Handbook of Software Fault Localization

Handbook of Software Fault Localization A comprehensive analysis of fault localization techniques and strategies In Handbook of Software Fault Localization: Foundations and Advances, distinguished computer scientists Prof. W. Eric Wong and Prof. T.H. Tse deliver a robust treatment of up-to-date techniques, tools, and essential issues in software fault localization. The authors offer collective discussions of fault localization strategies with an emphasis on the most important features of each approach. The book also explores critical aspects of software fault localization, like multiple bugs, successful and failed test cases, coincidental correctness, faults introduced by missing code, the combination of several fault localization techniques, ties within fault localization rankings, concurrency bugs, spreadsheet fault localization, and theoretical studies on fault localization. Readers will benefit from the authors’ straightforward discussions of how to apply cost-effective techniques to a variety of specific environments common in the real world. They will also enjoy the in-depth explorations of recent research directions on this topic. Handbook of Software Fault Localization also includes: A thorough introduction to the concepts of software testing and debugging, their importance, typical challenges, and the consequences of poor efforts Comprehensive explorations of traditional fault localization techniques, including program logging, assertions, and breakpoints Practical discussions of slicing-based, program spectrum-based, and statistics-based techniques In-depth examinations of machine learning-, data mining-, and model-based techniques for software fault localization Perfect for researchers, professors, and students studying and working in the field, Handbook of Software Fault Localization: Foundations and Advances is also an indispensable resource for software engineers, managers, and software project decision makers responsible for schedule and budget control.

Editor Biographies xv List of Contributors xvii 1 Software Fault Localization: an Overview of Research, Techniques, and Tools 1 W. Eric Wong, Ruizhi Gao, Yihao Li, Rui Abreu, Franz Wotawa, and Dongcheng li 1.1 Introduction 1 1.2 Traditional Fault Localization Techniques 14 1.3 Advanced Fault Localization Techniques 15 1.4 Subject Programs 47 1.5 Evaluation Metrics 50 1.6 Software Fault Localization Tools 53 1.7 Critical Aspects 58 1.8 Conclusion 71 Notes 73 References 73 2 Traditional Techniques for Software Fault Localization 119 Yihao Li, Linghuan Hu, W. Eric Wong, Vidroha Debroy, and Dongcheng li 2.1 Program Logging 119 2.2 Assertions 121 2.3 Breakpoints 124 2.4 Profiling 125 2.5 Discussion 128 2.6 Conclusion 130 References 131 3 Slicing-Based Techniques for Software Fault Localization 135 W. Eric Wong, Hira Agrawal, and Xiangyu Zhang 3.1 Introduction 135 3.2 Static Slicing-Based Fault Localization 136 3.3 Dynamic Slicing-Based Fault Localization 138 3.4 Execution Slicing-Based Fault Localization 179 3.5 Discussions 193 3.6 Conclusion 194 Notes 195 References 195 4 Spectrum-Based Techniques for Software Fault Localization 201 W. Eric Wong, Hua Jie Lee, Ruizhi Gao, and Lee Naish 4.1 Introduction 201 4.2 Background and Notation 203 4.3 Insights of Some Spectra-Based Metrics 210 4.4 Equivalence Metrics 212 4.5 Selecting a Good Suspiciousness Function (Metric) 219 4.6 Using Spectrum-Based Metrics for Fault Localization 222 4.7 Empirical Evaluation Studies of SBFL Metrics 232 4.8 Conclusion 261 Notes 262 References 263 5 Statistics-Based Techniques for Software Fault Localization 271 Zhenyu Zhang and W. Eric Wong 5.1 Introduction 271 5.2 Working with Statements 274 5.3 Working with Non-statements 283 5.4 Purifying the Input 286 5.5 Reinterpreting the Output 288 Notes 292 References 293 6 Machine Learning-Based Techniques for Software Fault Localization 297 W. Eric Wong 6.1 Introduction 297 6.2 BP Neural Network-Based Fault Localization 298 6.3 RBF Neural Network-Based Fault Localization 304 6.4 C4.5 Decision Tree-Based Fault Localization 309 6.5 Applying Simulated Annealing with Statement Pruning for an SBFL Formula 314 6.6 Conclusion 317 Notes 317 References 317 7 Data Mining-Based Techniques for Software Fault Localization 321 Peggy Cellier, Mireille Ducassé, Sébastien Ferré, Olivier Ridoux, and W. Eric Wong 7.1 Introduction 321 7.2 Formal Concept Analysis and Association Rules 324 7.3 Data Mining for Fault Localization 329 7.4 The Failure Lattice for Multiple Faults 336 7.5 Discussion 342 7.6 Fault Localization Using N-gram Analysis 346 7.7 Fault Localization for GUI Software Using N-gram Analysis 353 7.8 Conclusion 360 Notes 361 References 361 8 Information Retrieval-Based Techniques for Software Fault Localization 365 Xin Xia and David Lo 8.1 Introduction 365 8.2 General IR-Based Fault Localization Process 368 8.3 Fundamental Information Retrieval Techniques for Software Fault Localization 369 8.4 Evaluation Metrics 372 8.5 Techniques for Different Scenarios 374 8.6 Empirical Studies 380 8.7 Miscellaneous 383 8.8 Conclusion 385 Notes 385 References 386 9 Model-Based Techniques for Software Fault Localization 393 Birgit Hofer, Franz Wotawa, Wolfgang Mayer, and Markus Stumptner 9.1 Introduction 393 9.2 Basic Definitions and Algorithms 395 9.3 Modeling for MBD 404 9.4 Application Areas 417 9.5 Hybrid Approaches 418 9.6 Conclusions 419 Notes 420 References 420 10 Software Fault Localization in Spreadsheets 425 Birgit Hofer and Franz Wotawa 10.1 Motivation 425 10.2 Definition of the Spreadsheet Language 427 10.3 Cones 430 10.4 Spectrum-Based Fault Localization 431 10.5 Model-Based Spreadsheet Debugging 435 10.6 Repair Approaches 440 10.7 Checking Approaches 443 10.8 Testing 445 10.9 Conclusion 446 Notes 446 References 447 11 Theoretical Aspects of Software Fault Localization 451 Xiaoyuan Xie and W. Eric Wong 11.1 Introduction 451 11.2 A Model-Based Hybrid Analysis 452 11.3 A Set-Based Pure Theoretical Framework 455 11.4 A Generalized Study 462 11.5 About the Assumptions 465 Notes 469 References 470 12 Software Fault Localization for Programs with Multiple Bugs 473 Ruizhi Gao, W. Eric Wong, and Rui Abreu 12.1 Introduction 473 12.2 One-Bug-at-a-Time 474 12.3 Two Techniques Proposed by Jones et al. 475 12.4 Localization of Multiple Bugs Using Algorithms from Integer Linear Programming 481 12.5 MSeer: an Advanced Fault Localization Technique for Locating Multiple Bugs in Parallel 483 12.6 Spectrum-Based Reasoning for Fault Localization 514 12.7 Other Studies 518 12.8 Conclusion 520 Notes 521 References 522 13 Emerging Aspects of Software Fault Localization 529 T.H. Tse, David Lo, Alex Gorce, Michael Perscheid, Robert Hirschfeld, and W. Eric Wong 13.1 Introduction 529 13.2 Application of the Scientific Method to Fault Localization 530 13.3 Fault Localization in the Absence of Test Oracles by Semi-proving of Metamorphic Relations 538 13.4 Automated Prediction of Fault Localization Effectiveness 560 13.5 Integrating Fault Localization into Automated Test Generation Tools 565 Notes 569 References 569 Index 581