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Languages Symposium\",\"VSN\":\"DLS\",\"V\":47,\"I\":2,\"FP\":51,\"LP\":60,\"DOI\":\"10.1145/2047849.2047856\",\"CC\":{\"1510987657\":[\"AspectU [28] introduces an aspect entity at the use-case requirement level similar to AspectJ at implementation level.\"],\"1563647787\":[\"Moreover, dependencies between usecase implementations are not obvious, leading to missing or erroneous annotations [18].\"],\"1574060188\":[\"Developers have to follow the infection chain backwards from the observable failure to the past defect, which is largely a search problem in time and space of programs [35].\"],\"1984129195\":[\"Contemporary object-oriented programming languages are very limited when it comes to reflecting the users’ perspectives in the actual source code of the system [34].\",\"Further research has refined this concept by defining metrics [23, 34] and heuristics [14] or interactively analyzing features at the sub-method level [10] to quantify features and source code more precisely.\"],\"1998033538\":[\"Further research has refined this concept by defining metrics [23, 34] and heuristics [14] or interactively analyzing features at the sub-method level [10] to quantify features and source code more precisely.\"],\"2001033929\":[\"It is hardly possible to determine solely from source code how objects contribute to the run-time behavior of the system, which is to a large degree due to language features such as late binding or polymorphism [8].\"],\"2002454301\":[\"Feature Localization Feature engineering [30] introduces features as the natural organization of a system’s functionality from the users’ point of view.\"],\"2041853131\":[\"Besides dynamic analysis, there are alternative approaches based on information retrieval techniques [24, 36].\"],\"2072661102\":[\"The TraceAnalyzer [12] is similar to our approach since it uses run-time information of scenarios to recover traceability links.\"],\"2077997855\":[\"Based on a few links created manually, LeanArt [16] recovers traceability links between use-case diagrams and types and variables.\"],\"2101730275\":[\"Feature-oriented programming (FOP) [4] and context-oriented programming (COP) [19] are paradigms that capture increments in program functionality.\"],\"2104354357\":[\"Similar concepts [6] focus on test coverage [3] and recovering architectural entities [5].\"],\"2111014165\":[\"A further approach uses static and dynamic concepts with several tools such as parser and processor emulation [1] solving difficulties of collecting dynamic data and combining features and micro architecture together.\"],\"2113476536\":[\"Further research has refined this concept by defining metrics [23, 34] and heuristics [14] or interactively analyzing features at the sub-method level [10] to quantify features and source code more precisely.\"],\"2113647890\":[\"Due to the crosscutting characteristics of use-cases in design and implementation activities [21, 22], their realizing objects end up being scattered over and tangled with the rest of the system.\",\"Aspects Use-case modularity [21] argues that aspect-oriented programming can provide the missing link between use-cases and implementation.\"],\"2121234902\":[\"Developers frequently have to associate requirements expressed by a customer or user with the responsible locations in a system’s implementation [32].\",\"After test execution, the collected traces are used to map source code entities to use-case objects in a so-called use-case method-map (adapted from feature analysis [17, 32])—use-case implementations are said to refer to a method when that method has been executed at least once in a specific use-case trace.\",\"The Software Reconnaissance technique [32, 33] was the first to use dynamic analysis to locate features.\"],\"2125682153\":[\"Another approach extends the idea with static analysis of dependency graphs and formal concept analysis [13].\"],\"2128581098\":[\"There are also some approaches based on information retrieval [2, 26].\"],\"2129559874\":[\"Requirements Traceability Requirements traceability refers to the ability to follow the life of a requirement, both forwards and backwards [15].\",\"This reuse of requirements documents can lead to a significant decrease in time, effort, and costs of software development [15].\"],\"2133815117\":[\"Similar concepts [6] focus on test coverage [3] and recovering architectural entities [5].\"],\"2148357053\":[\"This initial task consists of studying and analyzing an often only partially understood system to store the mappings of system functionalities to source code [25], which is likely to be nontrivial and timeconsuming.\"],\"2150275961\":[\"Feature-oriented programming (FOP) [4] and context-oriented programming (COP) [19] are paradigms that capture increments in program functionality.\"],\"2151318864\":[\"The Software Reconnaissance technique [32, 33] was the first to use dynamic analysis to locate features.\"],\"2163960678\":[\"There are also some approaches based on information retrieval [2, 26].\"],\"2169326591\":[\"Similar concepts [6] focus on test coverage [3] and recovering architectural entities [5].\"],\"2169540278\":[\"Further research has refined this concept by defining metrics [23, 34] and heuristics [14] or interactively analyzing features at the sub-method level [10] to quantify features and source code more precisely.\"],\"2539187648\":[\"Besides dynamic analysis, there are alternative approaches based on information retrieval techniques [24, 36].\",\"For instance, latent semantic indexing will be used to locate similar source code identifiers in different documents [24].\"],\"2803343605\":[\"After test execution, the collected traces are used to map source code entities to use-case objects in a so-called use-case method-map (adapted from feature analysis [17, 32])—use-case implementations are said to refer to a method when that method has been executed at least once in a specific use-case 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Symposium on Applied Computing\",\"VSN\":\"SAC\",\"FP\":2169,\"LP\":2175,\"DOI\":\"10.1145/1774088.1774546\",\"CC\":{\"61997153\":[\"PyDCL is our implementation of DCL in and for the Python programming language [28].\"],\"166270156\":[\"iContract by Kramer [20] uses structured comments (like [25, 31]) for specifying contracts and provides a preprocessor that instruments the original source code with contract checks.\"],\"956539890\":[\"Some AOP languages, such as CaesarJ [3] and AspectS [12] overcome this limitation and provide dynamic aspect weaving, though they lack in supporting annotationbased pointcuts.\"],\"1491095550\":[\"Some AOP languages, such as CaesarJ [3] and AspectS [12] overcome this limitation and provide dynamic aspect weaving, though they lack in supporting annotationbased pointcuts.\"],\"1555946950\":[\"The ideas of DBC [21] and their first incarnation in the Eiffel programming language [22] have contributed to software engineering for almost two decades now [27].\"],\"1556513858\":[\"So far, COP has been implemented for several languages such as Lisp [5], Smalltalk [13], Python [29], 1 employerLayer = layer(\\\"Employer\\\")\"],\"1574060188\":[\"In future work, we are interested in exploring inductive debugging concepts in combination with automatically generated contracts [32].\",\"Future work will be concerned with inductive debugging techniques [32].\"],\"1584704555\":[\"In Duncan and Hölzle’s Handshake [6] contracts are read from a separate file with a Java-like syntax.\"],\"1992443356\":[\"So far, COP has been implemented for several languages such as Lisp [5], Smalltalk [13], Python [29], 1 employerLayer = layer(\\\"Employer\\\")\"],\"2052363833\":[\"With Design by Contract (DBC [16, 21]) programmers can separate the specification of pre- and postconditions and invariants from their application code to improve code comprehensibility and quality.\",\"The ideas of DBC [21] and their first incarnation in the Eiffel programming language [22] have contributed to software engineering for almost two decades now [27].\",\"Besides the original DBC implementation in Eiffel [21], we can find DBC extensions to several other programming languages.\"],\"2087175184\":[\"So far, COP has been implemented for several languages such as Lisp [5], Smalltalk [13], Python [29], 1 employerLayer = layer(\\\"Employer\\\")\",\"PyContext [29] is another COP library in Python.\"],\"2090496119\":[\"With Design by Contract (DBC [16, 21]) programmers can separate the specification of pre- and postconditions and invariants from their application code to improve code comprehensibility and quality.\"],\"2111706174\":[\"The roots of DBC can be traced back to the work of Floyd [8] and Hoare [15].\"],\"2118399307\":[\"The ideas of DBC [21] and their first incarnation in the Eiffel programming language [22] have contributed to software engineering for almost two decades now [27].\"],\"2125682153\":[\"For instance, grouping contracts related to specific requirements is almost impossible since the implementation of most of the requirements are spread over several classes and so cannot be related to a single one [7, 9].\"],\"2143238865\":[\"Aspect-oriented programming [19] (AOP) provides language abstractions to encapsulate crosscutting concerns, thus it is conceptually related to COP.\"],\"2144114063\":[\"An overview of most of them is provided in [1].\",\"It supports the layer-in-class approach [1] and with that allows developers to define their partial methods within the scope of the actual classes these methods are contributing to.\"],\"2146987093\":[\"Guerreiro [10] implements contracts for C++.\"],\"2150275961\":[\"In this paper, we present dynamic contract layers (DCL), which augment the flexibility of state-of-theart DBC approaches by combining them with ideas from context-oriented programming (COP [14]).\",\"It turns out that context-oriented programming [14] (COP) is an ideal base for our extension to DBC.\",\"A broader introduction to COP is provided in [14].\"],\"2161825580\":[\"During the evaluation of an assertion all subsequent method calls must be executed without any evaluation [23].\"],\"2164859807\":[\"Today, there are at least three freely available implementations of DBC in Python: Design by Contract by Plösch [25], ContractPy [31], and PyDBC [4].\",\"iContract by Kramer [20] uses structured comments (like [25, 31]) for specifying contracts and provides a preprocessor that instruments the original source code with contract checks.\"],\"2165121897\":[\"Later work by Parnas [24] already\"],\"2172169742\":[\"Ruby [26], and Java [2].\"],\"2480195817\":[\"Contract4J [30] is an AspectJ [18] based tool that supports classic DBC.\"],\"2803343605\":[\"For instance, grouping contracts related to specific requirements is almost impossible since the implementation of most of the requirements are spread over several classes and so cannot be related to a single one [7, 9].\",\"Feature analysis [9] is a 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on source code related questions that arise during maintenance.\"],\"2100894766\":[\"Developers of object-oriented software systems spend a significant amount of time on program comprehension [1]– [3].\"],\"2123344540\":[\"The feature driven browser in [15] and Senseo [16] are both extensions to an IDE that provide additional support by collecting run-time information.\",\"The IDE extension Senseo [16] supports the navigation in source code artifacts.\"],\"2131664240\":[\"Visualized run-time information has to be available within some hundreds of milliseconds rather than minutes [5].\",\"Schneiderman [5] argues that two seconds is the upper limit for responding to a user request.\"],\"2132383311\":[\"[14] presented three studies concerning reachability questions, which are described as a “search across feasible paths through a program for target statements matching search criteria”.\"],\"2148357053\":[\"They support reasoning about the behavior of programs in general, which might be 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prevent long rectangles that are difficult to see [20] or they highlight objects that are also neighbors in the hierarchical structure [21], [22].\"],\"2066031375\":[\"Doing this coverage ondemand is necessary as a complete statement-level coverage analysis of the whole system would slow down the execution by a factor of 100 [13].\"],\"2070321219\":[\"Our approach can additionally determine an expert by analyzing who last changed the method, who wrote the initial implementation, and who changes the method the most frequently [12].\"],\"2079317829\":[\"We argue that the required testing effort depends on individual skills and knowledge about the system under observation: Similarly to the debugging activity [11] more experienced developers invent better hypotheses than novices.\"],\"2088772524\":[\"AweSOM is an implementation of a SOM (Simple Object Machine) virtual machine in Squeak/Smalltalk [7].\"],\"2096508355\":[\"Commonly, well tested applications own only a coverage rate around 70-80% [4] and increasing\",\"Numerous studies [6], [8], [4] report similar observations during software testing.\"],\"2116771900\":[\"this coverage requires much more development effort [5].\"],\"2132627437\":[\"Numerous studies [6], [8], [4] report similar observations during software testing.\",\"suggest elementary guidelines [8].\"],\"2137440139\":[\"For these tests to be effective in identifying erroneous behavior it is necessary that test cases cover as much as possible of the system code [2].\"],\"2143661621\":[\"TestQ is a tool capable of statically analysing test code [18].\"],\"2146872957\":[\"of a compact and scalable tree map [10].\",\"The visualization of our approach is based on tree maps [10] that visualize arbitrary hierarchical structures by subdividing a given area into small rectangles.\"],\"2148322842\":[\"Hapao is a test coverage tool which uses a graphical visualization to facilitate the discovery of not (completely) tested code [17].\"],\"2151099659\":[\"Moreover, collecting run-time information at statement or branch level comes along with a perceivable performance decrease [6].\",\"Numerous studies [6], [8], [4] report similar observations during software testing.\",\"On the other hand developers complain that they do not know how much code is covered and how well the tested code is [6].\",\"surveyed numerous of them [6].\"],\"2155848253\":[\"While the dynamic analysis for method coverage can be implemented with aspect-oriented programming [16], statement-level coverage depends on the language features.\"],\"2157659145\":[\"the reliability of systems [9].\"],\"2162045655\":[\"[19] proposed a seminal work that aims at finding faults within a software system by comparing unit test results.\"],\"2170606151\":[\"In the course of time several other approaches have improved the standard layout algorithm: they prevent long rectangles that are difficult to see [20] or they highlight objects that are also neighbors 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languages\",\"IA\":{\"IndexLength\":134,\"InvertedIndex\":{\"Dynamically\":[0],\"typed\":[1],\"programming\":[2],\"languages\":[3,39],\"are\":[4,13],\"powerful\":[5],\"tools\":[6],\"for\":[7,98,107],\"rapid\":[8],\"software\":[9],\"development.\":[10],\"However,\":[11],\"there\":[12],\"scenarios\":[14],\"that\":[15,125],\"would\":[16],\"benefit\":[17],\"from\":[18],\"actual\":[19],\"type\":[20,49,65,73,105,126],\"information\":[21,106],\"being\":[22],\"available---e.\":[23],\"g.,\":[24],\"code\":[25,35,80,84,109],\"generation\":[26],\"and\":[27],\"optimisation\":[28],\"as\":[29,31],\"well\":[30,54],\"program\":[32],\"comprehension.\":[33],\"Since\":[34],\"written\":[36],\"in\":[37,85,93,116],\"such\":[38],\"usually\":[40],\"makes\":[41],\"little\":[42],\"or\":[43],\"no\":[44],\"explicit\":[45],\"assumptions\":[46],\"about\":[47],\"types,\":[48],\"inference\":[50],\"is\":[51,76],\"not\":[52],\"particularly\":[53],\"suited\":[55],\"to\":[56,71,102],\"obtain\":[57,104],\"the\":[58,83,89],\"desired\":[59],\"information.\":[60,74],\"This\":[61],\"paper\":[62],\"introduces\":[63],\"harvesting\":[66,96,127],\",\":[67],\"a\":[68,108],\"practical\":[69],\"approach\":[70,112],\"obtaining\":[72],\"It\":[75],\"based\":[77],\"on\":[78],\"stepwise\":[79],\"execution\":[81],\"of\":[82,91],\"question,\":[86],\"closely\":[87],\"observing\":[88],\"types\":[90],\"entities\":[92],\"question.\":[94],\"Type\":[95],\"allows\":[97],\"exploiting\":[99],\"unit\":[100],\"tests\":[101],\"automatically\":[103],\"base.\":[110],\"The\":[111],\"has\":[113],\"been\":[114],\"implemented\":[115],\"Squeak/Smalltalk.\":[117],\"Its\":[118],\"evaluation,\":[119],\"using\":[120],\"several\":[121],\"complex\":[122],\"applications,\":[123],\"shows\":[124],\"yields\":[128],\"excellent\":[129],\"results\":[130],\"with\":[131],\"high\":[132],\"precision.\":[133]}},\"S\":[{\"Ty\":3,\"U\":\"http://www.hirschfeld.org/writings/media/HauptPerscheidHirschfeld_2011_TypeHarvestingAPracticalApproachToObtainingTypingInformationInDynamicProgrammingLanguages_AcmDL.pdf\"},{\"Ty\":1,\"U\":\"https://dl.acm.org/citation.cfm?id=1982464\"},{\"Ty\":1,\"U\":\"http://dblp.uni-trier.de/db/conf/sac/sac2011.html#HauptPH11\"},{\"Ty\":1,\"U\":\"https://doi.acm.org/10.1145/1982185.1982464\"},{\"Ty\":0,\"U\":\"http://doi.acm.org/10.1145/1982185.1982464\"}],\"VFN\":\"ACM Symposium on Applied Computing\",\"VSN\":\"SAC\",\"FP\":1282,\"LP\":1289,\"DOI\":\"10.1145/1982185.1982464\",\"CC\":{\"1513058800\":[\"In fact, there exist approaches that adopt incremental execution of relevant tests as those parts of an application covered by them are changed [19, 21].\"],\"1574060188\":[\"Finally, dynamic analysis tools can verify deduced type information to identify failure causes [24].\"],\"1577728776\":[\"There exist inference engines [4, 2, 1, 20, 16, 6] that are however necessarily incomplete.\",\"More recent approaches [4, 2, 1, 20, 16, 6] mostly focus on obtaining type information for interfaces (i.\",\"Moreover, their precision is sometimes lower [20, 16].\"],\"1580606833\":[\"Other projects have pursued similar goals without necessarily aiming for systems software [13, 15, 2], mostly applying source-to-source translation and type inference.\"],\"1770006921\":[\"Second, we present an implementation of type harvesting in Squeak [12], an implementation of Smalltalk [7].\"],\"2031627901\":[\"In fact, there exist approaches that adopt incremental execution of relevant tests as those parts of an application covered by them are changed [19, 21].\"],\"2048486205\":[\"There also exist lightweight approaches like pluggable types [3, 8], where developers can annotate methods with type information.\",\"Apart from these two, pluggable types [3, 8] are worth mentioning, but since they require developers to provide type information, we do not discuss them here.\"],\"2053664570\":[\"Type inference for dynamically typed programming languages has been researched early on [22].\"],\"2088772524\":[\"One of the four projects, AweSOM [9], is a research project, namely a virtual machine for a Smalltalk dialect (SOM Smalltalk) written in Squeak.\"],\"2093334386\":[\"Type feedback [11] is a VM technique that drives just-in-time compiler optimisation decisions based on dynamically collected type information.\"],\"2120363698\":[\"There exist inference engines [4, 2, 1, 20, 16, 6] that are however necessarily incomplete.\",\"Other projects have pursued similar goals without necessarily aiming for systems software [13, 15, 2], mostly applying source-to-source translation and type inference.\",\"More recent approaches [4, 2, 1, 20, 16, 6] mostly focus on obtaining type information for interfaces (i.\"],\"2122592814\":[\"Type inference for the Ruby programming language [6] has been augmented by profile-guided typing [5].\"],\"2133468633\":[\"Additional type information reduces the set of call graph branches to the possibilities actually assigned in a specific context [10].\"],\"2135536553\":[\"There exist inference engines [4, 2, 1, 20, 16, 6] that are however necessarily incomplete.\",\"More recent approaches [4, 2, 1, 20, 16, 6] mostly focus on obtaining type information for interfaces (i.\",\"Type inference for the Ruby programming language [6] has been augmented by profile-guided typing [5].\"],\"2138732532\":[\"There exist inference engines [4, 2, 1, 20, 16, 6] that are however necessarily incomplete.\",\"More recent approaches [4, 2, 1, 20, 16, 6] mostly focus on obtaining type information for interfaces (i.\"],\"2148357053\":[\"Developers maintain a mental model of program behaviour [14] by navigating the static call graph for a specific method of interest and following several paths comprised of sender and implementor relationships.\"],\"2149539713\":[\"There exist inference engines [4, 2, 1, 20, 16, 6] that are however necessarily incomplete.\",\"More recent approaches [4, 2, 1, 20, 16, 6] mostly focus on obtaining type information for interfaces (i.\",\"Moreover, their precision is sometimes lower [20, 16].\"],\"2165046128\":[\"There exist inference engines [4, 2, 1, 20, 16, 6] that are however necessarily incomplete.\",\"More recent approaches [4, 2, 1, 20, 16, 6] mostly focus on obtaining type information for interfaces (i.\"],\"2170311191\":[\"The Hermion [18] IDE extension for Squeak is designed for providing developers with additional run-time information during static source code navigation.\"],\"2172147300\":[\"Second, we present an implementation of type harvesting in Squeak [12], an implementation of Smalltalk [7].\"]},\"PR\":[1507181701,2305374267,2189052291,2089214613,2896137925,16483339,1581126267,208806687,1017474348,1578444545,2307785417,2085983541,202833674,2468602413,1606191713,2181924625,2889858359,1964178963,2794515005,812190219,1507181701,2305374267,2189052291,2089214613,2896137925,16483339,1581126267,208806687,1017474348,1578444545,2307785417,2085983541,202833674,2468602413,1606191713,2181924625,2889858359,1964178963,2794515005,812190219],\"ANF\":[{\"FN\":\"Michael\",\"LN\":\"Haupt\",\"S\":1},{\"FN\":\"Michael\",\"LN\":\"Perscheid\",\"S\":2},{\"FN\":\"Robert\",\"LN\":\"Hirschfeld\",\"S\":3}],\"BV\":\"Proceedings of the 2011 ACM Symposium on Applied Computing\",\"BT\":\"p\",\"PB\":\"ACM\"}"},{"logprob":-21.586,"Id":169400382,"Ty":"0","Ti":"an introduction to 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on Software Maintenance and Reengineering\",\"VSN\":\"CSMR\",\"FP\":124,\"LP\":133,\"DOI\":\"10.1109/CSMR-WCRE.2014.6747162\",\"CC\":{\"169400382\":[\"We have inserted a defect into the Seaside Web framework [8] and its request/response processing logic (BufferedResponse class, writeHeadersOn: method).\"],\"175708229\":[\"Later, a novel indexing and querying technique [24] ensures scalability to arbitrarily large execution traces and offers an interactive debugging experience.\"],\"1482473201\":[\"Unstuck [21] is the first back-in-time debugger for Smalltalk but suffers from similar performance problems.\"],\"1507612039\":[\"Object flow analysis [25] provides a practical back-in-time debugger that leverages the virtual machine and its garbage collector to remove no longer reachable objects and to discard corresponding events.\"],\"1574060188\":[\"Debugging is largely an attempt to understand what causes failures [1].\",\"They understand failure causes step by step, make fewer and simpler decisions about how to follow execution histories, and focus their attention on finding defects [1].\",\"Especially, the missing classification of suspicious and harmless program entities leads to numerous and often laborious decisions which execution subtree to follow [1].\",\"Such state differences have a high probability to include failure causes so that developers can rely on this information for creating their hypotheses [1].\"],\"1774013863\":[\"With a mapping on execution histories of our previous back-in-time debugger [5], [6], anomalies reveal infection chains and guide developers to root causes.\",\"Our test-driven fault navigation [5] is a debugging guide that integrates spectrum-based anomaly detection [10], [12] into a systematic breadth-first search for tracing failure causes back to defects.\",\"3 summarizes the call tree of our back-in-time debugger [5], [6] with our state navigation extension.\",\"We implement our state navigation as part of our test-driven fault navigation and its corresponding Path tools framework [5] for the Squeak/Smalltalk development environment [7].\",\"We base this study on our previous user study [5] in order to assess the positive influence of our state navigation.\",\"During the study, our participants are supposed to localize four failures which we have already applied in our previous study5 [5].\",\"So far, this tool already supports the classification of suspicious method calls with spectrum-based anomalies [5].\"],\"1972151373\":[\"With a mapping on execution histories of our previous back-in-time debugger [5], [6], anomalies reveal infection chains and guide developers to root causes.\",\"By integrating these spectrum-based anomalies into our back-in-time debugger [6], we highlight suspicious method calls and allow developers to distinguish between suspicious and expected run-time behavior.\",\"3 summarizes the call tree of our back-in-time debugger [5], [6] with our state navigation extension.\",\"The tool suite consists of our enhanced test runner PathMap [18] and our lightweight back-in-time debugger PathFinder [6].\",\"Compared to these tools, our PathFinder is a lightweight and specialized back-in-time debugger for localizing failure causes in failing test cases [6].\"],\"1981537308\":[\"Second, our anomalies shall be refined with interactive developer feedback [31] in such a way that identified false positives strengthen the remaining failure cause probabilities.\"],\"1983119041\":[\"Later, an extension to Daikon [26] solves this problem by optimizing polymorphism and filtering unchanged values.\"],\"1986331539\":[\"Screeners [28] further optimize the run-time overhead and decrease it to only 14 %.\"],\"2002568360\":[\"With likely invariants, our state navigation generates dynamic contracts [14] that automatically detect corrupted state in failing test cases.\"],\"2002985857\":[\"The trace-oriented debugger (TOD) [23] combines an efficient instrumentation for capturing exhaustive traces and a specialized distributed database.\"],\"2065296680\":[\"The tool suite consists of our enhanced test runner PathMap [18] and our lightweight back-in-time debugger PathFinder [6].\"],\"2066031375\":[\"Our type harvester gathers detailed type information of executed program entities [16]2.\"],\"2092221178\":[\"Compared to Daikon [11] that provides a considerable amount of more likely invariants, it has been shown that too many invariants can limit their intent for debugging [13], [17].\",\"A current study reports that automatically generated program invariants by Daikon [11] are sometimes hard to understand and tend to produce false positives [17].\",\"Finally, comparative studies [17], [30] of programmer-written and likely invariants conclude that a combination of both methods is most promising.\"],\"2092239677\":[\"Unfortunately, this idealized procedure requires deep knowledge of the system and its behavior [2].\"],\"2099866050\":[\"ClearView [29] also monitors invariants on the fly but it applies them to automatically patch upcoming failures.\"],\"2105263737\":[\"For a detailed description of our tools and how to debug with them, we refer to [19].\"],\"2110908283\":[\"3) Anomalies: What Are Possible Failure Causes?: Anomalies such as from program spectra [10] or likely invariants [11] automatically identify possible failure causes by deriving runtime properties from reference runs and comparing them with failing executions.\",\"ing dynamic analysis of likely invariants tends to be timeconsuming because each object has to be explored at each execution point in full detail [11].\",\"Compared to Daikon [11] that provides a considerable amount of more likely invariants, it has been shown that too many invariants can limit their intent for debugging [13], [17].\",\"A current study reports that automatically generated program invariants by Daikon [11] are sometimes hard to understand and tend to produce false positives [17].\",\"Daikon [11] comprises a set of automatic techniques for inferring generalized program state from execution traces.\"],\"2114178685\":[\"Finally, comparative studies [17], [30] of programmer-written and likely invariants conclude that a combination of both methods is most promising.\"],\"2116409384\":[\"Diduce [27] extends Daikon’s approach and derives invariants on the fly.\"],\"2162045655\":[\"Differences have a high probability of including failure causes [12] and so help developers to narrow down the search space by answering which program entities are potentially infected.\",\"Our test-driven fault navigation [5] is a debugging guide that integrates spectrum-based anomaly detection [10], [12] into a systematic breadth-first search for tracing failure causes back to defects.\"],\"2162376048\":[\"Since failures and defects can be far apart from each other, their unknown infection chains are consequently long and demand a laborious effort for debugging [3].\",\"However, starting debugging at failures still includes a long way back to their root causes [3].\"],\"2164372721\":[\"WhyLine [22] allows developers to ask a set of “why did” and “why didn’t” questions such as why a line of code was not reached.\",\"First, our approach will be extended with why-questions [22] to even better guide developers through execution histories.\"],\"2172147300\":[\"• The Path tools framework implements our completely automatic approach as part of our test-driven fault navigation in Squeak/Smalltalk [7].\",\"We implement our state navigation as part of our test-driven fault navigation and its corresponding Path tools framework [5] for the Squeak/Smalltalk development environment [7].\"],\"2782959840\":[\"Based on the coverage of our failing tests, we instrument each of the included classes and their methods with harvester wrappers to transparently add analysis code around the original implementation [15].\"],\"2798692074\":[\"For example, typos are common and often difficult to localize 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Symposium on Software Reliability Engineering\",\"VSN\":\"ISSRE\",\"FP\":269,\"LP\":274,\"DOI\":\"10.1109/ISSREW.2014.36\",\"CC\":{\"107792539\":[\"” [7].\"],\"1502739415\":[\"The earliest studies trying to understand how debugging works date as far back as 1974 [3].\",\"Gould and Drongowski [3] conducted a lab study with 30 participants.\"],\"1843474218\":[\"For example, there have been multiple approaches to automate parts of the fault localization process [23]–[40], a categorization and overview can be found in [10].\"],\"1960390258\":[\"“Debugging is twice as hard as writing the program in the first place” [1].\"],\"1989678938\":[\"A year later, the same authors studied developers equipped with a symbolic debugger [11].\"],\"2000711964\":[\"In 1997, Eisenstadt [14] collected 59 bug anecdotes from experts and proposed a three dimensional classification of bug stories:\",\"However, to the best of our knowledge, the latest general purpose debugging study amongst professional software developers is more than 15 years old [14].\",\"We ask them to position it in all three dimensions of a bug war story Eisenstadt [14] defined: The type of the bug, why it was especially hard to debug, and what technique turned out to be most helpful to find it.\"],\"2092239677\":[\"In 1985, Vessey found evidence that programming experts and novices differ in their debugging strategies [13].\"],\"2132383311\":[\"Since 2000, many researchers have tried to improve the understanding of specific aspects of debugging [9], [15]–[22], but these focus mostly on the introduction of new tools or how debugging can be taught to students.\"],\"2141109493\":[\"In 1982, Weiser introduced the notion of program slicing [12].\"],\"2156357889\":[\"For example, there have been multiple approaches to automate parts of the fault localization process [23]–[40], a categorization and overview can be found in [10].\"],\"2794372210\":[\"In the following years, debugging tools have been improved and the lack of knowledge has been tackled [2], [4]–[6].\",\"“Debugging: The 9 Indispensable Rules for Finding Even the Most Elusive Software and Hardware Problems” [6] was one of the first general purpose debugging books.\"],\"2798692074\":[\"“Debugging by Thinking” [5] relates debugging with other domains of problem solving and tries to apply their 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