The document describes an approach for detecting process antipatterns in BPEL processes. It begins by discussing the motivation for detecting antipatterns, which are poor design decisions that can negatively impact quality of service. It then reviews related work on modeling antipatterns, detecting them in BPMN models, and defining patterns in BPEL. The identified gaps are that antipatterns have not been considered for BPEL processes and quality aspects were not included. The proposed approach involves specifying antipatterns as rules, transforming BPEL processes into a generic model, and then detecting antipatterns by applying the rules. A small experiment is described to detect two antipatterns in three sample BPEL processes.
130905 francis palma - detection of process antipatterns - a bpel perspectivePtidej Team
The document presents an approach for detecting antipatterns in BPEL (Business Process Execution Language) processes. It specifies seven common antipatterns using rules of inference. The approach transforms BPEL processes into simplified and generic models to ease implementation of detection rules. It then applies the rules semi-automatically to detect antipatterns. A small experiment detects two antipatterns in three example BPEL processes. The approach aims to improve process quality and maintainability by identifying antipatterns.
This document describes the fundamental test process, which includes test planning, analysis and design, implementation and execution, evaluating exit criteria and reporting, and test closure activities. It provides details on the main tasks for each part of the test process, such as determining test scope and objectives, designing test cases, executing tests, assessing if testing goals have been met, and finalizing and archiving test materials for future use. The overall process aims to systematically test software through a planned sequence of activities to uncover defects and ensure quality.
5 M-CARE: Социално включване
http://mcare-project.eu/?lang=bg
Този проект (M-Care - 539913-LLP-1-2013-1-TR-LEONARDO-LMP) е частично финансиран от Европейската комисия. Настоящата публикация излага само възгледите на автора, като Комисията не носи отговорност за изчерпателността и верността на информацията, посочена тук, нито за възможните начини за нейната употреба.
130214 wei wu - extracting business rules and removing duplication with irisPtidej Team
The document discusses using the IRIS tool to extract business rules from source code and detect duplicated rules. It outlines extracting terms and conditions from database-related code elements. Rules are extracted by identifying top-level conditional statements and associated code elements. Duplicated rules are detected by normalizing rules and comparing identifiers. Examples show rules extracted from COBOL code and duplicated rules identified. Future work includes refining detection of similar rules and removing irrelevant elements.
Fatigue, drugs and alcohol are defined in research as problem areas for the building and construction industry. Too few of us actually understand what drugs are, their relationship to each other and how they affect our workers. Non-drug related fatigue is also poorly recognised on-site. In today's session Frontline Diagnostics provided the attendees with a preliminary understanding of drugs in the work environment and ways to manage them through a simple but comprehensive Drug-Safe Workplace programme.
130905 francis palma - detection of process antipatterns - a bpel perspectivePtidej Team
The document presents an approach for detecting antipatterns in BPEL (Business Process Execution Language) processes. It specifies seven common antipatterns using rules of inference. The approach transforms BPEL processes into simplified and generic models to ease implementation of detection rules. It then applies the rules semi-automatically to detect antipatterns. A small experiment detects two antipatterns in three example BPEL processes. The approach aims to improve process quality and maintainability by identifying antipatterns.
This document describes the fundamental test process, which includes test planning, analysis and design, implementation and execution, evaluating exit criteria and reporting, and test closure activities. It provides details on the main tasks for each part of the test process, such as determining test scope and objectives, designing test cases, executing tests, assessing if testing goals have been met, and finalizing and archiving test materials for future use. The overall process aims to systematically test software through a planned sequence of activities to uncover defects and ensure quality.
5 M-CARE: Социално включване
http://mcare-project.eu/?lang=bg
Този проект (M-Care - 539913-LLP-1-2013-1-TR-LEONARDO-LMP) е частично финансиран от Европейската комисия. Настоящата публикация излага само възгледите на автора, като Комисията не носи отговорност за изчерпателността и верността на информацията, посочена тук, нито за възможните начини за нейната употреба.
130214 wei wu - extracting business rules and removing duplication with irisPtidej Team
The document discusses using the IRIS tool to extract business rules from source code and detect duplicated rules. It outlines extracting terms and conditions from database-related code elements. Rules are extracted by identifying top-level conditional statements and associated code elements. Duplicated rules are detected by normalizing rules and comparing identifiers. Examples show rules extracted from COBOL code and duplicated rules identified. Future work includes refining detection of similar rules and removing irrelevant elements.
Fatigue, drugs and alcohol are defined in research as problem areas for the building and construction industry. Too few of us actually understand what drugs are, their relationship to each other and how they affect our workers. Non-drug related fatigue is also poorly recognised on-site. In today's session Frontline Diagnostics provided the attendees with a preliminary understanding of drugs in the work environment and ways to manage them through a simple but comprehensive Drug-Safe Workplace programme.
Detection of Process Antipatterns: An BPEL PerspectiveFrancis Palma
The document presents an approach for detecting process antipatterns in BPEL (Business Process Execution Language) processes. It defines seven antipatterns using rules of inference and describes a method to transform BPEL processes into a simplified generic model. An experiment applies the approach to detect two antipatterns in three sample BPEL processes with limited detection success due to the small process sizes. Future work is needed to automate the approach and detect more antipatterns in larger, real-world processes.
The document describes an approach called SODA-BP for specifying and detecting business process antipatterns. SODA-BP involves defining antipatterns using rule cards, generating detection algorithms from the rule cards, and applying the algorithms to detect antipattern occurrences in business processes. The approach was validated on eight antipatterns across 35 BPEL processes.
The document describes an approach called SODA-BP for specifying and detecting business process antipatterns. SODA-BP involves defining business process antipatterns using rule cards, generating detection algorithms from the rule cards, and applying the algorithms to detect antipatterns in processes. The researchers validate SODA-BP by specifying 8 antipatterns, implementing detection for them, and applying the detection to 35 business processes to identify occurrences of the antipatterns. Experimental results demonstrate that SODA-BP can accurately detect a variety of different antipatterns in processes.
Specification and Detection of Business Process AntipatternsFrancis Palma
The document describes an approach called SODA-BP for specifying and detecting business process antipatterns. SODA-BP involves defining antipatterns using rule cards, generating detection algorithms from the rule cards, and applying the algorithms to detect antipattern occurrences in business processes. The approach was validated on eight antipatterns across 35 BPEL processes.
This document presents the results of a systematic mapping study on software product size measurement methods. The study identified 79 different size measurement methods, most of which (86%) measure functional size. Only 19% of methods were novel, while the rest extended or tailored existing approaches. The study found that size measurement is most applicable to data-dominant domains, and future work could focus on tailoring methods for object-oriented development and automated measurement tool development.
This document presents an approach for detecting service-oriented architecture (SOA) antipatterns. It discusses problems in existing literature, such as a lack of specifications for SOA antipatterns and no approaches for detecting them. The proposed solution involves specifying SOA antipatterns using rule cards, generating detection algorithms, detecting suspicious services, and validating the results. A domain-specific language and framework called Service Oriented Detection for Antipatterns (SODA) are developed to implement this approach. The goal is to provide a solution for detecting SOA antipatterns in service-based systems and validating the impacts.
A Survey on Software Release Planning Models - Slides for the Presentation @ ...Supersede
Software release planning (SRP) is the problem of selecting which features or requirements will be included in the next release or releases. It is a crucial step in software development, which happens to be extremely complex given the need to reconcile multiple decision making criteria, (e.g., business value, effort and cost), while considering several constraints (e.g., feature precedencies, resource availa-bility). For this reason, several SRP models have been proposed in the literature. The objective of this study is to provide an updated review of SRP approaches reported in the literature.
Operational research is the scientific approach to problem solving and decision making. It involves formulating problems mathematically and using scientific techniques like simulation, optimization, and data analysis to solve complex real-world problems. Some key applications of operational research include supply chain management, transportation and logistics, production scheduling, and resource allocation in industries like airlines, manufacturing, and healthcare. The goal is to help decision makers identify optimal solutions and improve performance.
The document provides information about an Operations Research course. It includes the objective of the course, which is to develop and analyze mathematical models for decision problems and their systematic solution. It also lists the various topics that will be covered in the course, including linear programming, transportation problems, game theory, and metaheuristics. The course aims to help students identify and solve real-world business problems by applying appropriate operations research techniques.
Process Mining: A Guide for PractitionersMarlon Dumas
This document presents a guide for practitioners on process mining. It introduces process mining and discusses its main use cases. These use cases are categorized into discovery oriented, future and change oriented, alignment oriented, variant oriented, and performance oriented. The document also provides a framework to classify use cases and discusses the business-oriented questions that can be answered using different process mining use cases, such as improving transparency, quality, agility, efficiency and conformance.
applications of operation research in businessraaz kumar
1) Operations research is a quantitative approach to decision making based on the scientific method of problem solving. It involves modeling real-life situations as mathematical problems to arrive at optimal or near-optimal solutions.
2) The key steps in operations research problem solving are defining the problem, determining alternative solutions, evaluating alternatives using criteria, choosing the best alternative, implementing the chosen alternative, and evaluating the results.
3) Common techniques used in operations research include linear programming, transportation modeling, assignment modeling, and simulation methods like PERT/CPM. These techniques help optimize objectives while satisfying constraints.
Empirical research methods for software engineeringsarfraznawaz
This document outlines guidelines for empirical research methods in software engineering. It discusses case studies, experimental research, surveys, and post-mortem analysis. For each method, it provides examples and discusses how the method can be used to study software engineering problems. It also lists detailed guidelines for different aspects of empirical research, such as experimental context and design, data collection, analysis, and presentation and interpretation of results. The goal of the guidelines is to improve the quality and rigor of empirical studies in software engineering.
A Comparative Study between Agile Methods of Software DevelopmentFelipe Alves
The document presents an extension of a comparative study between agile software development methods. It analyzes methods such as XP, Scrum, Crystal, FDD, DSDM, ASD, Kanban, Agile Modeling, OpenUP, and AgileUP based on key points, main features, and limitations. The study aims to help organizations choosing the most suitable agile method for their software projects and to spread knowledge about these methods.
Operations research is a scientific approach to decision making that was developed during World War II and is now used widely in business and industry. It involves defining problems quantitatively and building mathematical models to represent real-world situations. These models are used to evaluate alternative solutions systematically and predict outcomes in order to optimize decisions. The process involves identifying problems, developing models, obtaining optimal solutions using techniques like linear programming, testing the model solutions, and implementing the best solution. Operations research helps organizations make more informed decisions using data, consider all options, and manage resources effectively.
Operations research is the application of analytical methods to help decision-makers choose optimal courses of action. It originated during World War II and uses mathematical techniques like linear programming, non-linear programming, and stochastic programming to optimize resource allocation. Linear programming involves maximizing or minimizing a linear objective function subject to linear constraints. Examples of linear programming problems include product mix problems, blending problems, and production scheduling problems.
These slides accompany the textbook "Software Engineering: A Practitioner's Approach" and were created by Roger Pressman. They cover various topics related to software engineering process models, including prescriptive models like the waterfall model and V-model, evolutionary models like prototyping, spiral development and concurrent development, and specific models like the Unified Process, Personal Software Process and Team Software Process. The slides also discuss process patterns, assessment methods and improving software processes.
Analysis of Feature Models using Alloy - A surveyAnjali Sreekumar
This is a presentation of the work on a survey related to Feature model analysis using Alloy presented during the FMSPLE workshop at Eindhoven University of Technology on 3rd April 2016.
This document discusses metrics that can be used to measure software processes and projects. It begins by explaining why measurement is important for assessing project status, tracking risks, finding problem areas, and improving processes. It then provides examples of different types of metrics that can be measured, including process metrics related to quality, productivity, and reuse, as well as project metrics related to inputs, outputs, results, effort, defects, and size. Guidelines are also given for establishing an effective metrics program.
This document outlines and compares two papers on task scheduling for software development projects. For the first paper, it summarizes the analytical method used to model tasks as a graph and schedule them across global teams to minimize project time. For the second paper, it summarizes the simulation model used to analyze how different scheduling strategies affect project progress and completion time. It then compares the two papers, noting that the first generates a scheduling policy while the second takes a policy as input, and that the second provides more insight but was only tested on simulated data.
The document discusses the history and current state of software engineering and its application to IoT systems. It notes that 50 years after the earliest software projects, issues still include cost overruns, property damage, risks to life and death, and challenges ensuring quality. For IoT, fragmentation across hardware, software, APIs and standards poses significant problems. The document proposes that research into IoT software engineering could help address these issues through approaches like developing software to run across diverse IoT platforms, and automatically miniaturizing software through techniques like multi-objective optimization to suit different IoT device capabilities.
1) Issue trackers are often used to track more than just bugs, including features, enhancements, and refactoring work.
2) A manual analysis found that nearly half of issues labeled as "bugs" in issue trackers were actually not bugs.
3) Relying on issue tracker labels alone can introduce significant errors into datasets used for tasks like bug prediction and severity estimation. More work is needed to clean noisy and unreliable data.
More Related Content
Similar to 130411 francis palma - detection of process antipatterns -- a bpel perspective
Detection of Process Antipatterns: An BPEL PerspectiveFrancis Palma
The document presents an approach for detecting process antipatterns in BPEL (Business Process Execution Language) processes. It defines seven antipatterns using rules of inference and describes a method to transform BPEL processes into a simplified generic model. An experiment applies the approach to detect two antipatterns in three sample BPEL processes with limited detection success due to the small process sizes. Future work is needed to automate the approach and detect more antipatterns in larger, real-world processes.
The document describes an approach called SODA-BP for specifying and detecting business process antipatterns. SODA-BP involves defining antipatterns using rule cards, generating detection algorithms from the rule cards, and applying the algorithms to detect antipattern occurrences in business processes. The approach was validated on eight antipatterns across 35 BPEL processes.
The document describes an approach called SODA-BP for specifying and detecting business process antipatterns. SODA-BP involves defining business process antipatterns using rule cards, generating detection algorithms from the rule cards, and applying the algorithms to detect antipatterns in processes. The researchers validate SODA-BP by specifying 8 antipatterns, implementing detection for them, and applying the detection to 35 business processes to identify occurrences of the antipatterns. Experimental results demonstrate that SODA-BP can accurately detect a variety of different antipatterns in processes.
Specification and Detection of Business Process AntipatternsFrancis Palma
The document describes an approach called SODA-BP for specifying and detecting business process antipatterns. SODA-BP involves defining antipatterns using rule cards, generating detection algorithms from the rule cards, and applying the algorithms to detect antipattern occurrences in business processes. The approach was validated on eight antipatterns across 35 BPEL processes.
This document presents the results of a systematic mapping study on software product size measurement methods. The study identified 79 different size measurement methods, most of which (86%) measure functional size. Only 19% of methods were novel, while the rest extended or tailored existing approaches. The study found that size measurement is most applicable to data-dominant domains, and future work could focus on tailoring methods for object-oriented development and automated measurement tool development.
This document presents an approach for detecting service-oriented architecture (SOA) antipatterns. It discusses problems in existing literature, such as a lack of specifications for SOA antipatterns and no approaches for detecting them. The proposed solution involves specifying SOA antipatterns using rule cards, generating detection algorithms, detecting suspicious services, and validating the results. A domain-specific language and framework called Service Oriented Detection for Antipatterns (SODA) are developed to implement this approach. The goal is to provide a solution for detecting SOA antipatterns in service-based systems and validating the impacts.
A Survey on Software Release Planning Models - Slides for the Presentation @ ...Supersede
Software release planning (SRP) is the problem of selecting which features or requirements will be included in the next release or releases. It is a crucial step in software development, which happens to be extremely complex given the need to reconcile multiple decision making criteria, (e.g., business value, effort and cost), while considering several constraints (e.g., feature precedencies, resource availa-bility). For this reason, several SRP models have been proposed in the literature. The objective of this study is to provide an updated review of SRP approaches reported in the literature.
Operational research is the scientific approach to problem solving and decision making. It involves formulating problems mathematically and using scientific techniques like simulation, optimization, and data analysis to solve complex real-world problems. Some key applications of operational research include supply chain management, transportation and logistics, production scheduling, and resource allocation in industries like airlines, manufacturing, and healthcare. The goal is to help decision makers identify optimal solutions and improve performance.
The document provides information about an Operations Research course. It includes the objective of the course, which is to develop and analyze mathematical models for decision problems and their systematic solution. It also lists the various topics that will be covered in the course, including linear programming, transportation problems, game theory, and metaheuristics. The course aims to help students identify and solve real-world business problems by applying appropriate operations research techniques.
Process Mining: A Guide for PractitionersMarlon Dumas
This document presents a guide for practitioners on process mining. It introduces process mining and discusses its main use cases. These use cases are categorized into discovery oriented, future and change oriented, alignment oriented, variant oriented, and performance oriented. The document also provides a framework to classify use cases and discusses the business-oriented questions that can be answered using different process mining use cases, such as improving transparency, quality, agility, efficiency and conformance.
applications of operation research in businessraaz kumar
1) Operations research is a quantitative approach to decision making based on the scientific method of problem solving. It involves modeling real-life situations as mathematical problems to arrive at optimal or near-optimal solutions.
2) The key steps in operations research problem solving are defining the problem, determining alternative solutions, evaluating alternatives using criteria, choosing the best alternative, implementing the chosen alternative, and evaluating the results.
3) Common techniques used in operations research include linear programming, transportation modeling, assignment modeling, and simulation methods like PERT/CPM. These techniques help optimize objectives while satisfying constraints.
Empirical research methods for software engineeringsarfraznawaz
This document outlines guidelines for empirical research methods in software engineering. It discusses case studies, experimental research, surveys, and post-mortem analysis. For each method, it provides examples and discusses how the method can be used to study software engineering problems. It also lists detailed guidelines for different aspects of empirical research, such as experimental context and design, data collection, analysis, and presentation and interpretation of results. The goal of the guidelines is to improve the quality and rigor of empirical studies in software engineering.
A Comparative Study between Agile Methods of Software DevelopmentFelipe Alves
The document presents an extension of a comparative study between agile software development methods. It analyzes methods such as XP, Scrum, Crystal, FDD, DSDM, ASD, Kanban, Agile Modeling, OpenUP, and AgileUP based on key points, main features, and limitations. The study aims to help organizations choosing the most suitable agile method for their software projects and to spread knowledge about these methods.
Operations research is a scientific approach to decision making that was developed during World War II and is now used widely in business and industry. It involves defining problems quantitatively and building mathematical models to represent real-world situations. These models are used to evaluate alternative solutions systematically and predict outcomes in order to optimize decisions. The process involves identifying problems, developing models, obtaining optimal solutions using techniques like linear programming, testing the model solutions, and implementing the best solution. Operations research helps organizations make more informed decisions using data, consider all options, and manage resources effectively.
Operations research is the application of analytical methods to help decision-makers choose optimal courses of action. It originated during World War II and uses mathematical techniques like linear programming, non-linear programming, and stochastic programming to optimize resource allocation. Linear programming involves maximizing or minimizing a linear objective function subject to linear constraints. Examples of linear programming problems include product mix problems, blending problems, and production scheduling problems.
These slides accompany the textbook "Software Engineering: A Practitioner's Approach" and were created by Roger Pressman. They cover various topics related to software engineering process models, including prescriptive models like the waterfall model and V-model, evolutionary models like prototyping, spiral development and concurrent development, and specific models like the Unified Process, Personal Software Process and Team Software Process. The slides also discuss process patterns, assessment methods and improving software processes.
Analysis of Feature Models using Alloy - A surveyAnjali Sreekumar
This is a presentation of the work on a survey related to Feature model analysis using Alloy presented during the FMSPLE workshop at Eindhoven University of Technology on 3rd April 2016.
This document discusses metrics that can be used to measure software processes and projects. It begins by explaining why measurement is important for assessing project status, tracking risks, finding problem areas, and improving processes. It then provides examples of different types of metrics that can be measured, including process metrics related to quality, productivity, and reuse, as well as project metrics related to inputs, outputs, results, effort, defects, and size. Guidelines are also given for establishing an effective metrics program.
This document outlines and compares two papers on task scheduling for software development projects. For the first paper, it summarizes the analytical method used to model tasks as a graph and schedule them across global teams to minimize project time. For the second paper, it summarizes the simulation model used to analyze how different scheduling strategies affect project progress and completion time. It then compares the two papers, noting that the first generates a scheduling policy while the second takes a policy as input, and that the second provides more insight but was only tested on simulated data.
Similar to 130411 francis palma - detection of process antipatterns -- a bpel perspective (20)
The document discusses the history and current state of software engineering and its application to IoT systems. It notes that 50 years after the earliest software projects, issues still include cost overruns, property damage, risks to life and death, and challenges ensuring quality. For IoT, fragmentation across hardware, software, APIs and standards poses significant problems. The document proposes that research into IoT software engineering could help address these issues through approaches like developing software to run across diverse IoT platforms, and automatically miniaturizing software through techniques like multi-objective optimization to suit different IoT device capabilities.
1) Issue trackers are often used to track more than just bugs, including features, enhancements, and refactoring work.
2) A manual analysis found that nearly half of issues labeled as "bugs" in issue trackers were actually not bugs.
3) Relying on issue tracker labels alone can introduce significant errors into datasets used for tasks like bug prediction and severity estimation. More work is needed to clean noisy and unreliable data.
The document discusses how to derive dependency structures for legacy J2EE applications. It proposes analyzing all application tiers together using a language-independent model and parsing various artifacts. Configuration files and limited data flow analysis are used to understand dependencies. Container dependencies are explicitly codified by studying technology specifications and codifying dependency rules to apply when certain code patterns are detected in applications. This allows completing an application's dependency graph.
The document discusses the state of practices of service identification in the industry for migrating legacy systems to service-oriented architectures (SOA). It finds that while service identification is seen as important, it remains primarily a manual process focused on identifying coarse-grained business services from source code and business processes. Wrapping and clustering functionalities are common techniques. Fully automating service identification is still challenging due to the need to understand complex legacy system dependencies. The document recommends service identification be business-driven and follow proven methodologies.
This document discusses techniques for testing advanced driver assistance systems (ADAS) through physics-based simulation. It faces challenges due to the large, complex, and multidimensional test input space as well as the computational expense of simulation. The document proposes using a genetic algorithm guided by decision trees to more efficiently search for critical test cases. Classification trees are built to partition the input space into homogeneous regions in order to better guide the selection and generation of test inputs toward more critical areas.
The document reports on the findings of a survey of 45 industrial practitioners on their experiences with legacy-to-SOA migrations. The key findings include: 1) Practitioners migrate legacy systems implemented in Cobol and Java to reduce maintenance costs and improve flexibility/interoperability; 2) Identifying services is an important step but is mostly manual and business-driven; 3) The most used techniques are functionality clustering and wrapping; 4) Desired service qualities are reusability, granularity and loose coupling; 5) Identified services prioritize domain-specific over technical services; 6) RESTful services are most targeted technology.
The document investigates the impact of linguistic anti-patterns (LAs) on program comprehension. It defines LAs as bad naming, documentation, and implementation practices. A study was conducted involving 92 students assessing programs with and without LAs. The study found that LAs negatively impact understandability by increasing time and reducing correctness. Certain LAs like A2, B4, and D1 had a stronger negative effect than others like E1. The study also found that providing knowledge about LAs can help mitigate their impact by making programs easier and faster to comprehend.
The document discusses research on identifying and analyzing the impact of patterns on the quality of multi-language systems. The objectives are to collect and categorize sets of programming languages used together, detect patterns in multi-language programs to track bugs and provide best practices, and study how patterns impact quality. The contributions will be a catalog of multi-language patterns and defects, a detection tool, and analysis of patterns' effects on quality attributes. Current work includes reviewing literature on language combinations and patterns to provide recommendations for high-quality multi-language development.
This document discusses research on change impact analysis in multi-language systems. It begins by outlining recommendations for best practices when using JNI, such as passing primitive types, minimizing calls between native and Java code, and properly handling strings. It then describes a qualitative analysis of JNI usage that identified common practices and issues. Finally, it proposes future work to survey developers on applying recommendations to facilitate change impact analysis in multi-language systems.
The document summarizes a recommendation system that suggests software processes for video game projects based on similarities to past projects. The system analyzes over 100 postmortems from previous games to build a database of development processes and project contexts. It uses principal component analysis to identify similar past projects and recommends a process by combining elements from similar projects' processes. The system was evaluated both quantitatively based on correctness and coverage metrics and qualitatively through surveys and a case study with a developer team.
Will io t trigger the next software crisisPtidej Team
This document discusses how the rise of the Internet of Things (IoT) could trigger a new software crisis due to issues like fragmentation, complexity, and lack of standards. It provides a brief history of software engineering challenges over the past 50 years such as cost overruns, safety issues, and prioritizing productivity over quality. The document then examines how these same problems are emerging in the IoT context today. It argues that IoT software engineering practices need to address issues like device software, cloud/app development, and privacy in order to avoid a major crisis.
This document discusses theories related to software design patterns. It notes that while design patterns are commonly used, there is a need for more research on how they impact software quality. The document proposes several areas for developing theories, including systematically categorizing existing patterns based on underlying principles, combining principles to identify new patterns, and developing theories of patterns from developer behavior and for building software systems. Formalizing patterns and identifying their relationships could help teaching and understanding of patterns.
Laleh M. Eshkevari defended her Ph.D dissertation on developing techniques for the automatic detection and classification of identifier renamings in software projects. Her dissertation outlined a taxonomy of renamings, described approaches for renaming detection based on line mapping, entity mapping and data flow analysis, and discussed methods for classifying renamings based on their form and semantic changes. Evaluation of the approaches on several open source projects showed high precision and recall for renaming detection and identified trends in how renamings are used in practice.
1) The document analyzes the co-occurrence of code smells like anti-patterns and clones in software systems and their impact on fault-proneness.
2) It finds that over 50% of classes with anti-patterns also have clones, and 59-78% of classes with clones also participate in anti-patterns.
3) Classes with both anti-patterns and clones are significantly more fault-prone than other classes, with the risk of faults being at least 7 times higher in one system studied.
Trustrace is an approach that uses software repository links like SVN commits to improve the trust in automatically recovered traceability links between requirements and code. It calculates an initial trust value for links based on IR techniques like VSM, and then reweights the links based on additional information from the software repository. An evaluation on two case studies found Trustrace improved precision over VSM alone and showed no significant difference in recall, supporting the hypothesis that Trustrace can improve link recovery accuracy over IR-only approaches.
The document presents a taxonomy called ProMeTA for classifying program metamodels used in program reverse engineering. ProMeTA defines characteristics such as target language, abstraction level, meta-language, and more to classify popular metamodels like AST, KDM, FAMIX. The taxonomy aims to provide a comprehensive guide for researchers and practitioners to select, design, and communicate metamodels. The paper also analyzes existing metamodels according to the ProMeTA taxonomy and identifies gaps to guide future metamodel development.
This document describes a controlled, multiple case study of software evolution and defects from industrial projects. It details the data sources used, including source code repositories, issue tracking databases, and interviews. Metrics such as code smells, size, effort, and defects were collected. Programming skills of developers were also measured. Code smell detection tools and custom scripts to analyze code changes were used to extract metrics on a variety of code issues and evolution over time. The data is available online for further analysis.
The document describes a study on detecting linguistic (anti)patterns in RESTful APIs. It presents an approach called DOLAR (Detection Of Linguistic Antipatterns in REST) that analyzes REST API URIs and detects antipatterns using heuristics-based algorithms. Experiments were conducted on 309 methods from 15 public REST APIs to test DOLAR's accuracy, the extensibility of the underlying SOFA framework, and the performance of detection algorithms. The results showed that 42% of methods exhibited contextualized resource names (a pattern) while 14% had contextless resource names (an antipattern), with detection taking under a second on average.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
HCL Notes and Domino License Cost Reduction in the World of DLAU
130411 francis palma - detection of process antipatterns -- a bpel perspective
1. Detection of Process Antipatterns:
An BPEL Perspective
Francis Palma1,2
Supervisors: Dr. Naouel Moha2 and Dr. Yann-Gaël Guéhéneuc1
April 12, 2013
1Ptidej
Team, École Polytechnique de Montréal, Canada
2Latece, Université du Québec à Montréal, Canada
2. Background
Background
• Service Oriented Architecture (SOA)
Motivation
Related Work
• Service-based systems (SBSs)
• Business Process Modeling Notation (BPMN)
• Business Process Execution Language (BPEL)
Approach
Experiments
• Service orchestration
• Design patterns and Antipatterns
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
2 of 19
5. Motivation
Background
Motivation
• Antipatterns:
- From wrong design decisions to poor solutions
• Poor solutions:
Related Work
Approach
- bad quality of service (QoS)
- less maintainability, evolvability etc.
• Detect antipatterns within processes
Experiments
• Improve design and QoS
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
3 of 19
6. Why BPEL ?
• BPEL processes are off-the-rack entities
Background
Motivation
Related Work
Approach
Experiments
• Antipatterns in models (BPMN) already got much attention
in the literature
• Transformation errors:
- business analysts create the processes, technical
developers implement the technology
- translation, adaptation, and–or implementation errors
• Early design errors:
- errors by analysts, eventually transferred to the process
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
4 of 19
8. Related Work (1/2)
Background
Motivation
Model Antipatterns:
- Onoda et al. (1999) catalog of five deadlock patterns
- Persson et al. (2006) and Stirna et al. (2009) provided six process patterns
and 13 process antipatterns
- Koehler and Vanhatalo (2007) described 14 structural antipatterns in
process models
- Trcka et al. (2009) formalized 9 process antipatterns using temporal logic
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
5 of 19
9. Related Work (1/2)
Background
Motivation
Related Work
Approach
Model Antipatterns:
- Onoda et al. (1999) catalog of five deadlock patterns
- Persson et al. (2006) and Stirna et al. (2009) provided six process patterns
and 13 process antipatterns
- Koehler and Vanhatalo (2007) described 14 structural antipatterns in
process models
- Trcka et al. (2009) formalized 9 process antipatterns using temporal logic
Detection of Model Antipatterns:
- Gruhn and Laue (2010) proposed a heuristic-based approach for
discovering problems in BPMs
- Laue and Awad (2010) visually represented process antipatterns
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
5 of 19
10. Related Work (1/2)
Background
Motivation
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Model Antipatterns:
- Onoda et al. (1999) catalog of five deadlock patterns
- Persson et al. (2006) and Stirna et al. (2009) provided six process patterns
and 13 process antipatterns
- Koehler and Vanhatalo (2007) described 14 structural antipatterns in
process models
- Trcka et al. (2009) formalized 9 process antipatterns using temporal logic
Detection of Model Antipatterns:
- Gruhn and Laue (2010) proposed a heuristic-based approach for
discovering problems in BPMs
- Laue and Awad (2010) visually represented process antipatterns
Process Patterns:
- Wohed et al. (2002) analyzed BPEL4WS based on workflow and
communication patterns
- Aalst et al. (2003) discussed 26 control flow, branching-synchronization,
and structural patterns
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
5 of 19
11. Related Work (2/2)
Identified gaps from the literature:
Background
Motivation
- Antipatterns and detection approaches were considered
only for BPMN models
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
6 of 19
12. Related Work (2/2)
Identified gaps from the literature:
Background
Motivation
Related Work
- Antipatterns and detection approaches were considered
only for BPMN models
- No other formal specifications for process antipatterns
except the one by Trcka et al. (2009)
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
6 of 19
13. Related Work (2/2)
Identified gaps from the literature:
Background
Motivation
Related Work
Approach
- Antipatterns and detection approaches were considered
only for BPMN models
- No other formal specifications for process antipatterns
except the one by Trcka et al. (2009)
- Various quality aspects (e.g., availability or response time
of Web services) were not considered
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
6 of 19
14. Related Work (2/2)
Identified gaps from the literature:
Background
Motivation
Related Work
Approach
Experiments
- Antipatterns and detection approaches were considered
only for BPMN models
- No other formal specifications for process antipatterns
except the one by Trcka et al. (2009)
- Various quality aspects (e.g., availability or response time
of Web services) were not considered
- No automatic detection approach for BPEL process
antipatterns until now
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
6 of 19
16. Solution towards detection
Background
Motivation
Related Work
Approach
• We propose to:
- specify process antipatterns using classical Rules of
Inference
- define a concrete approach
• We perform a small detection experiment
- two antipatterns, three example BPEL processes
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
7 of 19
18. Approach (2/5): Specify Rules
Background
Motivation
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
9 of 19
19. Approach (2/5): Specify Rules
Background
Motivation
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
9 of 19
20. Approach (3/5): Process Transform
Background
Motivation
• Process transformation (more abstract and simplified)
(a) from the original BPEL to a simplified BPEL
Related Work
Approach
Experiments
(b) from the simplified BPEL to a generic model
• Goal of this transformation is to ease:
- implementation of the rules
- further analysis of the processes
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
10 of 19
21. Approach (4/5): Process Transform
Background
Motivation
(a)
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
11 of 19
22. Approach (4/5): Process Transform
Background
Motivation
(a)
Related Work
Approach
Experiments
(b)
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
11 of 19
23. Approach (5/5): Detection
Background
Motivation
Related Work
Approach
Experiments
Conclusion
• The implementation of rules
• Applying implemented algorithms on transformed models
• Detection is now semi-automatic
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
12 of 19
25. Experiments (1/5): Input
travelProcess
3 Web services
7 I/O Var
auctionProcess
3 Web services
6 I/O Var
salesProcess
2 Web services
4 I/O Var
Background
Motivation
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
13 of 19
26. Experiments (2/5): Rule Specification
Background
Motivation
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
14 of 19
27. Experiments (2/5): Rule Specification
Background
Motivation
Related Work
Approach
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
14 of 19
30. Experiments (4/5): Results (cont.)
Background
Motivation
Related Work
Approach
salesProcess
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
16 of 19
31. Experiments (4/5): Results (cont.)
Background
travelProcess
Motivation
Related Work
Approach
salesProcess
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
16 of 19
32. Experiments (5/5): Threats to Validity
Background
External validity: Possibility to generalize the results
Motivation
for other large and realistic business processes
Related Work
Approach
Construct validity: Different engineers might define
rules differently
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
17 of 19
38. Future work
Background
Motivation
• Automate the approach
• Detect more process antipatterns
• Perform experiments on other large and complex
Related Work
Approach
business processes
• Analyze the processes dynamically
Experiments
Conclusion
April 12, 2013
Francis Palma | Detection of Process Antipatterns: An BPEL Perspective
19 of 19