requirements identified by the operational and technical stakeholders. A product owner or a scrum master manages the backlogs, updating them based on the results of releases and sprints, changing operational estimates effort for the sprint, and often decomposes the stories into tasks. Typically, the scrum master and development team manage the sprint backlog.5 The scope of a sprint, unlike that of a release manager, product owner, tester, and system engineer, and a development team led by a scrum master (scrum master and product owner are roles specific to the Scrum methodology, and may vary if using other

disposal. julia> Threads.nthreads() 4 300CHAPTER 24. MULTI-THREADING 301 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Array{Int64,1}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes. Note realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

disposal. julia> Threads.nthreads() 4 300CHAPTER 24. MULTI-THREADING 301 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Array{Int64,1}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes. Note realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

disposal. 318CHAPTER 25. MULTI-THREADING 319 julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Array{Int64,1}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

disposal. 318CHAPTER 25. MULTI-THREADING 319 julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Array{Int64,1}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

disposal. 318CHAPTER 25. MULTI-THREADING 319 julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Array{Int64,1}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

(_| | | Version 1.13.0-DEV.639 (2025-05-25) _/ |\__'_|_|_|\__'_| | Commit 925d504ade4 (1 day old master) |__/ | julia> 1 + 2 3 julia> ans 3 To exit the interactive session, type CTRL-D (press the verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Vector{Int64}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER

verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Vector{Int64}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Vector{Int64}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used

verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you addprocs(2) 2-element Vector{Int64}: 2 3 Module Distributed must be explicitly loaded on the master process before invoking addprocs. It is automatically made available on the worker processes.CHAPTER realized, while memory associated with globals may be collected when they are reas- signed on the master, no such action is taken on the workers as the bindings continue to be valid. clear! can be used