Spectrum-Based Fault Localization (SBFL) is a popular technique to assist developers in pinpointing faulty elements within their code based on test outcomes and code coverage. In this paper, we examine the impact of context switching, i.e., when developers must frequently shift their attention between different code parts (such as methods and classes) while going down the SBFL ranked list to find the faulty statement. The basis of our study is the observation that it requires less effort to investigate statements that are next to each other rather than those in different methods and classes. In particular, we analyse the number of visited methods and classes, as well as the frequency of switches between them during the fault localization process. We found that, in programs from the Defects4J benchmark, developers need to explore 40 methods and 12 classes on average, before finding the faulty statement, leading to 53 method- and 40 class switches, respectively.

Finding the specific location of an error during debugging can be assisted by a variety of automated methods. One such method is Spectrum-Based Fault Localization (SBFL), which is based on test execution statistics, and is a commonly used automated method for identifying errors. The core idea of SBFL is to examine the pass/fail and coverage statistics of each test case, and then assign a level of suspicion to different parts of the program, using one of many different heuristic formulas. Another approach is to use the syntactic relationship of the program elements to trace the computation path from the observed behaviour to the actual error. For example, by using Program Slicing, a subset of the program, including the error itself, can be determined which may have contributed to the computation at the observed location in the program.Both Program Slicing and Spectrum-Based Fault Localization have a wealth of literature dedicated to them individually. However, there have been efforts to combine the two techniques in an attempt to more effectively identify faults. Previous research has demonstrated that these hybrid solutions can bring together the best aspects of the underlying methods. However, much of this research has concentrated on specific SBFL and PS algorithms, and a particular type of combination is usually proposed. Our aim is to carry out a comprehensive examination of the potential of combining these two approaches for fault localization. As we believe that this area has not yet been fully explored, we hope to develop new and innovative methods as well.

Spectrum-Based Fault Localization (SBFL) is a semi-automated debugging technique that gained popularity in the last decades due to its intuitive approach and relatively simple implementability. Despite this, the performance of practical SBFL techniques in terms of fault localization capability does not reach the threshold that would enable their acceptance by professional programmers. Almost all modern SBFL approaches are based on the code coverage-based spectrum, and on the assumption that a code element covered by failing tests should be treated as suspicious. However, it is easy to see that this is an over-approximation because many code elements may be executed that do not contribute to the test output, hence serving as noise in the process. A possible solution is to use backward dynamic program slices as program spectra computed from the output statement as the criterion, instead of the coverage. There are very few theoretical and practical results about this approach, so in this work we revisit the method and show how much more inferior coverage-based spectra are compared to slice-based spectra, both on theoretical and practical levels. We argue that code coverage-based SBFL is currently in a research pit due to this inherent approximation, and research on slice-based spectra should once more attain a much higher focus.