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The New Way C++ Does Computational Finance
The goal of Financial Instrument Pricing Using C++, Second Edition, is to apply modern C++ language and design features to the creation of efficient and robust applications. This book not only documents these developments, but also highlights the advantages for the quant developer:
- Comprehensive and detailed exposition of improved and new C++ syntax; extensive examples and application code
- Using C++11 libraries for random number generation, concurrency, STL and more
- Overhaul of object-oriented design patterns and porting them to a multiparadigm programming model
- IEEE 754 and multiprecision; interfacing C++ with .NET and C#
- Modern PDE/FDM: ADE; Soviet Splitting and Method of Lines, (Parallel) Monte Carlo and lattice methods
- Support for numerical libraries
- Machine-readable code
Daniel Duffy used a spiral model approach in writing each chapter of this book: analyse a little, design a little, and code a little. Each cycle ends with a working prototype in C++ and shows how a given algorithm or numerical method works. Additionally, each chapter contains non-trivial exercises and projects that discuss improvements and extensions to the material. This book is for designers and application developers in computational finance, and assumes the reader has some fundamental experience of C++ and derivatives pricing.
The New Way C++ Does Computational Finance
The goal of Financial Instrument Pricing Using C++, Second Edition, is to apply modern C++ language and design features to the creation of efficient and robust applications. This book not only documents these developments, but also highlights the advantages for the quant developer:
- Comprehensive and detailed exposition of improved and new C++ syntax; extensive examples and application code
- Using C++11 libraries for random number generation, concurrency, STL and more
- Overhaul of object-oriented design patterns and porting them to a multiparadigm programming model
- IEEE 754 and multiprecision; interfacing C++ with .NET and C#
- Modern PDE/FDM: ADE; Soviet Splitting and Method of Lines, (Parallel) Monte Carlo and lattice methods
- Support for numerical libraries
- Machine-readable code
Daniel Duffy used a spiral model approach in writing each chapter of this book: analyse a little, design a little, and code a little. Each cycle ends with a working prototype in C++ and shows how a given algorithm or numerical method works. Additionally, each chapter contains non-trivial exercises and projects that discuss improvements and extensions to the material. This book is for designers and application developers in computational finance, and assumes the reader has some fundamental experience of C++ and derivatives pricing.
DANIEL J. DUFFY started the company Datasim in 1987 to promote C++ as a new object-oriented language for developing applications in the roles of developer, architect and requirements analyst to help clients design and analyse software systems for Computer Aided Design (CAD), process control and hardware- software systems, logistics, holography (optical technology) and computational finance. He used a combination of top-down functional decomposition and bottom-up object-oriented programming techniques to create stable and extendible applications. Prior to Datasim, he worked on engineering and financial applications in oil and gas and semiconductor industries using a range of numerical methods (for example, the finite element method [FEM]) on mainframe and mini-computers.
Duffy has BA (Mod), MSc and PhD degrees in pure, numerical and applied mathematics and has been active in promoting partial differential equation (PDE) and finite difference methods (FDM) to applications in computational finance. He was responsible for the introduction of the Fractional Step ("Soviet Splitting") method and the Alternating Direction Explicit (ADE) method in computational finance.
He is the originator of two very popular and leading C++ online courses (both C++98 and C++11/14/17) on [...] in cooperation with Quantnet LLC and Baruch College (CUNY), NYC. He also trains quants, developers and designers around the world. Duffy can be contacted at [...] In his spare time, he tries to keep in shape by workouts in the dojo.
CHAPTER 1 A Tour of C++ and Environs 1
1.1 Introduction and Objectives 1
1.2 What is C++? 1
1.3 C++ as a Multiparadigm Programming Language 2
1.4 The Structure and Contents of this Book: Overview 4
1.5 A Tour of C++11: Black-Scholes and Environs 6
1.6 Parallel Programming in C++ and Parallel C++ Libraries 12
1.7 Writing C++ Applications; Where and How to Start? 14
1.8 For whom is this Book Intended? 16
1.9 Next-Generation Design and Design Patterns in C++ 16
1.10 Some Useful Guidelines and Developer Folklore 17
1.11 About the Author 18
1.12 The Source Code and Getting the Source Code 19
CHAPTER 2 New and Improved C++ Fundamentals 21
2.1 Introduction and Objectives 21
2.2 The C++ Smart Pointers 21
2.3 Using Smart Pointers in Code 23
2.4 Extended Examples of Smart Pointers Usage 30
2.5 Move Semantics and Rvalue References 34
2.6 Other Bits and Pieces: Usability Enhancements 39
2.7 Summary and Conclusions 52
2.8 Exercises and Projects 52
CHAPTER 3 Modelling Functions in C++ 59
3.1 Introduction and Objectives 59
3.2 Analysing and Classifying Functions 60
3.3 New Functionality in C++: std::function<> 64
3.4 New Functionality in C++: Lambda Functions and Lambda Expressions 65
3.5 Callable Objects 69
3.6 Function Adapters and Binders 70
3.7 Application Areas 75
3.8 An Example: Strategy Pattern New Style 75
3.9 Migrating from Traditional Object-Oriented Solutions: Numerical Quadrature 78
3.10 Summary and Conclusions 81
3.11 Exercises and Projects 82
CHAPTER 4 Advanced C++ Template Programming 89
4.1 Introduction and Objectives 89
4.2 Preliminaries 91
4.3 decltype Specifier 94
4.4 Life Before and After decltype 101
4.5 std::result_of and SFINAE 106
4.6 std::enable_if 108
4.7 Boost enable_if 112
4.8 std::decay()Trait 114
4.9 A Small Application: Quantities and Units 115
4.10 Conclusions and Summary 118
4.11 Exercises and Projects 118
CHAPTER 5 Tuples in C++ and their Applications 123
5.1 Introduction and Objectives 123
5.2 An std:pair Refresher and New Extensions 123
5.3 Mathematical and Computer Science Background 128
5.4 Tuple Fundamentals and Simple Examples 130
5.5 Advanced Tuples 130
5.6 Using Tuples in Code 133
5.7 Other Related Libraries 138
5.8 Tuples and Run-Time Efficiency 140
5.9 Advantages and Applications of Tuples 142
5.10 Summary and Conclusions 143
5.11 Exercises and Projects 143
CHAPTER 6 Type Traits, Advanced Lambdas and Multiparadigm Design in C++ 147
6.1 Introduction and Objectives 147
6.2 Some Building Blocks 149
6.3 C++ Type Traits 150
6.4 Initial Examples of Type Traits 158
6.5 Generic Lambdas 161
6.6 How Useful will Generic Lambda Functions be in the Future? 164
6.7 Generalised Lambda Capture 171
6.7.1 Living Without Generalised Lambda Capture 173
6.8 Application to Stochastic Differential Equations 174
6.9 Emerging Multiparadigm Design Patterns: Summary 178
6.10 Summary and Conclusions 179
6.11 Exercises and Projects 179
CHAPTER 7 Multiparadigm Design in C++ 185
7.1 Introduction and Objectives 185
7.2 Modelling and Design 185
7.3 Low-Level C++ Design of Classes 190
7.4 Shades of Polymorphism 199
7.5 Is there More to Life than Inheritance? 206
7.6 An Introduction to Object-Oriented Software Metrics 207
7.7 Summary and Conclusions 210
7.8 Exercises and Projects 210
CHAPTER 8 C++ Numerics, IEEE 754 and Boost C++ Multiprecision 215
8.1 Introduction and Objectives 215
8.2 Floating-Point Decomposition Functions in C++ 219
8.3 A Tour of std::numeric_limits 221
8.4 An Introduction to Error Analysis 223
8.5 Example: Numerical Quadrature 224
8.6 Other Useful Mathematical Functions in C++ 228
8.7 Creating C++ Libraries 231
8.8 Summary and Conclusions 239
8.9 Exercises and Projects 239
CHAPTER 9 An Introduction to Unified Software Design 245
9.1 Introduction and Objectives 245
9.1.1 Future Predictions and Expectations 246
9.2 Background 247
9.3 System Scoping and Initial Decomposition 251
9.4 Checklist and Looking Back 259
9.5 Variants of the Software Process: Policy-Based Design 260
9.6 Using Policy-Based Design for the DVM Problem 268
9.7 Advantages of Uniform Design Approach 273
9.8 Summary and Conclusions 274
9.9 Exercises and Projects 275
CHAPTER 10 New Data Types, Containers and Algorithms in C++ and Boost C++ Libraries 283
10.1 Introduction and Objectives 283
10.2 Overview of New Features 283
10.3 C++ std::bitset and Boost Dynamic Bitset Library 284
10.4 Chrono Library 288
10.5 Boost Date and Time 301
10.6 Forwards Lists and Compile-Time Arrays 306
10.7 Applications of [...] 311
10.8 Boost uBLAS (Matrix Library) 313
10.9 Vectors 316
10.10 Matrices 318
10.11 Applying uBLAS: Solving Linear Systems of Equations 322
10.12 Summary and Conclusions 330
10.13 Exercises and Projects 331
CHAPTER 11 Lattice Models Fundamental Data Structures and Algorithms 333
11.1 Introduction and Objectives 333
11.2 Background and Current Approaches to Lattice Modelling 334
11.3 New Requirements and Use Cases 335
11.4 A New Design Approach: A Layered Approach 335
11.5 Initial '101' Examples of Option Pricing 347
11.6 Advantages of Software Layering 349
11.7 Improving Efficiency and Reliability 352
11.8 Merging Lattices 355
11.9 Summary and Conclusions 357
11.10 Exercises and Projects 357
CHAPTER 12 Lattice Models Applications to Computational Finance 367
12.1 Introduction and Objectives 367
12.2 Stress Testing the Lattice Data Structures 368
12.3 Option Pricing Using Bernoulli Paths 372
12.4 Binomial Model for Assets with Dividends 374
12.5 Computing Option Sensitivities 377
12.6 (Quick) Numerical Analysis of the Binomial Method 379
12.7 Richardson Extrapolation with Binomial Lattices 382
12.8 Two-Dimensional Binomial Method 382
12.9 Trinomial Model of the Asset Price 384
12.10 Stability and Convergence of the Trinomial Method 385
12.11 Explicit Finite Difference Method 386
12.12 Summary and Conclusions 389
12.13 Exercises and Projects 389
CHAPTER 13 Numerical Linear Algebra: Tridiagonal Systems and Applications 395
13.1 Introduction and Objectives 395
13.2 Solving Tridiagonal Matrix Systems 395
13.3 The Crank-Nicolson and Theta Methods 406
13.4 The ADE Method for the Impatient 411
13.5 Cubic Spline Interpolation 415
13.6 Some Handy Utilities 427
13.7 Summary and Conclusions 428
13.8 Exercises and Projects 429
CHAPTER 14 Data Visualisation in Excel 433
14.1 Introduction and Objectives 433
14.2 The Structure of Excel-Related Objects 433
14.3 Sanity Check: Is the Excel Infrastructure Up and Running? 435
14.4 ExcelDriver and Matrices 437
14.5 ExcelDriver and Vectors 444
14.6 Path Generation for Stochastic Differential Equations 448
14.7 Summary and Conclusions 459
14.8 Exercises and Projects 459
14.9 Appendix: COM Architecture Overview 463
14.10 An Example 468
14.11 Virtual Function Tables 471
14.12 Differences between COM and Object-Oriented Paradigm 473
14.13 Initialising the COM Library 474
CHAPTER 15 Univariate Statistical Distributions 475
15.1 Introduction, Goals and Objectives 475
15.2 The Error Function and Its Universality 475
15.3 One-Factor Plain Options 478
15.4 Option Sensitivities and Surfaces 488
15.5 Automating Data Generation 491
15.6 Introduction to Statistical Distributions and Functions 499
15.7 Advanced Distributions 504
15.8 Summary and Conclusions 511
15.9 Exercises and Projects 511
CHAPTER 16 Bivariate Statistical Distributions and Two-Asset Option Pricing 515
16.1 Introduction and Objectives 515
16.2 Computing Integrals Using PDEs 516
16.3 The Drezner Algorithm 521
16.4 The Genz Algorithm and the West/Quantlib Implementations 521
16.5 Abramowitz and Stegun Approximation 525
16.6 Performance Testing 528
16.7 Gauss-Legendre Integration 529
16.8 Applications to Two-Asset Pricing 531
16.9 Trivariate Normal Distribution 536
16.10 Chooser Options 543
16.11 Conclusions and Summary 545
16.12 Exercises and Projects 546
CHAPTER 17 STL Algorithms in Detail 551
17.1 Introduction and Objectives 551
17.2 Binders and std::bind 554
17.3 Non-modifying Algorithms 557
17.4 Modifying Algorithms 567
17.5 Compile-Time Arrays 575
17.6 Summary and Conclusions 576
17.7 Exercises and Projects 576
17.8 Appendix: Review of STL Containers and Complexity Analysis 583
CHAPTER 18 STL Algorithms Part II 589
18.1 Introduction and Objectives 589
18.2 Mutating Algorithms 589
18.3 Numeric Algorithms 597
18.4 Sorting Algorithms 601
18.5 Sorted-Range Algorithms 604
18.5.5 Merging 608
18.6 Auxiliary Iterator Functions 609
18.7 Needle in a Haystack: Finding the Right STL Algorithm 612
18.8 Applications to...
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Betriebswirtschaft |
| Genre: | Importe, Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Inhalt: | 1168 S. |
| ISBN-13: | 9780470971192 |
| ISBN-10: | 0470971193 |
| Sprache: | Englisch |
| Herstellernummer: | 14597119000 |
| Einband: | Gebunden |
| Autor: | Duffy, Daniel J |
| Auflage: | 2nd edition |
| Hersteller: |
Wiley
John Wiley & Sons |
| Verantwortliche Person für die EU: | Wiley-VCH GmbH, Boschstr. 12, D-69469 Weinheim, product-safety@wiley.com |
| Maße: | 251 x 174 x 63 mm |
| Von/Mit: | Daniel J Duffy |
| Erscheinungsdatum: | 09.10.2018 |
| Gewicht: | 1,889 kg |
DANIEL J. DUFFY started the company Datasim in 1987 to promote C++ as a new object-oriented language for developing applications in the roles of developer, architect and requirements analyst to help clients design and analyse software systems for Computer Aided Design (CAD), process control and hardware- software systems, logistics, holography (optical technology) and computational finance. He used a combination of top-down functional decomposition and bottom-up object-oriented programming techniques to create stable and extendible applications. Prior to Datasim, he worked on engineering and financial applications in oil and gas and semiconductor industries using a range of numerical methods (for example, the finite element method [FEM]) on mainframe and mini-computers.
Duffy has BA (Mod), MSc and PhD degrees in pure, numerical and applied mathematics and has been active in promoting partial differential equation (PDE) and finite difference methods (FDM) to applications in computational finance. He was responsible for the introduction of the Fractional Step ("Soviet Splitting") method and the Alternating Direction Explicit (ADE) method in computational finance.
He is the originator of two very popular and leading C++ online courses (both C++98 and C++11/14/17) on [...] in cooperation with Quantnet LLC and Baruch College (CUNY), NYC. He also trains quants, developers and designers around the world. Duffy can be contacted at [...] In his spare time, he tries to keep in shape by workouts in the dojo.
CHAPTER 1 A Tour of C++ and Environs 1
1.1 Introduction and Objectives 1
1.2 What is C++? 1
1.3 C++ as a Multiparadigm Programming Language 2
1.4 The Structure and Contents of this Book: Overview 4
1.5 A Tour of C++11: Black-Scholes and Environs 6
1.6 Parallel Programming in C++ and Parallel C++ Libraries 12
1.7 Writing C++ Applications; Where and How to Start? 14
1.8 For whom is this Book Intended? 16
1.9 Next-Generation Design and Design Patterns in C++ 16
1.10 Some Useful Guidelines and Developer Folklore 17
1.11 About the Author 18
1.12 The Source Code and Getting the Source Code 19
CHAPTER 2 New and Improved C++ Fundamentals 21
2.1 Introduction and Objectives 21
2.2 The C++ Smart Pointers 21
2.3 Using Smart Pointers in Code 23
2.4 Extended Examples of Smart Pointers Usage 30
2.5 Move Semantics and Rvalue References 34
2.6 Other Bits and Pieces: Usability Enhancements 39
2.7 Summary and Conclusions 52
2.8 Exercises and Projects 52
CHAPTER 3 Modelling Functions in C++ 59
3.1 Introduction and Objectives 59
3.2 Analysing and Classifying Functions 60
3.3 New Functionality in C++: std::function<> 64
3.4 New Functionality in C++: Lambda Functions and Lambda Expressions 65
3.5 Callable Objects 69
3.6 Function Adapters and Binders 70
3.7 Application Areas 75
3.8 An Example: Strategy Pattern New Style 75
3.9 Migrating from Traditional Object-Oriented Solutions: Numerical Quadrature 78
3.10 Summary and Conclusions 81
3.11 Exercises and Projects 82
CHAPTER 4 Advanced C++ Template Programming 89
4.1 Introduction and Objectives 89
4.2 Preliminaries 91
4.3 decltype Specifier 94
4.4 Life Before and After decltype 101
4.5 std::result_of and SFINAE 106
4.6 std::enable_if 108
4.7 Boost enable_if 112
4.8 std::decay()Trait 114
4.9 A Small Application: Quantities and Units 115
4.10 Conclusions and Summary 118
4.11 Exercises and Projects 118
CHAPTER 5 Tuples in C++ and their Applications 123
5.1 Introduction and Objectives 123
5.2 An std:pair Refresher and New Extensions 123
5.3 Mathematical and Computer Science Background 128
5.4 Tuple Fundamentals and Simple Examples 130
5.5 Advanced Tuples 130
5.6 Using Tuples in Code 133
5.7 Other Related Libraries 138
5.8 Tuples and Run-Time Efficiency 140
5.9 Advantages and Applications of Tuples 142
5.10 Summary and Conclusions 143
5.11 Exercises and Projects 143
CHAPTER 6 Type Traits, Advanced Lambdas and Multiparadigm Design in C++ 147
6.1 Introduction and Objectives 147
6.2 Some Building Blocks 149
6.3 C++ Type Traits 150
6.4 Initial Examples of Type Traits 158
6.5 Generic Lambdas 161
6.6 How Useful will Generic Lambda Functions be in the Future? 164
6.7 Generalised Lambda Capture 171
6.7.1 Living Without Generalised Lambda Capture 173
6.8 Application to Stochastic Differential Equations 174
6.9 Emerging Multiparadigm Design Patterns: Summary 178
6.10 Summary and Conclusions 179
6.11 Exercises and Projects 179
CHAPTER 7 Multiparadigm Design in C++ 185
7.1 Introduction and Objectives 185
7.2 Modelling and Design 185
7.3 Low-Level C++ Design of Classes 190
7.4 Shades of Polymorphism 199
7.5 Is there More to Life than Inheritance? 206
7.6 An Introduction to Object-Oriented Software Metrics 207
7.7 Summary and Conclusions 210
7.8 Exercises and Projects 210
CHAPTER 8 C++ Numerics, IEEE 754 and Boost C++ Multiprecision 215
8.1 Introduction and Objectives 215
8.2 Floating-Point Decomposition Functions in C++ 219
8.3 A Tour of std::numeric_limits 221
8.4 An Introduction to Error Analysis 223
8.5 Example: Numerical Quadrature 224
8.6 Other Useful Mathematical Functions in C++ 228
8.7 Creating C++ Libraries 231
8.8 Summary and Conclusions 239
8.9 Exercises and Projects 239
CHAPTER 9 An Introduction to Unified Software Design 245
9.1 Introduction and Objectives 245
9.1.1 Future Predictions and Expectations 246
9.2 Background 247
9.3 System Scoping and Initial Decomposition 251
9.4 Checklist and Looking Back 259
9.5 Variants of the Software Process: Policy-Based Design 260
9.6 Using Policy-Based Design for the DVM Problem 268
9.7 Advantages of Uniform Design Approach 273
9.8 Summary and Conclusions 274
9.9 Exercises and Projects 275
CHAPTER 10 New Data Types, Containers and Algorithms in C++ and Boost C++ Libraries 283
10.1 Introduction and Objectives 283
10.2 Overview of New Features 283
10.3 C++ std::bitset and Boost Dynamic Bitset Library 284
10.4 Chrono Library 288
10.5 Boost Date and Time 301
10.6 Forwards Lists and Compile-Time Arrays 306
10.7 Applications of [...] 311
10.8 Boost uBLAS (Matrix Library) 313
10.9 Vectors 316
10.10 Matrices 318
10.11 Applying uBLAS: Solving Linear Systems of Equations 322
10.12 Summary and Conclusions 330
10.13 Exercises and Projects 331
CHAPTER 11 Lattice Models Fundamental Data Structures and Algorithms 333
11.1 Introduction and Objectives 333
11.2 Background and Current Approaches to Lattice Modelling 334
11.3 New Requirements and Use Cases 335
11.4 A New Design Approach: A Layered Approach 335
11.5 Initial '101' Examples of Option Pricing 347
11.6 Advantages of Software Layering 349
11.7 Improving Efficiency and Reliability 352
11.8 Merging Lattices 355
11.9 Summary and Conclusions 357
11.10 Exercises and Projects 357
CHAPTER 12 Lattice Models Applications to Computational Finance 367
12.1 Introduction and Objectives 367
12.2 Stress Testing the Lattice Data Structures 368
12.3 Option Pricing Using Bernoulli Paths 372
12.4 Binomial Model for Assets with Dividends 374
12.5 Computing Option Sensitivities 377
12.6 (Quick) Numerical Analysis of the Binomial Method 379
12.7 Richardson Extrapolation with Binomial Lattices 382
12.8 Two-Dimensional Binomial Method 382
12.9 Trinomial Model of the Asset Price 384
12.10 Stability and Convergence of the Trinomial Method 385
12.11 Explicit Finite Difference Method 386
12.12 Summary and Conclusions 389
12.13 Exercises and Projects 389
CHAPTER 13 Numerical Linear Algebra: Tridiagonal Systems and Applications 395
13.1 Introduction and Objectives 395
13.2 Solving Tridiagonal Matrix Systems 395
13.3 The Crank-Nicolson and Theta Methods 406
13.4 The ADE Method for the Impatient 411
13.5 Cubic Spline Interpolation 415
13.6 Some Handy Utilities 427
13.7 Summary and Conclusions 428
13.8 Exercises and Projects 429
CHAPTER 14 Data Visualisation in Excel 433
14.1 Introduction and Objectives 433
14.2 The Structure of Excel-Related Objects 433
14.3 Sanity Check: Is the Excel Infrastructure Up and Running? 435
14.4 ExcelDriver and Matrices 437
14.5 ExcelDriver and Vectors 444
14.6 Path Generation for Stochastic Differential Equations 448
14.7 Summary and Conclusions 459
14.8 Exercises and Projects 459
14.9 Appendix: COM Architecture Overview 463
14.10 An Example 468
14.11 Virtual Function Tables 471
14.12 Differences between COM and Object-Oriented Paradigm 473
14.13 Initialising the COM Library 474
CHAPTER 15 Univariate Statistical Distributions 475
15.1 Introduction, Goals and Objectives 475
15.2 The Error Function and Its Universality 475
15.3 One-Factor Plain Options 478
15.4 Option Sensitivities and Surfaces 488
15.5 Automating Data Generation 491
15.6 Introduction to Statistical Distributions and Functions 499
15.7 Advanced Distributions 504
15.8 Summary and Conclusions 511
15.9 Exercises and Projects 511
CHAPTER 16 Bivariate Statistical Distributions and Two-Asset Option Pricing 515
16.1 Introduction and Objectives 515
16.2 Computing Integrals Using PDEs 516
16.3 The Drezner Algorithm 521
16.4 The Genz Algorithm and the West/Quantlib Implementations 521
16.5 Abramowitz and Stegun Approximation 525
16.6 Performance Testing 528
16.7 Gauss-Legendre Integration 529
16.8 Applications to Two-Asset Pricing 531
16.9 Trivariate Normal Distribution 536
16.10 Chooser Options 543
16.11 Conclusions and Summary 545
16.12 Exercises and Projects 546
CHAPTER 17 STL Algorithms in Detail 551
17.1 Introduction and Objectives 551
17.2 Binders and std::bind 554
17.3 Non-modifying Algorithms 557
17.4 Modifying Algorithms 567
17.5 Compile-Time Arrays 575
17.6 Summary and Conclusions 576
17.7 Exercises and Projects 576
17.8 Appendix: Review of STL Containers and Complexity Analysis 583
CHAPTER 18 STL Algorithms Part II 589
18.1 Introduction and Objectives 589
18.2 Mutating Algorithms 589
18.3 Numeric Algorithms 597
18.4 Sorting Algorithms 601
18.5 Sorted-Range Algorithms 604
18.5.5 Merging 608
18.6 Auxiliary Iterator Functions 609
18.7 Needle in a Haystack: Finding the Right STL Algorithm 612
18.8 Applications to...
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Betriebswirtschaft |
| Genre: | Importe, Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Inhalt: | 1168 S. |
| ISBN-13: | 9780470971192 |
| ISBN-10: | 0470971193 |
| Sprache: | Englisch |
| Herstellernummer: | 14597119000 |
| Einband: | Gebunden |
| Autor: | Duffy, Daniel J |
| Auflage: | 2nd edition |
| Hersteller: |
Wiley
John Wiley & Sons |
| Verantwortliche Person für die EU: | Wiley-VCH GmbH, Boschstr. 12, D-69469 Weinheim, product-safety@wiley.com |
| Maße: | 251 x 174 x 63 mm |
| Von/Mit: | Daniel J Duffy |
| Erscheinungsdatum: | 09.10.2018 |
| Gewicht: | 1,889 kg |
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