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Learn how Project Delivery Rate can be estimated using software and team sizes, using the ISBSG book, “Practical Software Project Estimation”.
Big Data in software engineering estimation, can be a valuable tool to improve the accuracy, efficiency, and transparency of the estimation process. However, it is important to be aware of the challenges associated with using big data before adopting this approach.
Estimating the cost and schedule of custom software development from preliminary requirements or a Concept of Operations (ConOps) document can be challenging. Software size and productivity are major drivers of software development costs. This presentation outlines a streamlined six-step process to develop a data-founded and defensible cost and schedule ROM estimate from high-level requirements/ConOps documents. A sample ConOps case study will be used to demonstrate the six-step process.
Software development projects often fail to meet expectations, exceed budgets, and overrun schedules. Often, the cause is bad estimation practices.
Nesma and the International Cost Estimation and Analysis Association (ICEAA) developed the Cost Estimation Body of Knowledge for Software (CEBoK-S).
This presentation addresses the industry’s main issues, CEBoK-S and aims to solve these issues. ISBSG data is used to estimate software projects using functional size and relevant historic data.
We present the methods that focus solutions to the “Next Release Problem” for agile-driven developments. This includes: new algorithm proposals and novel techniques that model how the software requirements interact .
Non-Functional Requirements are a challenging concept. How can NFR data be gathered and used to improve effort/cost estimations.
The presentation describes capabilities and capability-based planning. Discussed are the challenges in software cost estimation and how capability-based cost estimation models for software differ throughout the life cycle. I conclude with a summary methodology to develop a capability-based cost estimation for software, which is to define capability groups with similar software functions and associated effort ranges.
A study of agile projects in the ISBSG dataset that included metrics such as the number of sprints/iterations and sprint/iteration length was done. This resulted in a normalized velocity metric (FPs Per Sprint Week/Person) that could be used to for benchmarking purposes. This metric, along with team size could be used to examine the productivity changes with different team sizes.
Create new functionality, enhance existing functionality, remove technical debt, compensate respective effort in a controlled, measurable way.
This short paper examines whether there have been more New Development or Enhancement type projects submitted to the ISBSG Repository. It investigates whether the median project size for these projects has increased or decreased over time.
The short paper analyses the effort spent on general and specific software maintenance and support activities.
How would you like to have your project’s productivity benchmarked against the ISBSG Repository? This short paper explains how you can receive a free benchmark report, when you submit project data to the ISBSG repository.
This short paper compares the productivity of projects that have different application types, from the ISBSG Repository. The application types are: Business Applications, Real-Time Applications, Mathematically-Intensive Application and Infrastructure Software.
ITIL4 has 7 recommendations to improving services. They are relevant for all businesses. Use real-life examples to apply these principles from a measurement perspective .
Harold Van Heeringen has extensively used ISBSG Data as a benchmarking tool for client organizations.
In this webinar, Harold uses his expertise to demonstrate how ISBSG data (in Excel-format and via the ISBSG Productivity Data Query Tool) can be used to improve estimation and planning.