Usually when I am online making a payment or using social media, I am not thinking about software quality. But lately I feel like I have been encountering more bugs than usual.  From activities like clicking on a link where I should be able to input my payment information, to doing a search and receiving an error message, or being redirected to a completely different page which had nothing to do with the mission I had set out to accomplish.  These bugs are sometimes frustrating and I started to wonder what could have been done to prevent these from being released into production.

Since I spend a lot of time speaking with people that manage software projects, I have noticed that quality is often one of the most overlooked aspects of a software system. People I’ve spoken with have mentioned that quality is often not even discussed during the early planning stages of development projects, but it is usually a deciding factor when the software is ready to be released and should be considered from the beginning of the project.

Using a tool like SLIM early in the planning stages of a project can help us with these issues. Not only can it provide reliable cost and schedule estimates, but it can also help estimate how many defects one can expect to find between system test and actual delivery. It can also estimate the Mean Time to Defect (MTTD), which is the amount of time between errors discovered.

QSM recently published the sixth article in the QSM Agile Round Table series. The QSM Agile Round Table was formed to discuss the role of estimation in agile environments. QSM customers shared their questions, challenges, and experiences on the relevance and benefits of scope-based estimation in an agile environment. The previous two articles focused on determining size in a consistent enough manner across multiple products, projects, and agile teams in order to have good historical data on which to base an estimate. They looked at several possible units of measure for software size, including story points, function points, and source lines of code (SLOC). SLIM-Estimate and SLIM-Collaborate permit any of those units, as well as others, to be used for software sizing. In order to use a sizing unit other than SLOC in the SLIM tools, you must assign a gearing factor.  For function points, gearing factors are discussed here. In this article, QSM's Andy Berner addresses ways of choosing a gearing factor for story points.

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QSM recently published the fifth article in the QSM Agile Round Table series.  The QSM Agile Round Table was formed to discuss the role of estimation in agile environments.  QSM customers shared their questions, challenges, and experiences on the relevance and benefits of scope-based estimation in an agile environment. This article continues the focus from the previous article on determining size in a consistent enough manner across multiple products, projects, and agile teams so that you have good historical data on which to base an estimate. QSM's Andy Berner looks at other sizing units besides story points, in particular function points and source lines of code. 

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QSM is pleased to share the fourth article in the QSM Agile Round Table series.  The QSM Agile Round Table was formed to discuss the role of estimation in agile environments.  QSM customers shared their questions, challenges, and experiences on the relevance and benefits of scope-based estimation in an agile environment. The previous article in this series, “Big Rock Estimation” written by Aaron Jeutter from Rockwell Automation, addressed the question of how to determine the size of a release absent of a “big upfront requirements phase”, and thus when the requirements are only known at a very high level and subject to refinement and change.  The next three articles written by Andy Berner will focus on determining size in a consistent enough manner across multiple products, projects, and agile teams so that you have good historical data on which to base an estimate. They will also show how to apply these techniques with the SLIM Suite of products.

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Executive teams and your end clients always want to know, “how good are our development teams?”  Agile development teams usually promise that they can deliver faster and cheaper with better quality.  But how do you truly know this is the case?  The only way to really know is to apply quantitative measurement to agile.  With the SLIM solution you can look at a completed agile project and determine the productivity that was demonstrated.  This productivity metric encompasses all environmental factors, such as how good is the skill level and experience of your development team?  How good are the tools and methodology in place?  What is the technical complexity of the software you are building? 

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QSM recently announced a major update to the QSM Software Project Database, a large and robust body of data that helps software and IT professionals estimate the cost, time and effort requirements for their software and systems projects. As a result, QSM clients and SLIM Suite users can benefit from the most up-to-date and expansive software project benchmarking data, particularly in the agile domain.

With this large update, we’ve validated and added more than 2,500 new projects across nine major application domains (Avionics, IT, Command & Control, Microcode, Process Control, Real Time, Scientific, System Software, and Telecom) and 45 sub-domains. The result is a database with more than 13,000 completed projects, extending what is already the largest continuously updated software project metrics database in the world.

With these enhanced data insights -- all gathered from real-world projects -- SLIM Suite users have access to the most up-to-date software project benchmarking data and can quickly and easily sanity-check estimates against industry data.

IT and Agile Projects Get a Boost

The Scaled Agile Framework (SAFe) has realized widespread adoption by organizations desiring to accelerate product delivery without sacrificing quality. The alignment of product vision, business value, and development velocity is an key contributor to successful large-scale agile development.  Presented by QSM's Laura Zuber on June 20 at 11:00 AM EST, this upcoming ITMPI webinar demonstrates how scope-based estimation techniques can be used to model the relationship between vision, value, and velocity at different levels of the framework and stages of implementation to guide release planning and management decisions.

Laura Zuber has 25 years of experience in software development consulting, training, and support. She has conducted training and coaching sessions for all QSM SLIM-Suite tools and helped customers implement SLIM across a wide variety of processes and platforms. Laura has managed software development projects, served as a senior software process improvement specialist, performed process assessments, designed and implemented best practices, and authored numerous training programs. She is a Certified Scrum Master and lead consultant for using SLIM with agile development.

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For a number of years, the federal government has been on a mission to reduce waste and enhance efficiencies across departments, including IT. But according to the CIO Council’s 2017 State of Federal Information Technology report, 43% of the federal government’s $80 billion in IT projects cataloged in September 2016 were listed as over budget or behind schedule. In this article for GCN, Doug Putnam takes a look at some of the common pitfalls that lead to project cost and schedule overruns and how parametric estimation can help government CIOs and their teams avoid these traps.

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With agile projects, we hear a lot about the planning benefits of having a fixed number of people with a fixed number of sprints.  All great stuff when it comes to finishing on time and within budget. But one of the things we also need to focus on is the quality of the software.  We often hear stories about functionality getting put on hold because of reliability goals not being met.

There are some agile estimation models available to help with this, and they can provide this information at the release level, before the project starts or during those early sprints. They provide this information by leveraging historical data along with time-tested forecasting models that are built to support agile projects. 

In the first view, you can see the estimate for the number of defects remaining. This is a big picture view of the overall release. Product managers and anyone concerned with client satisfaction can use these models to predict when the software will be reliable enough for delivery to the customer.

In the second view, you can see the total MTTD (Mean Time to Defect) and the MTTD by severity level. The MTTD is the amount of time that elapses between discovered defects. Each chart shows the months progressing on the horizontal axis and the MTTD (in days) improve over time on the vertical axis. 

Developing software within the DoD presents a unique set of challenges, including but not limited to budget cuts, Congressionally mandated changes, changing software requirements, and so on. It should come as no surprise, therefore, that cost estimators have faced significant challenges when estimating systems in the Defense arena. A recent initiative put forth by the DoD was to improve its estimation process by leveraging historical data collected from forensic analyses of recently completed software development efforts. This article by Taylor Putnam-Majarian and John Staiger, discusses (1) some of the challenges faced throughout this initiative, (2) the data collection process, and (3) how one can leverage data to improve cost estimates. This article was originally published in Crosstalk Magazine.

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