Objective C Runtime Reference
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Palmetto Tatters Guild Glossary of Tatting Terms (Not All Inclusive!)
Palmetto Tatters Guild Glossary of Tatting Terms (not all inclusive!) Tat Days Written * or or To denote repeating lines of a pattern. Example: Rep directions or # or § from * 7 times & ( ) Eg. R: 5 + 5 – 5 – 5 (last P of prev R). Modern B Bead (Also see other bead notation below) notation BTS Bare Thread Space B or +B Put bead on picot before joining BBB B or BBB|B Three beads on knotting thread, and one bead on core thread Ch Chain ^ Construction picot or very small picot CTM Continuous Thread Method D Dimple: i.e. 1st Half Double Stitch X4, 2nd Half Double Stitch X4 dds or { } daisy double stitch DNRW DO NOT Reverse Work DS Double Stitch DP Down Picot: 2 of 1st HS, P, 2 of 2nd HS DPB Down Picot with a Bead: 2 of 1st HS, B, 2 of 2nd HS HMSR Half Moon Split Ring: Fold the second half of the Split Ring inward before closing so that the second side and first side arch in the same direction HR Half Ring: A ring which is only partially closed, so it looks like half of a ring 1st HS First Half of Double Stitch 2nd HS Second Half of Double Stitch JK Josephine Knot (Ring made of only the 1st Half of Double Stitch OR only the 2nd Half of Double Stitch) LJ or Sh+ or SLJ Lock Join or Shuttle join or Shuttle Lock Join LPPCh Last Picot of Previous Chain LPPR Last Picot of Previous Ring LS Lock Stitch: First Half of DS is NOT flipped, Second Half is flipped, as usual LCh Make a series of Lock Stitches to form a Lock Chain MP or FP Mock Picot or False Picot MR Maltese Ring Pearl Ch Chain made with pearl tatting technique (picots on both sides of the chain, made using three threads) P or - Picot Page 1 of 4 PLJ or ‘PULLED LOOP’ join or ‘PULLED LOCK’ join since it is actually a lock join made after placing thread under a finished ring and pulling this thread through a picot. -
Scoping Changes with Method Namespaces
Scoping Changes with Method Namespaces Alexandre Bergel ADAM Project, INRIA Futurs Lille, France [email protected] Abstract. Size and complexity of software has reached a point where modular constructs provided by traditional object-oriented programming languages are not expressive enough. A typical situation is how to modify a legacy code without breaking its existing clients. We propose method namespaces as a visibility mechanism for behavioral refine- ments of classes (method addition and redefinition). New methods may be added and existing methods may be redefined in a method namespace. This results in a new version of a class accessible only within the defining method namespace. This mechanism, complementary to inheritance in object-orientation and tradi- tional packages, allows unanticipated changes while minimizing the impact on former code. Method Namespaces have been implemented in the Squeak Smalltalk system and has been successfully used to provide a translated version of a library without ad- versely impacting its original clients. We also provide benchmarks that demon- strate its application in a practical setting. 1 Introduction Managing evolution and changes is a critical part of the life cycle of all software sys- tems [BMZ+05, NDGL06]. In software, changes are modeled as a set of incremental code refinements such as class redefinition, method addition, and method redefinition. Class-based object-oriented programming languages (OOP) models code refinements with subclasses that contain behavioral differences. It appears that subclassing is well adapted when evolution is anticipated. For example, most design patterns and frame- works rely on class inheritance to express future anticipated adaptation and evolution. However, subclassing does not as easily help in expressing unanticipated software evo- lution [FF98a, BDN05b]. -
Memory Management and Garbage Collection
Overview Memory Management Stack: Data on stack (local variables on activation records) have lifetime that coincides with the life of a procedure call. Memory for stack data is allocated on entry to procedures ::: ::: and de-allocated on return. Heap: Data on heap have lifetimes that may differ from the life of a procedure call. Memory for heap data is allocated on demand (e.g. malloc, new, etc.) ::: ::: and released Manually: e.g. using free Automatically: e.g. using a garbage collector Compilers Memory Management CSE 304/504 1 / 16 Overview Memory Allocation Heap memory is divided into free and used. Free memory is kept in a data structure, usually a free list. When a new chunk of memory is needed, a chunk from the free list is returned (after marking it as used). When a chunk of memory is freed, it is added to the free list (after marking it as free) Compilers Memory Management CSE 304/504 2 / 16 Overview Fragmentation Free space is said to be fragmented when free chunks are not contiguous. Fragmentation is reduced by: Maintaining different-sized free lists (e.g. free 8-byte cells, free 16-byte cells etc.) and allocating out of the appropriate list. If a small chunk is not available (e.g. no free 8-byte cells), grab a larger chunk (say, a 32-byte chunk), subdivide it (into 4 smaller chunks) and allocate. When a small chunk is freed, check if it can be merged with adjacent areas to make a larger chunk. Compilers Memory Management CSE 304/504 3 / 16 Overview Manual Memory Management Programmer has full control over memory ::: with the responsibility to manage it well Premature free's lead to dangling references Overly conservative free's lead to memory leaks With manual free's it is virtually impossible to ensure that a program is correct and secure. -
Project Snowflake: Non-Blocking Safe Manual Memory Management in .NET
Project Snowflake: Non-blocking Safe Manual Memory Management in .NET Matthew Parkinson Dimitrios Vytiniotis Kapil Vaswani Manuel Costa Pantazis Deligiannis Microsoft Research Dylan McDermott Aaron Blankstein Jonathan Balkind University of Cambridge Princeton University July 26, 2017 Abstract Garbage collection greatly improves programmer productivity and ensures memory safety. Manual memory management on the other hand often delivers better performance but is typically unsafe and can lead to system crashes or security vulnerabilities. We propose integrating safe manual memory management with garbage collection in the .NET runtime to get the best of both worlds. In our design, programmers can choose between allocating objects in the garbage collected heap or the manual heap. All existing applications run unmodified, and without any performance degradation, using the garbage collected heap. Our programming model for manual memory management is flexible: although objects in the manual heap can have a single owning pointer, we allow deallocation at any program point and concurrent sharing of these objects amongst all the threads in the program. Experimental results from our .NET CoreCLR implementation on real-world applications show substantial performance gains especially in multithreaded scenarios: up to 3x savings in peak working sets and 2x improvements in runtime. 1 Introduction The importance of garbage collection (GC) in modern software cannot be overstated. GC greatly improves programmer productivity because it frees programmers from the burden of thinking about object lifetimes and freeing memory. Even more importantly, GC prevents temporal memory safety errors, i.e., uses of memory after it has been freed, which often lead to security breaches. Modern generational collectors, such as the .NET GC, deliver great throughput through a combination of fast thread-local bump allocation and cheap collection of young objects [63, 18, 61]. -
Investigating Powershell Attacks
Investigating PowerShell Attacks Black Hat USA 2014 August 7, 2014 PRESENTED BY: Ryan Kazanciyan, Matt Hastings © Mandiant, A FireEye Company. All rights reserved. Background Case Study WinRM, Victim VPN SMB, NetBIOS Attacker Victim workstations, Client servers § Fortune 100 organization § Command-and-control via § Compromised for > 3 years § Scheduled tasks § Active Directory § Local execution of § Authenticated access to PowerShell scripts corporate VPN § PowerShell Remoting © Mandiant, A FireEye Company. All rights reserved. 2 Why PowerShell? It can do almost anything… Execute commands Download files from the internet Reflectively load / inject code Interface with Win32 API Enumerate files Interact with the registry Interact with services Examine processes Retrieve event logs Access .NET framework © Mandiant, A FireEye Company. All rights reserved. 3 PowerShell Attack Tools § PowerSploit § Posh-SecMod § Reconnaissance § Veil-PowerView § Code execution § Metasploit § DLL injection § More to come… § Credential harvesting § Reverse engineering § Nishang © Mandiant, A FireEye Company. All rights reserved. 4 PowerShell Malware in the Wild © Mandiant, A FireEye Company. All rights reserved. 5 Investigation Methodology WinRM PowerShell Remoting evil.ps1 backdoor.ps1 Local PowerShell script Persistent PowerShell Network Registry File System Event Logs Memory Traffic Sources of Evidence © Mandiant, A FireEye Company. All rights reserved. 6 Attacker Assumptions § Has admin (local or domain) on target system § Has network access to needed ports on target system § Can use other remote command execution methods to: § Enable execution of unsigned PS scripts § Enable PS remoting © Mandiant, A FireEye Company. All rights reserved. 7 Version Reference 2.0 3.0 4.0 Requires WMF Requires WMF Default (SP1) 3.0 Update 4.0 Update Requires WMF Requires WMF Default (R2 SP1) 3.0 Update 4.0 Update Requires WMF Default 4.0 Update Default Default Default (R2) © Mandiant, A FireEye Company. -
Garbage Collection for Java Distributed Objects
GARBAGE COLLECTION FOR JAVA DISTRIBUTED OBJECTS by Andrei A. Dãncus A Thesis Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements of the Degree of Master of Science in Computer Science by ____________________________ Andrei A. Dãncus Date: May 2nd, 2001 Approved: ___________________________________ Dr. David Finkel, Advisor ___________________________________ Dr. Mark L. Claypool, Reader ___________________________________ Dr. Micha Hofri, Head of Department Abstract We present a distributed garbage collection algorithm for Java distributed objects using the object model provided by the Java Support for Distributed Objects (JSDA) object model and using weak references in Java. The algorithm can also be used for any other Java based distributed object models that use the stub-skeleton paradigm. Furthermore, the solution could also be applied to any language that supports weak references as a mean of interaction with the local garbage collector. We also give a formal definition and a proof of correctness for the proposed algorithm. i Acknowledgements I would like to express my gratitude to my advisor Dr. David Finkel, for his encouragement and guidance over the last two years. I also want to thank Dr. Mark Claypool for being the reader of this thesis. Thanks to Radu Teodorescu, co-author of the initial JSDA project, for reviewing portions of the JSDA Parser. ii Table of Contents 1. Introduction……………………………………………………………………………1 2. Background and Related Work………………………………………………………3 2.1 Distributed -
Logix 5000 Controllers Security, 1756-PM016O-EN-P
Logix 5000 Controllers Security 1756 ControlLogix, 1756 GuardLogix, 1769 CompactLogix, 1769 Compact GuardLogix, 1789 SoftLogix, 5069 CompactLogix, 5069 Compact GuardLogix, Studio 5000 Logix Emulate Programming Manual Original Instructions Logix 5000 Controllers Security Important User Information Read this document and the documents listed in the additional resources section about installation, configuration, and operation of this equipment before you install, configure, operate, or maintain this product. Users are required to familiarize themselves with installation and wiring instructions in addition to requirements of all applicable codes, laws, and standards. Activities including installation, adjustments, putting into service, use, assembly, disassembly, and maintenance are required to be carried out by suitably trained personnel in accordance with applicable code of practice. If this equipment is used in a manner not specified by the manufacturer, the protection provided by the equipment may be impaired. In no event will Rockwell Automation, Inc. be responsible or liable for indirect or consequential damages resulting from the use or application of this equipment. The examples and diagrams in this manual are included solely for illustrative purposes. Because of the many variables and requirements associated with any particular installation, Rockwell Automation, Inc. cannot assume responsibility or liability for actual use based on the examples and diagrams. No patent liability is assumed by Rockwell Automation, Inc. with respect to use of information, circuits, equipment, or software described in this manual. Reproduction of the contents of this manual, in whole or in part, without written permission of Rockwell Automation, Inc., is prohibited. Throughout this manual, when necessary, we use notes to make you aware of safety considerations. -
Multithreading Design Patterns and Thread-Safe Data Structures
Lecture 12: Multithreading Design Patterns and Thread-Safe Data Structures Principles of Computer Systems Autumn 2019 Stanford University Computer Science Department Lecturer: Chris Gregg Philip Levis PDF of this presentation 1 Review from Last Week We now have three distinct ways to coordinate between threads: mutex: mutual exclusion (lock), used to enforce critical sections and atomicity condition_variable: way for threads to coordinate and signal when a variable has changed (integrates a lock for the variable) semaphore: a generalization of a lock, where there can be n threads operating in parallel (a lock is a semaphore with n=1) 2 Mutual Exclusion (mutex) A mutex is a simple lock that is shared between threads, used to protect critical regions of code or shared data structures. mutex m; mutex.lock() mutex.unlock() A mutex is often called a lock: the terms are mostly interchangeable When a thread attempts to lock a mutex: Currently unlocked: the thread takes the lock, and continues executing Currently locked: the thread blocks until the lock is released by the current lock- holder, at which point it attempts to take the lock again (and could compete with other waiting threads). Only the current lock-holder is allowed to unlock a mutex Deadlock can occur when threads form a circular wait on mutexes (e.g. dining philosophers) Places we've seen an operating system use mutexes for us: All file system operation (what if two programs try to write at the same time? create the same file?) Process table (what if two programs call fork() at the same time?) 3 lock_guard<mutex> The lock_guard<mutex> is very simple: it obtains the lock in its constructor, and releases the lock in its destructor. -
Memory Management with Explicit Regions by David Edward Gay
Memory Management with Explicit Regions by David Edward Gay Engineering Diploma (Ecole Polytechnique F´ed´erale de Lausanne, Switzerland) 1992 M.S. (University of California, Berkeley) 1997 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the GRADUATE DIVISION of the UNIVERSITY of CALIFORNIA at BERKELEY Committee in charge: Professor Alex Aiken, Chair Professor Susan L. Graham Professor Gregory L. Fenves Fall 2001 The dissertation of David Edward Gay is approved: Chair Date Date Date University of California at Berkeley Fall 2001 Memory Management with Explicit Regions Copyright 2001 by David Edward Gay 1 Abstract Memory Management with Explicit Regions by David Edward Gay Doctor of Philosophy in Computer Science University of California at Berkeley Professor Alex Aiken, Chair Region-based memory management systems structure memory by grouping objects in regions under program control. Memory is reclaimed by deleting regions, freeing all objects stored therein. Our compiler for C with regions, RC, prevents unsafe region deletions by keeping a count of references to each region. RC's regions have advantages over explicit allocation and deallocation (safety) and traditional garbage collection (better control over memory), and its performance is competitive with both|from 6% slower to 55% faster on a collection of realistic benchmarks. Experience with these benchmarks suggests that modifying many existing programs to use regions is not difficult. An important innovation in RC is the use of type annotations that make the structure of a program's regions more explicit. These annotations also help reduce the overhead of reference counting from a maximum of 25% to a maximum of 12.6% on our benchmarks. -
Resource Management: Linux Kernel Namespaces and Cgroups
Resource management: Linux kernel Namespaces and cgroups Rami Rosen [email protected] Haifux, May 2013 www.haifux.org 1/121 http://ramirose.wix.com/ramirosen TOC Network Namespace PID namespaces UTS namespace Mount namespace user namespaces cgroups Mounting cgroups links Note: All code examples are from for_3_10 branch of cgroup git tree (3.9.0-rc1, April 2013) 2/121 http://ramirose.wix.com/ramirosen General The presentation deals with two Linux process resource management solutions: namespaces and cgroups. We will look at: ● Kernel Implementation details. ●what was added/changed in brief. ● User space interface. ● Some working examples. ● Usage of namespaces and cgroups in other projects. ● Is process virtualization indeed lightweight comparing to Os virtualization ? ●Comparing to VMWare/qemu/scaleMP or even to Xen/KVM. 3/121 http://ramirose.wix.com/ramirosen Namespaces ● Namespaces - lightweight process virtualization. – Isolation: Enable a process (or several processes) to have different views of the system than other processes. – 1992: “The Use of Name Spaces in Plan 9” – http://www.cs.bell-labs.com/sys/doc/names.html ● Rob Pike et al, ACM SIGOPS European Workshop 1992. – Much like Zones in Solaris. – No hypervisor layer (as in OS virtualization like KVM, Xen) – Only one system call was added (setns()) – Used in Checkpoint/Restart ● Developers: Eric W. biederman, Pavel Emelyanov, Al Viro, Cyrill Gorcunov, more. – 4/121 http://ramirose.wix.com/ramirosen Namespaces - contd There are currently 6 namespaces: ● mnt (mount points, filesystems) ● pid (processes) ● net (network stack) ● ipc (System V IPC) ● uts (hostname) ● user (UIDs) 5/121 http://ramirose.wix.com/ramirosen Namespaces - contd It was intended that there will be 10 namespaces: the following 4 namespaces are not implemented (yet): ● security namespace ● security keys namespace ● device namespace ● time namespace. -
Moscow ML .Net Owner's Manual
Moscow ML .Net Owner's Manual Version 0.9.0 of November 2003 Niels Jørgen Kokholm, IT University of Copenhagen, Denmark Peter Sestoft, Royal Veterinary and Agricultural University, Copenhagen, Denmark This document describes Moscow ML .Net 0.9.0, a port of Moscow ML 2.00 to the .Net platform. The focus is on how Moscow ML .Net differs from Moscow ML 2.0. Three other documents, the Moscow ML Owner’s Manual [7], the Moscow ML Language Overview [5] and the Moscow ML Library Documentation [6] describe general aspects of the Moscow ML system. Moscow ML implements Standard ML (SML), as defined in the 1997 Definition of Standard ML, including the SML Modules language and some extensions. Moreover, Moscow ML supports most re- quired parts of the SML Basis Library. It supports separate compilation and the generation of stand-alone executables. The reader is assumed to be familiar with the .Net platform [2]. Contents 1 Characteristics of Moscow ML .Net 2 1.1 Compiling and linking 2 1.2 Command-line options 3 1.3 Additional primitives in the built-in units 3 1.4 The libraries 4 2 Installation 5 3 External programming interface 5 3.1 How external assemblies are found and loaded 5 3.2 How to call a .Net static method from Moscow ML .Net. 6 3.2.1 An example 7 3.2.2 Passing arguments and using results 7 3.2.3 Representation of ML Values 8 3.2.4 Notes 8 3.2.5 An experimental auto-marshalling import mechanism: clr_val 8 3.3 How to call an ML function from .Net 10 3.3.1 Example 10 3.3.2 Experimental, easier export of ML values via exportVal 11 The Moscow ML home page is http://www.dina.kvl.dk/~sestoft/mosml.html 1 1 Characteristics of Moscow ML .Net Unlike most other ports of Moscow ML, this port is not based on porting the Caml Light runtime, but is based on the creation of a new backend that generates .Net CIL code. -
Garbage Collection in Object Oriented Databases Using
Garbage Collection in Ob ject Or iente d Databas e s Us ing Transactional Cyclic Reference Counting S Ashwin Prasan Roy S Se shadr i Avi Silb erschatz S Sudarshan 1 2 Indian Institute of Technology Bell Lab orator ie s Mumbai India Murray Hill NJ sashwincswi sce du avib elllabscom fprasans e shadr isudarshagcs eiitber netin Intro duction Ob ject or iente d databas e s OODBs unlike relational Ab stract databas e s supp ort the notion of ob ject identity and ob jects can refer to other ob jects via ob ject identi ers Requir ing the programmer to wr ite co de to track Garbage collection i s imp ortant in ob ject ob jects and the ir reference s and to delete ob jects that or iente d databas e s to f ree the programmer are no longer reference d i s error prone and leads to f rom explicitly deallo cating memory In thi s common programming errors such as memory leaks pap er we pre s ent a garbage collection al garbage ob jects that are not referre d to f rom any gor ithm calle d Transactional Cyclic Refer where and havent b een delete d and dangling ref ence Counting TCRC for ob ject or iente d erence s While the s e problems are pre s ent in tradi databas e s The algor ithm i s bas e d on a var i tional programming language s the eect of a memory ant of a reference counting algor ithm pro leak i s limite d to individual runs of programs s ince p os e d for functional programming language s all garbage i s implicitly collecte d when the program The algor ithm keeps track of auxiliary refer terminate s The problem b ecome s more s