Isolating cause-effect chains from computer programs

By Andreas Zeller. SIGSOFT '02/FSE-10, 2002

657 citations recorded by the source corpus.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/7c10b26af2f9f4181a7a3949af37af6e0b1657bf

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Citations in the corpus

HDD: hierarchical delta debugging (2006, methodology): “Zeller hints at intelligent partition choices in [19].”
Locating causes of program failures (2005, background): “In earlier work [16], we have shown how to search in space-by focusing on those variables that actually cause the failure.”
BugFix: A learning-based tool to assist developers in fixing bugs (2009, background): “In the Delta Debugging framework, failure-inducing input is identified [33] that allows for the computation of cause-effect chains for failures [32] which can in turn be linked to faulty code [6].”
Empirical evaluation of the tarantula automatic fault-localization technique (2005, methodology): “Other techniques perform a binary search of the memory state using one failing test case and one passing test case to find likely faulty statements (e.g., [2] [15]).”
Understanding and detecting real-world performance bugs (2012, background): “Invariant-based bug detection and delta debugging [14, 60] are also promising.”
Designing the whyline: a debugging interface for asking questions about program behavior (2004, background): “There have been many attempts to design more useful debugging paradigms and tools, including automatic debugging [1], relative debugging [21], program slicing [20, 22], and visualizations [6], but few of these have been shown to be usable, let alone to reduce debugging time.”
An Evaluation of Similarity Coefficients for Software Fault Localization (2006, methodology): “An example of a different (black box) technique in that category is Delta Debugging [20], which compares the program states of a failing and a passing run, and actively searches for failure-inducing circumstances in the differences between these states.”
A Survey on Software Fault Localization (2016, methodology): “The theory of coun-terfactual reasoning is also found in other studies such as [137], [179], [400].”
Metallaxis‐FL: mutation‐based fault localization (2015, methodology): “This method recognizes and isolates input parts responsible for failures [6], recognizes chains of program states that lead to the failure [5] and links these chains with the faulty code.”
Fault localization with nearest neighbor queries (2003, methodology): “Zeller’s technique for isolating causes by manipulating two program runs [28] presumably works better when the runs are similar, and therefore could use our technique as a preparation step.”
On the Accuracy of Spectrum-based Fault Localization (2007, methodology): “Delta Debugging compares the program states of a failing and a passing run, and actively searches for failureinducing circumstances in the differences between these states.”
Spectrum-Based Multiple Fault Localization (2009, methodology): “SFL uses abstraction of program traces to correlate software component activity with program failures (a statistical approach) [4], [14], [20], [24], [29], [37].”
Guided GUI testing of android apps with minimal restart and approximate learning (2013, background): “It was proposed in the context of fault isolation and has been successfully applied to many problems [22, 84, 99, 123].”
SherLog: error diagnosis by connecting clues from run-time logs (2010, methodology): “Error diagnosis requiring error reproduction: Traditional error diagnosis and fault localization often relieson reproducing the error on the vendors’ site [1, 2, 7, 16, 25, 42, 44, 50 ].”
SOBER: statistical model-based bug localization (2005, methodology): “The best strategy for the optimal value of k is to choose the one under which a bug can be located with minimum code checking, i.e., kopt =argmin E[Tk], (11) k where E[Tk] is the average value of T -Score for a set of bugs under study given a .xed value of k. 5.2 Cause Transition Algorithm: CT T”
Practitioners' expectations on automated fault localization (2016, background): “, [17, 38, 58], have received hundreds of citations mostly by papers proposing more recent techniques.”
Locating faults through automated predicate switching (2006, methodology): “In a series of articles [17, 16, 15], the delta debugging algorithm has been developed to automatically simplify or isolate a failure-inducing input [17, 16], produce cause effect chains [15] and to link cause transitions [2] to the faulty code.”