The vast majority are working on stuff like the scheduling software. If you try to build the dentist software to the standards for the space shuttle, it will take you 70 years and cost a trillion dollars, and won't be noticeably better than the competition. Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group.
Create a free Team What is Teams? Learn more. Asked 5 years, 2 months ago. Active 4 years, 7 months ago. Viewed 4k times. According to this As opposed to the constraints in other kinds of engineering, where the constraints of what you can build are the constraints of physical systems, the constraints imposed in building large software systems are the limitations of our own minds.
This sounds interesting on paper, but it also got me thinking. What about memory constraints? Shouldn't we also think of how to manage memory to prevent leaks? If we call a recursive function, shouldn't we consider the size of the stack if TCO is not possible? Can someone explain what this means? Improve this question. Reducing scope, project duration and time to market decreases; therefore ROI not only increases, but gets realized much sooner. Adopting Open-Source software is naturally a way to reduce I.
You avoid developing all the equivalent functionality. The broader the Open-Source solution, the more you decrease I. The narrower the proprietary extensions you develop yourself, the smaller the OE. Choose your market so your proprietary development becomes as small as possible. Choose the Open-Source project to maximize coverage of your requirements, and conversely minimize what you have to implement yourself. When it comes to choosing a market, instead of targeting broad markets, by focusing on a market niche i.
For instance, if you were in the CRM business, providing a solution targeted at certain professional categories, with some unique features say complying to law requirement , you can ask for a higher price.
Increasing sales price is a way to increase throughput. Combine this with the previous example: By embracing an Open-Source software as a platform on top of which you can develop your own solutions, you are freeing resources to develop other value adding code. The custom code will add value appreciated by the market niche. With more resources, you can also have more frequent releases, which if paid for increase throughput. Instead, use the freed engineering capabilities to develop further value adding functions or products.
The strategy of embracing an Open-Source project decreases OE just like outsourcing , because there is less work to be done in-house. Outsourcing the development of such functionality, rather than exploiting Open Source software, increases OE but less than doing the development in-house.
By choosing to target a long tail niche market and defining the scope of functionality covered respectively by the Open-Source component and your proprietary development, you give the proprietary code a positive impact on ROI , according to TA.
Choosing Open-Source allows to reduce I. Limiting the scope of the proprietary code reduces OE. The strategy to target a niche market, increases T because higher prices can be commanded. Adopting Open-Source software is seen as I ; with the very beneficial quality of being zero. Though there is a component of OE too, to cover the new kinds of activities that come with Open-Source Software.
Using Open-Source Software is not a zero cost operation. Only the acquisition is zero cost. Consider the total cost of ownership, and at least the expenses for gaining the knowledge about how to use Open-Source Software. Often it also means assigning development resources for integration, extensions and maintenance of Open-Source Software. Time must be invested in tracking down problems in Open-Source Software, especially as is often the case with smaller Open-Source Software solutions when support is not available.
The sum of all these additional OE is negligible compared to the effect of the I we are focusing on. Finally consider that the work on the proprietary code is all covered by OE.
Using just Q appears to consider cost the implied assumption being that cost is proportional to quantity as prevalent over throughput. As illustrated in the example about decreasing operating expenses by avoiding feature creep, the ATPF metric has important practical applications. The throughput per story point just subtracts a constant factor, the totally variable costs, from the revenue figure. Take advantage of these software specific production metrics derived from TA.
Consider the ACPF last. As each software engineering task is performed, CA uses time sheets to add the cost of those tasks to the recorded value of the software being produced. So the longer a project lasts and the more effort it consumes, the more CA values the software asset. PDQ solves everything as though it were in steady state. The tradeoff is that you cannot computer higher order statistics.
Analytic solvers are generally faster than simulators and this makes it ideal for the Performance-by-Design methodology described in the book. PDQ is not a hardwired application constrained to run only on certain personal computers.
Instead, PDQ is provided as open source, written in the C language, to enable it to be used in the environment of your choice—from laptop to cloud. Moreover, PDQ is not a stand-alone application but a library of functions for solving performance models expressed as circuits or networks of queues. This also means that PDQ is available in a number of popular programming languages including C, Perl, Python and more recently, the R statistical language.
You can read more at Link. There are other versions of PDQ available and you are free to try them out instead. You should pick the build of PDQ that works best for you and what you are trying to do. Before you start, please make sure your virtual machine has a route to the internet. You can try pinging or resolving a remote IP address and confirm that you have connectivity. You will also note that all my installation commands are based on Ubuntu Linux. Would recommend you take time going through them.
The science of the study of queues is called Queueing Theory and in many ways was inveted by Anger Krarup Erlang. Emergent properties are a consequence of the relationships between system components. They can therefore only be assessed and measured once the components have been integrated into a system. System reliability is a good example of an emergent property. System failures often occur because of unforeseen inter-relationships between components.
It is practically impossible to anticipate all possible component relationships. System reliability depends on the context where the system is used. A system that is reliable in one environment may be less reliable in a different environment because the physical conditions e. A deterministic system is one where a given sequence of inputs will always produce the same sequence of outputs. Software systems are deterministic; systems that include humans are non-deterministic.
A socio-technical system will not always produce the same sequence of outputs from the same input sequence:. Complex systems are developed to address 'wicked problems' - problems where there cannot be a complete specification. Different stakeholders see the problem in different ways and each has a partial understanding of the issues affecting the system. Consequently, different stakeholders have their own views about whether or not a system is 'successful'.
Success is a judgment and cannot be objectively measured. Success is judged using the effectiveness of the system when deployed rather than judged against the original reasons for procurement. Conceptual design investigates the feasibility of an idea and develops that idea to create an overall vision of a system.
Conceptual design precedes and overlaps with requirements engineering. May involve discussions with users and other stakeholders and the identification of critical requirements. The aim of conceptual design is to create a high-level system description that communicates the system purpose to non-technical decision makers.
System procurement is the process of acquiring a system or systems to meet some identified organizational need.
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