However, our main goal will be to distinguish and characterize the technologies in terms of sustainable development. In the long run, the main question we aim to answer: Is the technology project sustainable or not sustainable? What are the criteria for "good" and "evil" here?
Setting the purpose of evaluation is the key. Without it, the metrics are simply data. There should be a decision focus. Metrics are categorized into quantitative-subjective, qualitative, and integrated metrics. The type is often determined by the availability and accuracy of raw data.
Data must be accessible and affordable; otherwise, assumptions and surrogate information would inevitably undermine the adequacy and validity of assessment.
Standardization and coherence in rules of construction of technology evaluation metrics are yet to be achieved. In the broad area of science and technology, the practice of creating and using metrics is in the form of a "menu. Designing comprehensive universal metrics, which would work as "magic crystal" for decision makers, is difficult, if at all possible, because different stakeholders care about different impacts.
Most analytical approaches separate contexts and rather develop multi-metric frameworks for assessment. The table below lists some examples of metrics used for technology evaluation in various contexts. This list is not exhaustive, by any means, and in each assessment project metrics must be justified and modified for specific research purpose.
While working on this course, you should feel free to modify existing metrics or create new ones for the specific needs of your assessment. There are no "mandatory" criteria for evaluation - it all depends on the purpose and the message you try to deliver. In parentheses, some examples of metrics are given for the case of a wastewater treatment facility. In the above hierarchy, Levels 1 and 2 may be sufficient for understanding the promise of technical performance.
These levels would be primary guides in relationships between research and development sector and industry, which look for reliable and efficient systems.
Ecological perspective would involve Level 3 in order to understand and track environmental impacts. Furthermore, sustainability analysis would have to involve Level 4 at the community scale and Level 5 at the economy scale, since only via thorough lifecycle assessment and system analysis is it possible to identify the correct targets for metric design.
One of the ways to understand if the choice of metric that is adequate to the purpose is sensitivity analysis. By varying impact factors, see how metrics respond. Simulating a series of "what-if" and "what-if-not" scenarios will lead you to designing a proper metric model and defining the boundaries. Which of the following metrics would be suitable for comparing firewood and coal as heating fuels in sustainability analysis?
We all know that the process of repeating actions without change with the expectation of different results is the definition of insanity. But repeating the same work without adjustments that do not achieve goals is the definition of managing by metrics. Why would software developers keep doing something that is not getting them closer to goals such as better software experiences? Because they are focusing on software metrics that do not measure progress toward that goal.
Some software metrics have no value when it comes to indicating software quality or team workflow. Management and software development teams need to work on software metrics that drive progress towards goals and provide verifiable, consistent indicators of progress.
Prefix works with. There is no standard or definition of software metrics that have value to software development teams. And software metrics have different value to different teams. It depends on what are the goals for the software development teams. As a starting point, here are some software metrics that can help developers track their progress. Agile process metrics focus on how agile teams make decisions and plan. These metrics do not describe the software, but they can be used to improve the software development process.
Lead time quantifies how long it takes for ideas to be developed and delivered as software. Lowering lead time is a way to improve how responsive software developers are to customers. Screenshot via Pearsoned. Cycle time describes how long it takes to change the software system and implement that change in production.
Team velocity measures how many software units a team completes in an iteration or sprint. This is an internal metric that should not be used to compare software development teams. The definition of deliverables changes for individual software development teams over time and the definitions are different for different teams. It is important to pay attention to how this software metric trends. Production metrics attempt to measure how much work is done and determine the efficiency of software development teams.
The software metrics that use speed as a factor are important to managers who want software delivered as fast as possible.
Active days is a measure of how much time a software developer contributes code to the software development project. This does not include planning and administrative tasks. The purpose of this software metric is to assess the hidden costs of interruptions. Assignment scope is the amount of code that a programmer can maintain and support in a year. This software metric can be used to plan how many people are needed to support a software system and compare teams.
Efficiency attempts to measure the amount of productive code contributed by a software developer. The amount of churn shows the lack of productive code. Thus a software developer with a low churn could have highly efficient code.
Code churn represents the number of lines of code that were modified, added or deleted in a specified period of time. If code churn increases, then it could be a sign that the software development project needs attention.
Example Code Churn report, screenshot via Visual Studio. Impact measures the effect of any code change on the software development project. A code change that affects multiple files could have more impact than a code change affecting a single file.
Both metrics measure how the software performs in the production environment. Since software failures are almost unavoidable, these software metrics attempt to quantify how well the software recovers and preserves data. Image via Wikimedia Commons. Application crash rate is calculated by dividing how many times an application fails F by how many times it is used U.
Security metrics reflect a measure of software quality. These metrics need to be tracked over time to show how software development teams are developing security responses.
Mean time to repair in this context measures the time from the security breach discovery to when a working remedy is deployed. Size-oriented metrics focus on the size of the software and are usually expressed as kilo lines of code KLOC.
It is a fairly easy software metric to collect once decisions are made about what constitutes a line of code. When was the last time you made sure your monitored metrics are as effective as they could be? He is the most experienced business intelligence practitioner to tackle QuickBooks.
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