Exception Handling Patterns for Process Modeling

Lerner, Barbara; Christov, Stefan C.; Osterweil, Leon J.; Bendraou, Reda; Kannengiesser, Udo; Wise, Alexander

doi:10.1109/tse.2010.1

Cited by 103 publications

(44 citation statements)

References 19 publications

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“…Exception disturbs the typical stream of the project's guideline [18]. There are different reasons due to which exception can occur:…”

Section: Exception Handlingmentioning

confidence: 99%

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Novel Approaches to Improve Software Quality

Hassan¹,

Umair²,

Ali³

2017

IJSEIA

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“…Exception disturbs the typical stream of the project's guideline [18]. There are different reasons due to which exception can occur:…”

Section: Exception Handlingmentioning

confidence: 99%

“… Wrong path to the file  User don't have access to that directory  Directory does not found  Invalid command by user  Loss of Network Connection Some exception occurs due to user and programmer error and other due to failure of physical resources [18]. There are three different types of exceptions:…”

Section: Exception Handlingmentioning

confidence: 99%

Novel Approaches to Improve Software Quality

Hassan¹,

Umair²,

Ali³

2017

IJSEIA

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show abstract

“…Automated creation and adaptation of the data collection processes will thus be favourable. In this area, only a small number of approaches exist, e.g., AgentWork [28] and SmartPM [29] However, these are limited to rule based detection of exceptions and application of countermeasures.…”

Section: Dynamic Processesmentioning

confidence: 99%

Towards Collecting Sustainability Data in Supply Chains with Flexible Data Collection Processes

Mundbrod

Kolb

Reichert

2015

Lecture Notes in Business Information Processing

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Abstract. Nowadays, OEMs from many domains (e.g., electronics and automotive) face rising pressure from customers and legal regulations to produce more sustainable products. This involves the reporting and publishing of various sustainability indicators. However, the demands of legal entities and customers constitute a tremendous challenge as products in these domains comprise various components and sub-components provided by suppliers. Hence, sustainability data collection must be executed along the entire supply chain. In turn, this involves a myriad of different automated and manual tasks as well as quickly changing situations. In combination with potentially long-running processes, these issues result in great process variability that cannot be predicted at design time. In the SustainHub project, a dedicated information system for supporting data collection processes is developed. This paper provides three contributions: (1) it identifies core challenges for sustainable supply chain communication, (2) it reviews state-of-the-art technical solutions for such challenges, and (3) it gives a first overview of the approach we are developing in the SustainHub project to address the challenges. By achieving that, this comprehensive approach has the potential to unify and simplify supply chain communication in the future.

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“…In this paper, we focus on the common software engineering process of refactoring an object. This work builds on our prior work on exception handling patterns in processes [4], but by elaborating upon this particular kind of software rework, this elaboration provides more clarity about the nature of rework and how it fits our exception-driven rework pattern. It also sheds light on the critical role of context in performing rework.…”

Section: Introductionmentioning

confidence: 99%

The role of context in exception-driven rework

Zhao

Lerner

Osterweil

2012

2012 5th International Workshop on Exception Handling (WEH)

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Abstract-Exception-driven rework occurs commonly in software development. In this paper, we describe a simple refactoring process, showing the use of the exception-driven rework exception handling pattern within it. We also discuss the important role that context plays in supporting the user during rework in helping the user keep track of the tasks being worked on and to facilitate resumption of normal activities upon completion of the exception handling work. The example process is specified in the Little-JIL process definition language. The use of context information in supporting the user is illustrated using a Data Derivation Graph (DDG), a graph that is automatically generated to document the ways in which artifact values are evolved during execution of a Little-JIL process.

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Exception Handling Patterns for Process Modeling

Cited by 103 publications

References 19 publications

Novel Approaches to Improve Software Quality

Novel Approaches to Improve Software Quality

Towards Collecting Sustainability Data in Supply Chains with Flexible Data Collection Processes

The role of context in exception-driven rework

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