If an artifact would not naturally be produced in the process of creating working software, the artifact is added to the product backlog.

The second guideline is there to cover cases when the product owner (or any other outside stakeholder) wants an artifact produced (usually a document) that the team would not normally produce.

For example, suppose the product owner asks the team to write a document describing every table and field in the database. I’ve certainly seen projects where such a document has been extremely helpful. (In fact, I’ve both requested and written such a document before.) But, I’ve always seen projects where this would have been unnecessary.

If the team thought this database description document were helpful, they would produce it in the process of creating the working software. And Guideline No. 1 would apply. But if they don’t think this document is necessary, they won’t produce it. Unless, that is, the product owner insists, which is where Guideline No. 2 comes in.

If the product owner wants this document, the product owner creates a new product backlog item saying so. The team can then estimate the time it will take to develop this document, just like they’d estimate any other product backlog item.

Putting an estimate on creating the document makes its cost explicit. This forces a product owner to think about the opportunity cost of developing that document. The product owner will be able to ponder: This five-point document or five points worth of new features?

I don’t know which the product owner will choose, but this approach makes the cost of that artifact explicit, allowing it to be compared with the value of additional features instead.

I’d love to know your thoughts on this. How does your team handle product owner requests for artifacts the team wouldn’t naturally produce? What artifacts does your team find helpful? Please share your thoughts in the discussion below.

Handling Requests for Unnecessary Artifacts

Mike Cohn's Blog - Tue, 09/30/2014 - 15:00

The following was originally published in Mike Cohn's monthly newsletter. If you like what you're reading, sign up to have this content delivered to your inbox weeks before it's posted on the blog, here.

“Working software over comprehensive documentation.” You’ve certainly seen that statement on the Agile Manifesto. It is perhaps the most important of the Manifesto’s four value statements—working software is, after all, the reason a team has undertaken a software development effort.

It is also one of the most misused parts of the Manifesto. This is the quote people cite when trying to get out of all documentation, which is not what the Manifesto says we should value.

Some documentation on a project can be great. But most non-agile teams write too much and talk too little. Some agile teams go to the opposite extreme, but many seem to find a good balance.

Occasionally, though, a team and product owner may disagree on the necessity of a document—usually with the product owner wanting a document and the team saying it’s not necessary. I’ve found two guidelines helpful in determining how to handle requests for various artifacts, especially documentation, on an agile project.

Guideline No. 1: If a team would produce an artifact while in the process of creating working software, that artifact is just naturally produced.

This guideline covers essentially everything a team would want to produce while on the way to building a system or product. It includes, for example, source code. It also includes any design documents, user guides and other items that the team wants to produce for the benefit of the current team, future teams maintaining the software or end users.

Guideline No. 2: If an artifact would not naturally be produced in the process of creating working software, the artifact is added to the product backlog.

The second guideline is there to cover cases when the product owner (or any other outside stakeholder) wants an artifact produced (usually a document) that the team would not normally produce.

For example, suppose the product owner asks the team to write a document describing every table and field in the database. I’ve certainly seen projects where such a document has been extremely helpful. (In fact, I’ve both requested and written such a document before.) But, I’ve always seen projects where this would have been unnecessary.

If the team thought this database description document were helpful, they would produce it in the process of creating the working software. And Guideline No. 1 would apply. But if they don’t think this document is necessary, they won’t produce it. Unless, that is, the product owner insists, which is where Guideline No. 2 comes in.

If the product owner wants this document, the product owner creates a new product backlog item saying so. The team can then estimate the time it will take to develop this document, just like they’d estimate any other product backlog item.

Putting an estimate on creating the document makes its cost explicit. This forces a product owner to think about the opportunity cost of developing that document. The product owner will be able to ponder: This five-point document or five points worth of new features?

I don’t know which the product owner will choose, but this approach makes the cost of that artifact explicit, allowing it to be compared with the value of additional features instead.

I’d love to know your thoughts on this. How does your team handle product owner requests for artifacts the team wouldn’t naturally produce? What artifacts does your team find helpful? Please share your thoughts in the discussion below.

Is Agile Dead or Can Good Software Development Scale?

From the Editor of Methods & Tools - Tue, 09/30/2014 - 13:23
As Agile becomes widely accepted as a software development approach, many large organizations have adopted it, mainly in its Scrum form to reduce development cycle. There might be even a fair share of adopters that are trying really to apply Agile values. If the topic of scaling Agile has been discussed for many years and you can read the excellent books of Graig Larman and Bas Vodde on this topic. We have also recently seen the emergence of proprietary” approaches, like SAFE, to achieve this goal. At the same time, ...

Distributed Agile: Sprint Planning

#6 Make sure the telecommunications tools work.

#6 Make sure the telecommunications tools work.

In Distributed Agile: Distributed Team Degree of Difficulty Matrix, I described the many flavors of distributed Agile teams and the complexity different configurations create. While all things being equal, distributed team are less effective than collocated teams. Never the less, distributed Agile with teams spread across countries, continents and companies have become a fact of life. There are techniques to help distributed Agile teams become more effective. In an environment using Scrum, the first formal activities for most team’s is sprint planning. There are numerous techniques that can help make distributed Agile more effective. These techniques include:

1.   Bring the team physically together. Co-location, whether for a single sprint or some periodic basis, will increase the team’s ability to understand each other and know how to work together more effectively.
2.   Develop a sprint planning checklist. The process of getting together and planning is a fairly predictable process. Capture the typical preparation and meeting tasks and make sure they happen. Items can include booking rooms, securing video or telecom facilities, publishing an agenda with breaks and more.
3.   Review the definition of done. Ensure that everyone understands the organization’s definition of done before the starting to plan. The definition of done will help the team know the tasks they need to complete during the sprint to meet the organization’s (or product owner’s) process standards.
4.   Focus on the stories. Don’t let distractions get in the way of planning. Before beginning the planning session, review the process that will be followed with the entire team. Make sure that planning the next sprint is the only topic on the agenda.
5.   Ensure that the stories have been properly groomed. The stories that the team will accept and plan need to be properly formed and have acceptance criteria. This generally means that the stories that are most apt to be accepted by team (and a few more) need to have been through a grooming session. Make this a prerequisite for the planning meeting.
6.   Make sure the telecommunications tools work and have a backup. Distributed planning means that all of the team will be using the phone or video conference. Make sure they are set up and tested. Also always have a backup plan in case your favorite collaboration tool fails because sooner or later it will. Planning is a whole team activity and when the whole team can’t participate planning, it will lose effectiveness.
7.   Everyone should understand the big picture. Have the product owner provide an overview of the goals of the project, and how the current sprint will support those goals. Repeating the big picture will provide the team with a common touch point to validate progress.
8.   Use physical tools for interaction. Physical tools, like flip charts and card walls, can be difficult when many locations are involved in sprint planning. However, when possible, use physical tools like flip charts and whiteboard and then use webcams (preferable) and cameras to share data. Have one location scribe one story and then switch locations for the next story.
9.   Try multiple facilitators. When a team is evenly distributed between two locations consider having another scrum master act as a second facilitator to ensure everyone stays on track. Similarly, have the Scrum master rotate between locations to facilitate the planning session. This can be very effective in helping each location feel connected.
10.Remember that sprint planning is a team meeting. Make sure everyone is involved.

Sprint planning, done well, helps a team understand what they have to do in order to consider a story complete, both from a functional and technical perspective. Distributed Agile teams will need to focus on making sure that everyone is involved and a part of the planning process. Remember to plan for planning, because when you are on the other end of a phone or videoconferencing the tools, process and logistics can make or break the meeting!


Categories: Process Management

The Cognitive Illusion of Bad Software Project Outcomes

Herding Cats - Glen Alleman - Tue, 09/30/2014 - 00:41

Daniel Kahneman's and Amos Tversky's paper On The Reality of Cognitive Illusion. ‡ They suggest, through their research, that intuitive predictions and judgements are often mediated by a small number of distinctive mental operations, called judgement heuristics. These heuristics often lead to characteristic errors and biases.

For example, the effect of aerial perspective on apparent distance is confirmed by the observation that the same mountain appears closer on a clear day rather than a hazy day. The intuitive predication and judgement of probability are often based on the relations of similarity between evidence and possible outcomes. This representativeness is an assessment of the degree of correspondence between a sample and a population. 

The next heuristic is the availability bias in which the probability is estimated by assessing availability or associative distance. † Experience shows and experiments confirm that large classes are recalled better and faster than instances of less frequent classes. That likely occurrences are easier to imagine than unlikely ones. And associative connections are strengthened when two events frequently co-occur. That these associative bonds are strengthened by repetition is the basis of memory. 

So Here's the Issue

When we hear or read that software projects fail often or Standish report says ..., or a personal anecdote that resonates with our own personal experience, we recall that experience from memory. The actual data from the population of all data are not used for comparison. Rather we assume - by applying the cognitive illusion - that the sample sata represents the large class of population data, since our repeated observations of the sample data class has reinforced our illusion that that sample data IS the population.

This is the core issue with anecdotal information when making decisions in the presence of uncertainty. Or speaking about a condition in the absence of statistically testable hypothesis. Or attempting to convey a message in the absence of external confirmation that the message is on solid footing compared to the population of data.

Why This Is Not Good Management

When we hear we're all bad at making estimates, in the absence of actual population statistics about estimate making, we're using Cognitive Illusions and Availability Heuristics. Because we have personal experience with making bad estimates and the majority of people we associate with have the same experience.

This experience is in no way representative of the population of people tasked with making estimates. This would be irrelevant of course if the conversation were simple chatter at the bar. But once that conversation enters the realm of policy making, method development, or suggestions that the anecdotal observations need to result in changing how business conducts its business - we're bad at making estimates so the solution is to stop making estimates - then both availability bias and Cognitive Illusions have displaced the actual conversation about the very validity of the anecdotal concepts. And it is replaced by strong defense of the cognitively biased dea, no matter the credibility of the concept - which is most often weak at best and simply false at worse.

So next time you hear some statement about something involving observational and anecdotal data, ask a simple question.

What's the process by which these anecdotal observation have been tested in the broader population of conditions?

This is the core issue with the Standish Reports. They are self selected samples of projects that are troubled in the absence of the population of projects that are troubled and not troubled. 

Always ask for references, data representative of the references, and an assessment of the statistical confidence that the anecdotal data is in fact correlated with the population data. Otherwise it's just an opinion, and very likely an uniformed opinion.

And if you're paying money to listen to someone tell you ancedotal data and don't speak up and ask those questions, you've participated in the availability heuristic and cognitive illusion along with the speaker.

† Availability: A Heuristic for Judging Frequency and Probability, Amos Tversky and Daniel Kahneman, a chapter appearing in Cognitive Psychology, 1973

‡ On the Reality of Cognitive Illusions, Daniel Kahneman and Amos Tversky, Psychological Review, Vol. 103, No. 3, pp. 582-591

Categories: Project Management

PostgreSQL: ERROR: column does not exist

Mark Needham - Mon, 09/29/2014 - 23:40

I’ve been playing around with PostgreSQL recently and in particular the Northwind dataset typically used as an introductory data set for relational databases.

Having imported the data I wanted to take a quick look at the employees table:

postgres=# SELECT * FROM employees LIMIT 1;
 EmployeeID | LastName | FirstName |        Title         | TitleOfCourtesy | BirthDate  |  HireDate  |           Address           |  City   | Region | PostalCode | Country |   HomePhone    | Extension | Photo |                                                                                      Notes                                                                                      | ReportsTo |              PhotoPath               
------------+----------+-----------+----------------------+-----------------+------------+------------+-----------------------------+---------+--------+------------+---------+----------------+-----------+-------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------+--------------------------------------
          1 | Davolio  | Nancy     | Sales Representative | Ms.             | 1948-12-08 | 1992-05-01 | 507 - 20th Ave. E.\nApt. 2A | Seattle | WA     | 98122      | USA     | (206) 555-9857 | 5467      | \x    | Education includes a BA IN psychology FROM Colorado State University IN 1970.  She also completed "The Art of the Cold Call."  Nancy IS a member OF Toastmasters International. |         2 | http://accweb/emmployees/davolio.bmp
(1 ROW)

That works fine but what if I only want to return the ‘EmployeeID’ field?

postgres=# SELECT EmployeeID FROM employees LIMIT 1;
ERROR:  COLUMN "employeeid" does NOT exist
LINE 1: SELECT EmployeeID FROM employees LIMIT 1;

I hadn’t realised (or had forgotten) that field names get lower cased so we need to quote the name if it’s been stored in mixed case:

postgres=# SELECT "EmployeeID" FROM employees LIMIT 1;
 EmployeeID 
------------
          1
(1 ROW)

From my reading the suggestion seems to be to have your field names lower cased to avoid this problem but since it’s just a dummy data set I guess I’ll just put up with the quoting overhead for now.

Categories: Programming

R: Deriving a new data frame column based on containing string

Mark Needham - Mon, 09/29/2014 - 22:37

I’ve been playing around with R data frames a bit more and one thing I wanted to do was derive a new column based on the text contained in the existing column.

I started with something like this:

> x = data.frame(name = c("Java Hackathon", "Intro to Graphs", "Hands on Cypher"))
> x
             name
1  Java Hackathon
2 Intro to Graphs
3 Hands on Cypher

And I wanted to derive a new column based on whether or not the session was a practical one. The grepl function seemed to be the best tool for the job:

> grepl("Hackathon|Hands on|Hands On", x$name)
[1]  TRUE FALSE  TRUE

We can then add a column to our data frame with that output:

x$practical = grepl("Hackathon|Hands on|Hands On", x$name)

And we end up with the following:

> x
             name practical
1  Java Hackathon      TRUE
2 Intro to Graphs     FALSE
3 Hands on Cypher      TRUE

Not too tricky but it took me a bit too long to figure it out so I thought I’d save future Mark some time!

Categories: Programming

Instagram Improved their App's Performance. Here's How.

Is flat design just another pretty face or is it a huge performance hack cloaked as a UI revolution? It turns out flat design is a stone cold performance win.

This and more is expertly explained by Tyler Kieft, Engineer at Instagram, in a crisp and content filled talk he gave at the @scale conferenceInstagram on Typical Android. This talk was part of series of talks given by Facebook on how to design for the reality of mobile applications across the globe, where phones are slower, screens are smaller, and networks are slower than they are in the US.

Designing for a typical phone rather than a high-end phone required the Instagram team to rethink their design in a deep way. One of the revelations in Tyler's talk was that moving to a flat design was huge in making the application more beautiful, more usable, and it also substantially increased performance.

This was quite a surprise. I've only ever thought of flat design as just a way to think about how to build pretty UIs. Silly me. Thanks to Tyler for explaining the benefits of flat design so clearly and forcefully, using Instagram as a great example of what is possible.

Flat design is the anti-skeuomorphism, going digital native, eschewing a slavish obsession with the appearance of reality, adopting simple elements, simple typography, flat colors, and simple designs.

Using flat design Instagram was able shave off 120ms from its cold start times. It was also able to reduce the number of assets it took to display the feed screen from 29 assets down to 8 assets. All while making the application more beautiful, more usable, with giving more focus given to the content across different phone sizes.

How did flat design make all this possible? Please keep on reading...

Categories: Architecture

The Future of Jobs

Will you have a job in the future?

What will that job look like and how will the nature of work change?

Will automation take over your job in the near future?

These are the kinds of questions that Ruth Fisher, author of Winning the Hardware-Software Game, has tackled in a series of posts.

I wrote a summary post to distill her big ideas and insights about the future of jobs in my post:

The Future of Jobs

Fisher has done an outstanding job of framing out the landscape and walking the various arguments and perspectives on how automation will change the nature of work and shape the future of jobs.

One of the first things you might be wondering is, what jobs will automation take away?

Fisher addresses that.

Another question is, what new types jobs will be created?

While that’s an exercise for the reader, Fisher provides clues based on what industry luminaries have seen in terms of how jobs are changing.

The key is to know what automation can and can’t do, and to look at the pattern of work in terms of what’s better suited for humans, and what’s better suited for machines.

As one of my mentors puts it, “If the work can be automated, it’s not human.”

He’s a fan of people doing creative, non-routine work, where they can thrive and shine.

As I take on work, or push back on work, I look through a pretty simple lens:

  1. Is the work repetitive in nature? (in which case, something that should be automated)
  2. Is the work a high-value activity? (if not, why am I doing non high-value activities?)
  3. Does the work create greater capability? (for me, the team, the organization, etc.)
  4. Does the work play to my strengths? (if not, who is a better resource or provider.  You grow faster in your strengths, and in today’s world, if people aren’t giving their best where they have their best to give, it leads to a low-impact team that eventually gets out-executed, or put out to Pasteur.)
  5. Does the work lead to world-class impact?  (When everything gets exposed beyond the firewall, and when it’s a globally connected ecosystem, it’s really important to not only bring your A-game, but to play in a way where you can provide the best service in the world for your specific niche.   If you can’t be the best in your niche in a sustainable way, then you’re in the wrong niche.)

I find that by using this simple lens, I tend to take on high-value work that creates high-impact, that cannot be easily automated.  At the same time, while I perform the work, I look for way to turn things into repetitive activities that can be outsources or automated so that I can keep moving up the stack, and producing higher-value work … that’s more human.

Categories: Architecture, Programming

Scale Agile With Small-World Networks Posted

I posted my most recent Pragmatic Manager newsletter, Scale Agile With Small-World Networks on my site.

This is a way you can scale agile out, not up. No hierarchies needed.

Small-world networks take advantage of the fact that people want to help other people in the organization. Unless you have created MBOs (Management By Objectives) that make people not want to help others, people want to see the entire product succeed. That means they want to help others. Small-world networks also take advantage of the best network in your organization—the rumor mill.

If you enjoy reading this newsletter, please do subscribe. I let my readers know about specials that I run for my books and when new books come out first.

Categories: Project Management

What Ever Happened to the Founders of Sierra Online?

Making the Complex Simple - John Sonmez - Mon, 09/29/2014 - 15:00

Some of the fondest memories of my childhood involve playing adventure games like Space Quest, Kings Quest and Quest for Glory. I remember spending countless hours reloading from save spots and trying to figure out a puzzle. I remember that exciting feeling of anticipation when the Sierra logo flashed onto the screen as my 486 […]

The post What Ever Happened to the Founders of Sierra Online? appeared first on Simple Programmer.

Categories: Programming

R: Filtering data frames by column type (‘x’ must be numeric)

Mark Needham - Mon, 09/29/2014 - 06:46

I’ve been working through the exercises from An Introduction to Statistical Learning and one of them required you to create a pair wise correlation matrix of variables in a data frame.

The exercise uses the ‘Carseats’ data set which can be imported like so:

> install.packages("ISLR")
> library(ISLR)
> head(Carseats)
  Sales CompPrice Income Advertising Population Price ShelveLoc Age Education Urban  US
1  9.50       138     73          11        276   120       Bad  42        17   Yes Yes
2 11.22       111     48          16        260    83      Good  65        10   Yes Yes
3 10.06       113     35          10        269    80    Medium  59        12   Yes Yes
4  7.40       117    100           4        466    97    Medium  55        14   Yes Yes
5  4.15       141     64           3        340   128       Bad  38        13   Yes  No
6 10.81       124    113          13        501    72       Bad  78        16    No Yes

filter the categorical variables from a data frame and

If we try to run the ‘cor‘ function on the data frame we’ll get the following error:

> cor(Carseats)
Error in cor(Carseats) : 'x' must be numeric

As the error message suggests, we can’t pass non numeric variables to this function so we need to remove the categorical variables from our data frame.

But first we need to work out which columns those are:

> sapply(Carseats, class)
      Sales   CompPrice      Income Advertising  Population       Price   ShelveLoc         Age   Education 
  "numeric"   "numeric"   "numeric"   "numeric"   "numeric"   "numeric"    "factor"   "numeric"   "numeric" 
      Urban          US 
   "factor"    "factor"

We can see a few columns of type ‘factor’ and luckily for us there’s a function which will help us identify those more easily:

> sapply(Carseats, is.factor)
      Sales   CompPrice      Income Advertising  Population       Price   ShelveLoc         Age   Education 
      FALSE       FALSE       FALSE       FALSE       FALSE       FALSE        TRUE       FALSE       FALSE 
      Urban          US 
       TRUE        TRUE

Now we can remove those columns from our data frame and create the correlation matrix:

> cor(Carseats[sapply(Carseats, function(x) !is.factor(x))])
                  Sales   CompPrice       Income  Advertising   Population       Price          Age    Education
Sales        1.00000000  0.06407873  0.151950979  0.269506781  0.050470984 -0.44495073 -0.231815440 -0.051955242
CompPrice    0.06407873  1.00000000 -0.080653423 -0.024198788 -0.094706516  0.58484777 -0.100238817  0.025197050
Income       0.15195098 -0.08065342  1.000000000  0.058994706 -0.007876994 -0.05669820 -0.004670094 -0.056855422
Advertising  0.26950678 -0.02419879  0.058994706  1.000000000  0.265652145  0.04453687 -0.004557497 -0.033594307
Population   0.05047098 -0.09470652 -0.007876994  0.265652145  1.000000000 -0.01214362 -0.042663355 -0.106378231
Price       -0.44495073  0.58484777 -0.056698202  0.044536874 -0.012143620  1.00000000 -0.102176839  0.011746599
Age         -0.23181544 -0.10023882 -0.004670094 -0.004557497 -0.042663355 -0.10217684  1.000000000  0.006488032
Education   -0.05195524  0.02519705 -0.056855422 -0.033594307 -0.106378231  0.01174660  0.006488032  1.000000000
Categories: Programming

Don Yaeger's 16 Consistent Characteristics of Greatness

Herding Cats - Glen Alleman - Mon, 09/29/2014 - 04:40

Don Yeager has a small book mark sized card on 16 Consistent Characteristics of Greatness. I got my card at a PMI conference where he spoke. I'm repeating them here. Don's talk was about sports people he interviewed for magazines and books. The audience was hard-bitten Government and Industry project and program managers. Those accountable for millions and billions of dollars of high risk, high reward endeavors. After Don finished his talk, no a person in the room had dry eyes. Subscribe to Don's daily message at www.donyaeger.com

How They Think

1. It's personal - they hate to lose more than they love to win.

2. Rubbing elbows - they understand the value  of association.

3. Believe - they have faith in a higher power.

4. Contagious Enthusiasm - they are positive thinkers... They are enthusiastic... and that enthusiasm rubs off.

How They Prepare

5. Hope for the best, but ... They prepare for all possibilities before they step on the field.

6. What Off-Season? They are always working towards the next game... The goal is whart's ahead, and there's always something ahead.

7. Visualize Victory - They see victory before the game begins.

8. Inner Fire - they use adversity as fuel.

How They Work

9. Ice in Their Veins - they are risk-takers and don't fear making a mistake.

10. When All Else Fails - they know how - and when - to adjust their game plan.

11. Ultimate Teammate - they will assume whatever role is necessary for the team to win.

12. Not Just About the Benjamin's - they don't just play for the money.

How They Live

13. Do Unto Others - they know character is defined by how they treat those who cannot help them.

14. When No One Is Watching - they are comfortable in the mirror... They live their life with integrity.

15. When Everyone is Watching - they embrace the idea of being a role model.

16. Records Are Made To Be Broken - they know their legacy isn't what they did on the field. They are well rounded.

Categories: Project Management

SPaMCAST 309 – Agile User Acceptance Testing

www.spamcast.net

http://www.spamcast.net

Listen to the Software Process and Measurement Cast 309

Software Process and Measurement Cast number 309 features our essay on Agile user acceptance testing. Agile user acceptance testing (AUAT) confirms that the output of a project meets the business’ needs and requirements. The concept of acceptance testing early and often is almost inarguable, whether you are using Agile or any other method. AUAT generates early customer feedback, which increases customer satisfaction and reduces the potential for delivering defects. While implementing an effective and efficient AUAT isn’t always easy it most certainly is possible!

The essay begins:

The classic definition of a user acceptance test (UAT) is a process that confirms that the output of a project meets the business needs and requirements. UAT in an Agile project generally is more rigorous and timely than the classic end of project UAT found in waterfall projects. In waterfall projects, the UAT is usually the last step in the development process.  The problem with that classic scenario is that significant defects are found late in the process, or worse, the business discovers that what is being delivered isn’t exactly what they wanted. Agile projects provide a number of opportunities to interject UAT activities throughout the process, starting with the development of user stories, to the sprint reviews and demos, and finally the UAT sprints at the end of a release.  Each level provides a platform for active learning and feedback from the business.

Listen to the rest of the essay, here! —- this will be a link.

Next

SPaMCAST 310 features our interview with Michael Burrows. This is Michael’s second visit to the Software Process and Measurement Cast.  In this visit we discussed his new book, Kanban from the Inside.  The book lays out why Kanban is a management method built on a set of values rather than just a set of techniques. The argument is made that Kanban leads to better outcomes for projects, managers, organizations and customers!

Buy and read the book before the interview!

Upcoming Events

DCG Webinars:

Agile Risk Management – It Is Still Important! October 24, 2014 11:230 EDT

Has the adoption of Agile techniques magically erased risk from software projects? Or, have we just changed how we recognize and manage risk?  Or, more frighteningly, by changing the project environment through adopting Agile techniques, have we tricked ourselves into thinking that risk has been abolished?

Upcoming Conferences:

I will be presenting at the International Conference on Software Quality and Test Management in San Diego, CA on October 1.  I have a great discount code!!!! Contact me if you are interested.

I will be presenting at the North East Quality Council 60th Conference October 21st and 22nd in Springfield, MA.

More on all of these great events in the near future! I look forward to seeing all SPaMCAST readers and listeners that attend these great events!

The Software Process and Measurement Cast has a sponsor.

As many you know I do at least one webinar for the IT Metrics and Productivity Institute (ITMPI) every year. The ITMPI provides a great service to the IT profession. ITMPI’s mission is to pull together the expertise and educational efforts of the world’s leading IT thought leaders and to create a single online destination where IT practitioners and executives can meet all of their educational and professional development needs. The ITMPI offers a premium membership that gives members unlimited free access to 400 PDU accredited webinar recordings, and waives the PDU processing fees on all live and recorded webinars. The Software Process and Measurement Cast some support if you sign up here. All the revenue our sponsorship generates goes for bandwidth, hosting and new cool equipment to create more and better content for you. Support the SPaMCAST and learn from the ITMPI.

Shameless Ad for my book!

Mastering Software Project Management: Best Practices, Tools and Techniques co-authored by Murali Chematuri and myself and published by J. Ross Publishing. We have received unsolicited reviews like the following: “This book will prove that software projects should not be a tedious process, neither for you or your team.” Support SPaMCAST by buying the book here.

Available in English and Chinese.


Categories: Process Management

SPaMCAST 309 – Agile User Acceptance Testing

Software Process and Measurement Cast - Sun, 09/28/2014 - 22:00

 Software Process and Measurement Cast number 309 features our essay on Agile user acceptance testing. Agile user acceptance testing (AUAT) confirms that the output of a project meets the business’ needs and requirements. The concept of acceptance testing early and often is almost inarguable, whether you are using Agile or any other method. AUAT generates early customer feedback, which increases customer satisfaction and reduces the potential for delivering defects. While implementing an effective and efficient AUAT isn’t always easy it most certainly is possible!

The essay begins:

The classic definition of a user acceptance test (UAT) is a process that confirms that the output of a project meets the business needs and requirements. UAT in an Agile project generally is more rigorous and timely than the classic end of project UAT found in waterfall projects. In waterfall projects, the UAT is usually the last step in the development process.  The problem with that classic scenario is that significant defects are found late in the process, or worse, the business discovers that what is being delivered isn’t exactly what they wanted. Agile projects provide a number of opportunities to interject UAT activities throughout the process, starting with the development of user stories, to the sprint reviews and demos, and finally the UAT sprints at the end of a release.  Each level provides a platform for active learning and feedback from the business.

Listen to the rest of the essay!

Next

SPaMCAST 310 features our interview with Michael Burrows. This is Michael’s second visit to the Software Process and Measurement Cast.  In this visit we discussed his new book, Kanban from the Inside.  The book lays out why Kanban is a management method built on a set of values rather than just a set of techniques. The argument is made that Kanban leads to better outcomes for projects, managers, organizations and customers!

Buy and read the book before the interview!

Upcoming Events

DCG Webinars:

Agile Risk Management – It Is Still Important! October 24, 2014 11:230 EDT

Has the adoption of Agile techniques magically erased risk from software projects? Or, have we just changed how we recognize and manage risk?  Or, more frighteningly, by changing the project environment through adopting Agile techniques, have we tricked ourselves into thinking that risk has been abolished?

Upcoming Conferences:

I will be presenting at the International Conference on Software Quality and Test Management in San Diego, CA on October 1.  I have a great discount code!!!! Contact me if you are interested.

I will be presenting at the North East Quality Council 60th Conference October 21st and 22nd in Springfield, MA.

More on all of these great events in the near future! I look forward to seeing all SPaMCAST readers and listeners that attend these great events!

The Software Process and Measurement Cast has a sponsor.

As many you know I do at least one webinar for the IT Metrics and Productivity Institute (ITMPI) every year. The ITMPI provides a great service to the IT profession. ITMPI’s mission is to pull together the expertise and educational efforts of the world’s leading IT thought leaders and to create a single online destination where IT practitioners and executives can meet all of their educational and professional development needs. The ITMPI offers a premium membership that gives members unlimited free access to 400 PDU accredited webinar recordings, and waives the PDU processing fees on all live and recorded webinars. The Software Process and Measurement Cast some support if you sign up here. All the revenue our sponsorship generates goes for bandwidth, hosting and new cool equipment to create more and better content for you. Support the SPaMCAST and learn from the ITMPI.

Shameless Ad for my book!

Mastering Software Project Management: Best Practices, Tools and Techniques co-authored by Murali Chematuri and myself and published by J. Ross Publishing. We have received unsolicited reviews like the following: “This book will prove that software projects should not be a tedious process, neither for you or your team.” Support SPaMCAST by buying the book here.

Available in English and Chinese.

Categories: Process Management

One Week in F#

Phil Trelford's Array - Sun, 09/28/2014 - 20:30

With Sergey Tihon on vacation this week, I’ve collated a one off alternative F# Weekly roundup, covering some of the highlights from another busy week in the F# community.

News in brief

FSharp Logo

Events

This week has seen meetups in Nashville, Raleigh, Portland, Washington DC, Stockholm and London:

The Multi-hit brick! #fsharp #gamedev #breakout @DCFSharp @silverSpoon pic.twitter.com/nVPxUrhIZg

— Wesley Wiser (@wesleywiser) September 25, 2014

Recordings

Upcoming meetups

Upcoming Conferences

Projects

Blogs

FsiBot

.@djidja8 " ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤ ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤ ▤ ⬛ ▤ ⬛ ♙ ⬛ ▤ ⬛ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤ ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ⬛ ▤ ⬛ ▤ ⬛ ▤ ⬛ ▤"

— fsibot (@fsibot) September 22, 2014

Have a great week!

Categories: Programming