Knowledge-based fault localization in debugging

Sedlmeyer, Robert L.; Thompson, William B.; Johnson, Paul E.

doi:10.1145/1006140.1006154

Cited by 4 publications

(5 citation statements)

References 2 publications

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“…Since the early 1980s some knowledge-based approaches (Lukey, 1980;Sedlmeyer et al, 1983;Pau, 1986;Hunt, 1997) have been developed to automate the fault-localization process. These approaches require expert developers to manually provide knowledge about the expected program behaviour and a set of classified faults.…”

Section: Threats To Validitymentioning

confidence: 99%

Architecture‐driven assistance for fault‐localization tasks

2013

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Finding software faults is a problematic activity in many systems. Existing approaches usually work close to the system implementation and require developers to perform different code analyses. Although these approaches are effective, the amount of information to be managed by developers is often overwhelming. This problem calls for complementary approaches able to work at higher levels of abstraction than code, helping developers to keep intellectual control over the system when analyzing faults. In this context, we present an expert‐system approach, called FLABot, which assists developers in fault‐localization tasks by reasoning about faults using software architecture models. We have evaluated a prototype of FLABot in two medium‐size case studies, involving novice and non‐novice developers. We compared time consumed, code browsed and faults found by these developers, with and without the support of FLABot, observing interesting effort reductions when applying FLABot. The results and lessons learned have shown that our approach is practical and reduces the efforts for finding individual faults.

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Section: Threats To Validitymentioning

confidence: 99%

Architecture‐driven assistance for fault‐localization tasks

2013

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“…In short, fault isolation is an effort to identify source code statements that cause anomalous behavior [41]. This field of research is highly applicable to the work presented in this thesis largely because the endeavor to automated web configuration fault isolation is largely an attempt to isolated unsupported tags/rules using source code analysis.…”

Section: Fault Isolationmentioning

confidence: 99%

A Framework for Detecting and Diagnosing Configuration Faults in Web Applications

Memon

Eaton

2012

Advances in Computers

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Software portability is a key concern when target operational environments are highly configurable; variations in configuration settings can significantly impact software correctness. While portability is key for a wide range of software types, it is a significant challenge in web application development. The client configuration used to navigate and interact with web content is known to be an important factor in the subsequent quality of deployed web applications. With the widespread use of diverse, heterogeneous web client configurations, the results of web application deployment can vary unpredictably among users. Given existing approaches and limited development resources, attempting to develop web applications that are viewable, functional, and portable for the vast web configuration space is a significant undertaking. As a result, faults that only surface in precise configurations, termed configuration faults, have the potential to escape detection until web applications are fielded.This dissertation presents an automated, model-based framework that uses static analysis to detect and diagnose web configuration faults. This approach overcomes the limitations of current techniques by featuring an extensible model of the configuration space that enables efficient portability analysis across the vast array of client environments. The basic idea behind this approach is that source code fragments (i.e., HTML tags and CSS rules) embedded in web application source code adversely impact portability of web applications when they are unsupported in target client configurations; without proper support, the source code is either processed incorrectly or ignored, resulting in configuration faults. Using static analysis, configuration fault detection is performed by applying a model of the web application source against knowledge of support criteria; any unsupported source code detected is considered an index to potential configuration faults. In the effort to fully exploit this approach, improve practicality, and maximize fault detection efficiency, manual and automated approaches to knowledge acquisition have been implemented, variations of web application and client support knowledge models have been investigated, and visualization of configuration fault detection results has been explored. To optimize the automated acquisition of support knowledge, alternate learning strategies have been empirically investigated and provisions for capturing tag interaction have been integrated into the process.

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“…However, there is also a portion of automated debugging research which can apply equally, or at least be adapted, to suit both imperative and declarative programs. These approaches include using data-flow analysis to help with program slicing [23], predicate switching [24] and knowledge-based localisation [1].…”

Section: Learning From the Pastmentioning

confidence: 99%

“…Debugging is readily classified into three parts, identifying the existence of a problem, fault localisation and the actual correction of the problem [1]. Generally, once a problem is located, a developer who is adequately experienced with the technology can correct the problem with minimal effort.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, once a problem is located, a developer who is adequately experienced with the technology can correct the problem with minimal effort. Traditionally the majority of effort is spent on bug localisation [1][2][3] and the case in model transformations is no different. Based on the premise that automation of bug localisation will provide the greatest benefit to the developer or modeler, we describe debugging primarily in terms of this localisation.…”

Section: Introductionmentioning

confidence: 99%

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Forensic Debugging of Model Transformations

Hibberd

Lawley

Raymond

Model Driven Engineering Languages and Systems

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Abstract. Software bugs occur in model-driven development, just as they do with traditional development techniques. We explore the types of bugs that occur in model transformations and identify debugging approaches that can be applied or adapted to a model-driven context. Investigation shows that the detailed source-to-target traceability available with model transformations enables effective post-hoc, or forensic, debugging. Forensic debugging techniques are introduced for automated bug localisation in model transformations. The methods discussed are grounded with examples using the Eclipse Modeling Framework (EMF) and Tefkat, a declarative model transformation engine.

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Knowledge-based fault localization in debugging

Cited by 4 publications

References 2 publications

Architecture‐driven assistance for fault‐localization tasks

Architecture‐driven assistance for fault‐localization tasks

A Framework for Detecting and Diagnosing Configuration Faults in Web Applications

Forensic Debugging of Model Transformations

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