Are we Agile? If we ask a leader we'll get one perspective, but if we ask each person on the team we may be surprised by the variety of answers. Since 2002, IBM has used agile evaluation frameworks with dozens of teams to help them learn, improve, and share their experiences with agile practices. The metrics in the Extreme Programming Evaluation Framework, or (XP:EF) originally focused on XP, and similar instances covered other methods.[i] But because the framework can be used with a broader set of practices, it's simpler to say "the Agile Evaluation Framework" (Agile:EF). This article shares tips on using the framework in a lightweight manner to leverage "the simplest metrics that could possibly work."
Without a universal definition of agile, it can be difficult to separate those who are truly practicing agile, and those who have it wrong. While agile has grown immensely popular over the years, there are still some who have yet to convert. We took a look at each of these groups.
Software development is seen as chronically chaotic and complex to the extent that project management can achieve little control over projects or outcome [1, 2]. Recently, we have come into a new era of hope; hope of getting people - real people, users, both naïve and sophisticated - more involved with, more relevant to, and more visible in software development.
The goal of this paper is not to discuss the process, metrics, automation and outsourcing in great detail but to understand them well enough to hopefully find a common sense approach toward a workable solution of today's complex, demanding and ever changing nature of software testing.
Have you noticed that one of the easiest things to do in life is to come up with solutions, but one of the hardest is to actually implement them? In this article, Clarke Ching shows you how and when to use the questions "Why?" and "Why not?" along with a little "And Thinking" to turn a half-baked solution into one that is actually implementable in real life.
This article details an approach that managers can use to interpret metrics, which includes analyzing data, identifying important factors, and showing the interrelation between different metrics and their impact on the overall project health. By reading this article, practicing managers will not only be able to interpret the metrics in a meaningful way, but also be able to define more meaningful metrics for their day-to-day use. This article does not restrict itself to test metrics; it extends out to an organization's overall metrics program.
Dion Johnson use the martial arts metaphor four common issues with automated tests and how test automation specialiasts can "train" their scripts to identify, capture, and handle these problems. In this week's column, Dion talks about how to make develop test automation scripts that defend themselves from problems and failures.
There are a lot of tools available to testers. Some good, some not so good. As we use and gain experience with the various test tools, the set of tools in our tool box becomes larger. Having a large set of tools in your toolbox allows you to better adapt to any test situation.
Applying Root Cause Analysis (RCA) to software problems is fundamentally different from applying it to other engineering disciplines. Rather than analyzing a single major failure, we are usually analyzing a large number of failures with software. In this week's column, Ed Weller explains how to use RCA to your advantage.
The paper focuses on the new emerging concept of software reuse which is aimed at synergizing the focus on developing new software through software reuse. It hinges on the concept of componentization and how it eventually helps in reducing the lead time. This combined effort also leads to a domino effect of reduced lead time,testing time and improvement in the product quality as a whole.
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