Software development processes need to have an integrated environment that fulfills specific
developer needs. In this context, this paper describes the modeling approach SAGM ((Similarity
for Adaptive Guidance Model) that provides adaptive recursive guidance for software
processes, and specifically tailored regarding the profile of developers. A profile is defined from
a model of developers, through their roles, their qualifications, and through the relationships
between the context of the current activity and the model of the activities. This approach
presents a similarity measure that evaluates the similarities between the profiles created from
the model of developers and those of the development team involved in the execution of a
software process. This is to identify the profiles classification and to deduce the appropriate
type of assistance (that can be corrective, constructive or specific) to developers.
Adaptive guidance model based similarity for software process development pro...ijseajournal
This paper describes a modeling approach SAGM (Similarity for Adaptive Guidance Model) that provides
adaptive and recursive guidance for software process development. This approach, in accordance to
developer needs, allows specific tailored guidance regarding the profile of developers. A profile is partially
or completely defined from a model of developers, through their roles, their qualifications, and through the
relationships between the context of the current activity and the model of the defined activities. This
approach aims to define the generic profile of development context and a similarity measure that evaluates
the similarities between the profiles created from the model of developers and those of the development
team involved in the execution of a software process. This is to identify the profiles classification and to
deduce the appropriate type of assistance to developers (that can be corrective, constructive or specific).
This summary provides an overview of the key concepts discussed in the document:
1. The document discusses various object-oriented analysis and design concepts including use case modeling, the Unified Modeling Language (UML), activity diagrams, associations, aggregation, and composition.
2. It provides descriptions and examples of these concepts, such as defining use cases, actors, and use case diagrams. Activity diagrams are described as showing workflows and processes.
3. The document also discusses UML notation for modeling associations, including binary and ternary associations, and modeling cardinality ratios between associated classes.
Introduction to Object orientation , Modeling as a Design Technique Modeling ...DhwaniDesai21
This document provides an overview of object-oriented modeling concepts including the class model, state model, and interaction model. It discusses modeling as a design technique and introduces key concepts like abstraction. It then describes the three models in more detail providing examples of each. The class model represents static structure, the state model represents dynamic behavior over time, and the interaction model represents collaboration between objects.
This document discusses object-oriented concepts and modeling. It begins by listing three textbooks on these topics. It then provides an overview of object-oriented concepts like objects, classes, inheritance, polymorphism, and encapsulation. It describes the stages of object-oriented analysis, design and implementation. It discusses the three main models used in object-oriented modeling: class models, state models, and interaction models. Finally, it covers object-oriented themes like abstraction, encapsulation, and polymorphism and the purposes of modeling.
Unit 1( modelling concepts & class modeling)Manoj Reddy
The document discusses object-oriented modeling and design. It covers key concepts like classes, objects, inheritance, polymorphism, and encapsulation. It also discusses the Unified Modeling Language (UML) which provides standard notation for visualizing, specifying, constructing, and documenting models. The document is a lecture on object-oriented concepts for students to understand modeling using classes, objects, and relationships.
CS8592 Object Oriented Analysis & Design - UNIT Ipkaviya
This document provides an introduction to Object Oriented Analysis and Design (OOAD) and the Unified Process (UP). It discusses key OOAD concepts like objects, classes, inheritance, polymorphism, and encapsulation. It then describes the Unified Process, an iterative software development approach that involves inception, elaboration, construction, and transition phases. Each phase includes requirements analysis, design, implementation, and testing activities. The document also discusses the Unified Modeling Language (UML) and diagrams used in OOAD like use case diagrams, class diagrams, and sequence diagrams.
Adaptive guidance model based similarity for software process development pro...ijseajournal
This paper describes a modeling approach SAGM (Similarity for Adaptive Guidance Model) that provides
adaptive and recursive guidance for software process development. This approach, in accordance to
developer needs, allows specific tailored guidance regarding the profile of developers. A profile is partially
or completely defined from a model of developers, through their roles, their qualifications, and through the
relationships between the context of the current activity and the model of the defined activities. This
approach aims to define the generic profile of development context and a similarity measure that evaluates
the similarities between the profiles created from the model of developers and those of the development
team involved in the execution of a software process. This is to identify the profiles classification and to
deduce the appropriate type of assistance to developers (that can be corrective, constructive or specific).
This summary provides an overview of the key concepts discussed in the document:
1. The document discusses various object-oriented analysis and design concepts including use case modeling, the Unified Modeling Language (UML), activity diagrams, associations, aggregation, and composition.
2. It provides descriptions and examples of these concepts, such as defining use cases, actors, and use case diagrams. Activity diagrams are described as showing workflows and processes.
3. The document also discusses UML notation for modeling associations, including binary and ternary associations, and modeling cardinality ratios between associated classes.
Introduction to Object orientation , Modeling as a Design Technique Modeling ...DhwaniDesai21
This document provides an overview of object-oriented modeling concepts including the class model, state model, and interaction model. It discusses modeling as a design technique and introduces key concepts like abstraction. It then describes the three models in more detail providing examples of each. The class model represents static structure, the state model represents dynamic behavior over time, and the interaction model represents collaboration between objects.
This document discusses object-oriented concepts and modeling. It begins by listing three textbooks on these topics. It then provides an overview of object-oriented concepts like objects, classes, inheritance, polymorphism, and encapsulation. It describes the stages of object-oriented analysis, design and implementation. It discusses the three main models used in object-oriented modeling: class models, state models, and interaction models. Finally, it covers object-oriented themes like abstraction, encapsulation, and polymorphism and the purposes of modeling.
Unit 1( modelling concepts & class modeling)Manoj Reddy
The document discusses object-oriented modeling and design. It covers key concepts like classes, objects, inheritance, polymorphism, and encapsulation. It also discusses the Unified Modeling Language (UML) which provides standard notation for visualizing, specifying, constructing, and documenting models. The document is a lecture on object-oriented concepts for students to understand modeling using classes, objects, and relationships.
CS8592 Object Oriented Analysis & Design - UNIT Ipkaviya
This document provides an introduction to Object Oriented Analysis and Design (OOAD) and the Unified Process (UP). It discusses key OOAD concepts like objects, classes, inheritance, polymorphism, and encapsulation. It then describes the Unified Process, an iterative software development approach that involves inception, elaboration, construction, and transition phases. Each phase includes requirements analysis, design, implementation, and testing activities. The document also discusses the Unified Modeling Language (UML) and diagrams used in OOAD like use case diagrams, class diagrams, and sequence diagrams.
Formalization & data abstraction during use case modeling in object oriented ...csandit
This document discusses formalization and data abstraction during use case modeling in object-oriented analysis and design. It provides background on use case modeling and describes how data can be abstracted from use case steps. The document then presents a case study on an e-retail system to demonstrate modeling use cases, actors, and their relationships. It also discusses using activity diagrams to represent use case flows and the Object Constraint Language to add formalism and accuracy to data abstraction during analysis and design.
Course material from my Object-Oriented Development course.This presentation covers the analysis phases and focuses on class discovery, domain modeling, activity diagrams, and sequence diagrams.
The document discusses object-oriented modeling and design. It introduces object-oriented concepts like objects, classes, attributes, operations, associations, and aggregation. It explains how object-oriented analysis involves building models using these concepts to represent the structure and behavior of a system. The analysis model is then used during the design stage to create optimized implementation models before programming. Graphical notations are used to express the object-oriented models.
This paper deals with an adaptive guidance system for software processes. The aim is to define
an approach of process modeling with a recursive adaptation of the guidance. This one is
specifically adapted to the developer model through its role and its qualification, and in relation
to the activity model associated with the context of the activity in progress. This guidance system
is provided on the basis on the choice criteria like the suitable access mode, the assistance
function to be ensured and the object of assistance to be considered. The description of the suggested approach is done using the modeling formalism SPEM extended by new concepts and principles dedicated to the modeling of the adaptive guidance.
The document discusses object-oriented design and analysis. It covers key aspects of the design phase including identifying classes, class responsibilities, and relationships between classes. The purposes of the design phase are to gather information for implementation, reduce implementation time and cost, and be the most time-consuming phase. Results of design include text descriptions and diagrams depicting relationships, usage scenarios, and state changes. The document also discusses translating analysis concepts into design, including understanding quality attributes, constraints, and requirements.
Multiagent Based Methodologies have become an
important subject of research in advance Software Engineering.
Several methodologies have been proposed as, a theoretical
approach, to facilitate and support the development of complex
distributed systems. An important question when facing the
construction of Agent Applications is deciding which
methodology to follow. Trying to answer this question, a
framework with several criteria is applied in this paper for the
comparative analysis of existing multiagent system
methodologies. The results of the comparative over two of them,
conclude that those methodologies have not reached a sufficient
maturity level to be used by the software industry. The
framework has also proved its utility for the evaluation of any
kind of Multiagent Based Software Engineering Methodology
This document proposes optimizing service oriented architecture to support e-learning with adaptive and intelligent features. It discusses how adaptive learning refers to technologies that can dynamically recognize the role and profile of each learner and respond accordingly. It also discusses different adaptive learning approaches like macro, micro, and constructivist-collaborative approaches. Intelligent tutoring systems that utilize artificial intelligence techniques are also discussed. The proposal aims to make adaptive and intelligent e-learning features available as standard reusable services via an optimized service oriented architecture to enhance the overall system.
Object Oriented Analysis and Design with UML2 part1Haitham Raik
The document provides an overview of object-oriented analysis and design (OOA&D) with UML. It discusses key concepts like use cases, requirements analysis, UML diagrams, and architectural analysis. The presenter provides an agenda that covers OOA&D overview, UML overview, requirements overview, use cases overview, basic OO concepts, and architectural analysis.
Availability Assessment of Software Systems Architecture Using Formal ModelsEditor IJCATR
There has been a significant effort to analyze, design and implement the information systems to process the information and data, and solve various problems. On the one hand, complexity of the contemporary systems, and eye-catching increase in the variety and volume of information has led to great number of the components and elements, and more complex structure and organization of the information systems. On the other hand, it is necessary to develop the systems which meet all of the stakeholders' functional and non-functional requirements. Considering the fact that evaluation and assessment of the aforementioned requirements - prior to the design and implementation phases - will consume less time and reduce costs, the best time to measure the evaluable behavior of the system is when its software architecture is provided. One of the ways to evaluate the architecture of software is creation of an executable model of architecture.
The present research used availability assessment and took repair, maintenance and accident time parameters into consideration. Failures of software and hardware components have been considered in the architecture of software systems. To describe the architecture easily, the authors used Unified Modeling Language (UML). However, due to the informality of UML, they utilized Colored Petri Nets (CPN) for assessment too. Eventually, the researchers evaluated a CPN-based executable model of architecture through CPN-Tools.
CS8592 Object Oriented Analysis & Design - UNIT IV pkaviya
This document discusses object-oriented analysis and design patterns. It covers GRASP principles for assigning responsibilities to objects, such as information expert and controller. It also discusses design patterns including creational patterns like factory method and structural patterns like bridge and adapter. The document is focused on teaching object-oriented principles for designing reusable and well-structured code.
A Comparison of Traditional Simulation and MSAL (6-3-2015)Bob Garrett
This document compares traditional simulation approaches to the Model-Simulation-Analysis-Looping (MSAL) approach. It provides background information on system modeling and simulation basics, including conceptual models, simulation programs, sensitivity analysis, Monte Carlo methods, and simulation optimization. It then discusses risk and uncertainty, modeling systems of systems, and the current state of modeling and simulation in systems engineering. Finally, it introduces the MSAL approach, which uses graphs, analytics, and repeated simulation loops to address the increased complexity and uncertainty in systems of systems compared to traditional approaches. The MSAL approach aims to provide benefits like improved handling of uncertainty and complexity.
This document provides an overview of an Object-Oriented Modeling and Design course. It discusses key concepts like objects, classes, attributes, operations, encapsulation, and abstraction. It also describes the importance of modeling, different types of models (object, dynamic, functional), and object modeling notations like class diagrams and instance diagrams. The goal of the course is to understand object-oriented methodology and modeling software systems using the Unified Modeling Language (UML).
System Models in Software Engineering SE7koolkampus
The document discusses various types of system models used in requirements engineering including context models, behavioral models, data models, object models, and how CASE workbenches support system modeling. It describes behavioral models like data flow diagrams and state machine models, data models like entity-relationship diagrams, and object models using the Unified Modeling Language. CASE tools can support modeling through features like diagram editors, repositories, and code generation.
Wagner Farm Rescue Fund (WFRF) is a non-profit founded in 2002 to provide a humane alternative to slaughter for animals from Wagner Farm in Glenview, IL. WFRF had previously rescued 82 animals by purchasing them from Wagner Farm. However, in 2012, Wagner Farm ended its relationship with WFRF and now sells its animals for slaughter. WFRF's founder, Debbie Rubenstein, is seeking to reopen communications with Wagner Farm to continue providing humane alternatives for the animals.
A ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
Formalization & data abstraction during use case modeling in object oriented ...csandit
This document discusses formalization and data abstraction during use case modeling in object-oriented analysis and design. It provides background on use case modeling and describes how data can be abstracted from use case steps. The document then presents a case study on an e-retail system to demonstrate modeling use cases, actors, and their relationships. It also discusses using activity diagrams to represent use case flows and the Object Constraint Language to add formalism and accuracy to data abstraction during analysis and design.
Course material from my Object-Oriented Development course.This presentation covers the analysis phases and focuses on class discovery, domain modeling, activity diagrams, and sequence diagrams.
The document discusses object-oriented modeling and design. It introduces object-oriented concepts like objects, classes, attributes, operations, associations, and aggregation. It explains how object-oriented analysis involves building models using these concepts to represent the structure and behavior of a system. The analysis model is then used during the design stage to create optimized implementation models before programming. Graphical notations are used to express the object-oriented models.
This paper deals with an adaptive guidance system for software processes. The aim is to define
an approach of process modeling with a recursive adaptation of the guidance. This one is
specifically adapted to the developer model through its role and its qualification, and in relation
to the activity model associated with the context of the activity in progress. This guidance system
is provided on the basis on the choice criteria like the suitable access mode, the assistance
function to be ensured and the object of assistance to be considered. The description of the suggested approach is done using the modeling formalism SPEM extended by new concepts and principles dedicated to the modeling of the adaptive guidance.
The document discusses object-oriented design and analysis. It covers key aspects of the design phase including identifying classes, class responsibilities, and relationships between classes. The purposes of the design phase are to gather information for implementation, reduce implementation time and cost, and be the most time-consuming phase. Results of design include text descriptions and diagrams depicting relationships, usage scenarios, and state changes. The document also discusses translating analysis concepts into design, including understanding quality attributes, constraints, and requirements.
Multiagent Based Methodologies have become an
important subject of research in advance Software Engineering.
Several methodologies have been proposed as, a theoretical
approach, to facilitate and support the development of complex
distributed systems. An important question when facing the
construction of Agent Applications is deciding which
methodology to follow. Trying to answer this question, a
framework with several criteria is applied in this paper for the
comparative analysis of existing multiagent system
methodologies. The results of the comparative over two of them,
conclude that those methodologies have not reached a sufficient
maturity level to be used by the software industry. The
framework has also proved its utility for the evaluation of any
kind of Multiagent Based Software Engineering Methodology
This document proposes optimizing service oriented architecture to support e-learning with adaptive and intelligent features. It discusses how adaptive learning refers to technologies that can dynamically recognize the role and profile of each learner and respond accordingly. It also discusses different adaptive learning approaches like macro, micro, and constructivist-collaborative approaches. Intelligent tutoring systems that utilize artificial intelligence techniques are also discussed. The proposal aims to make adaptive and intelligent e-learning features available as standard reusable services via an optimized service oriented architecture to enhance the overall system.
Object Oriented Analysis and Design with UML2 part1Haitham Raik
The document provides an overview of object-oriented analysis and design (OOA&D) with UML. It discusses key concepts like use cases, requirements analysis, UML diagrams, and architectural analysis. The presenter provides an agenda that covers OOA&D overview, UML overview, requirements overview, use cases overview, basic OO concepts, and architectural analysis.
Availability Assessment of Software Systems Architecture Using Formal ModelsEditor IJCATR
There has been a significant effort to analyze, design and implement the information systems to process the information and data, and solve various problems. On the one hand, complexity of the contemporary systems, and eye-catching increase in the variety and volume of information has led to great number of the components and elements, and more complex structure and organization of the information systems. On the other hand, it is necessary to develop the systems which meet all of the stakeholders' functional and non-functional requirements. Considering the fact that evaluation and assessment of the aforementioned requirements - prior to the design and implementation phases - will consume less time and reduce costs, the best time to measure the evaluable behavior of the system is when its software architecture is provided. One of the ways to evaluate the architecture of software is creation of an executable model of architecture.
The present research used availability assessment and took repair, maintenance and accident time parameters into consideration. Failures of software and hardware components have been considered in the architecture of software systems. To describe the architecture easily, the authors used Unified Modeling Language (UML). However, due to the informality of UML, they utilized Colored Petri Nets (CPN) for assessment too. Eventually, the researchers evaluated a CPN-based executable model of architecture through CPN-Tools.
CS8592 Object Oriented Analysis & Design - UNIT IV pkaviya
This document discusses object-oriented analysis and design patterns. It covers GRASP principles for assigning responsibilities to objects, such as information expert and controller. It also discusses design patterns including creational patterns like factory method and structural patterns like bridge and adapter. The document is focused on teaching object-oriented principles for designing reusable and well-structured code.
A Comparison of Traditional Simulation and MSAL (6-3-2015)Bob Garrett
This document compares traditional simulation approaches to the Model-Simulation-Analysis-Looping (MSAL) approach. It provides background information on system modeling and simulation basics, including conceptual models, simulation programs, sensitivity analysis, Monte Carlo methods, and simulation optimization. It then discusses risk and uncertainty, modeling systems of systems, and the current state of modeling and simulation in systems engineering. Finally, it introduces the MSAL approach, which uses graphs, analytics, and repeated simulation loops to address the increased complexity and uncertainty in systems of systems compared to traditional approaches. The MSAL approach aims to provide benefits like improved handling of uncertainty and complexity.
This document provides an overview of an Object-Oriented Modeling and Design course. It discusses key concepts like objects, classes, attributes, operations, encapsulation, and abstraction. It also describes the importance of modeling, different types of models (object, dynamic, functional), and object modeling notations like class diagrams and instance diagrams. The goal of the course is to understand object-oriented methodology and modeling software systems using the Unified Modeling Language (UML).
System Models in Software Engineering SE7koolkampus
The document discusses various types of system models used in requirements engineering including context models, behavioral models, data models, object models, and how CASE workbenches support system modeling. It describes behavioral models like data flow diagrams and state machine models, data models like entity-relationship diagrams, and object models using the Unified Modeling Language. CASE tools can support modeling through features like diagram editors, repositories, and code generation.
Wagner Farm Rescue Fund (WFRF) is a non-profit founded in 2002 to provide a humane alternative to slaughter for animals from Wagner Farm in Glenview, IL. WFRF had previously rescued 82 animals by purchasing them from Wagner Farm. However, in 2012, Wagner Farm ended its relationship with WFRF and now sells its animals for slaughter. WFRF's founder, Debbie Rubenstein, is seeking to reopen communications with Wagner Farm to continue providing humane alternatives for the animals.
A ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
AUTO LANDING PROCESS FOR AUTONOMOUS FLYING ROBOT BY USING IMAGE PROCESSING BA...csandit
In today’s technological life, everyone is quite familiar with the importance of security
measures in our lives. So in this regard, many attempts have been made by researchers and one
of them is flying robots technology. One well-known usage of flying robot, perhaps, is its
capability in security and care measurements which made this device extremely practical, not
only for its unmanned movement, but also for the unique manoeuvre during flight over the
arbitrary areas. In this research, the automatic landing of a flying robot is discussed. The
system is based on the frequent interruptions that is sent from main microcontroller to camera
module in order to take images; these images have been distinguished by image processing
system based on edge detection, after analysing the image the system can tell whether or not to
land on the ground. This method shows better performance in terms of precision as well as
experimentally.
DESIGN, IMPLEMENT AND SIMULATE AN AGENT MOTION PLANNING ALGORITHM IN 2D AND 3...csandit
This article presents a computer simulated artificial intelligence (AI) agent that is able to move
and interact in 2D and 3D environments. The agent has two operating modes: Manual Mode
and Map or Autopilot mode. In the Manual mode the user has full control over the agent and
can move it in all possible directions depending on the environment. In addition to that, the
designed agent avoids hitting any obstacle by sensing them from a certain distance. The second
and most important mode is the Map mode, in which the user can create a custom map, assign a
starting and target location, and add predefined and sudden obstacles. The agent will then move
to the target location by finding the shortest path avoiding any collision with any obstacle
during the agent’s journey.
The article suggests as a solution, an algorithm that can help the agent to find the shortest path
to a predefined target location in a complex 3D environment, such as cities and mountains,
avoiding all predefined and sudden obstacles. It also avoids these obstacles during manual
control and moves the agent to a safe location automatically.
A SIMILARITY MEASURE FOR CATEGORIZING THE DEVELOPERS PROFILE IN A SOFTWARE PR...cscpconf
Software development processes need to have an integrated environment that fulfills specific
developer needs. In this context, this paper describes the modeling approach SAGM ((Similarity
for Adaptive Guidance Model) that provides adaptive recursive guidance for software
processes, and specifically tailored regarding the profile of developers. A profile is defined from
a model of developers, through their roles, their qualifications, and through the relationships
between the context of the current activity and the model of the activities. This approach
presents a similarity measure that evaluates the similarities between the profiles created from
the model of developers and those of the development team involved in the execution of a
software process. This is to identify the profiles classification and to deduce the appropriate
type of assistance (that can be corrective, constructive or specific) to developers.
Configuration of a Guidance Process for Software Process Modeling csandit
This document discusses the configuration of guidance processes for software process modeling. It proposes describing adaptive guidance processes in a "Y" structure with three dimensions: the development context, the adaptation form, and the provided guidance service. The development context considers the material/software platform, activity context, and developer profile. Adaptation forms include contextual, adaptive, and mixed guidance. Services include corrective, constructive, and automatic guidance. The document also presents a configuration management approach for guidance processes involving five interrelated elements: context description, guidance process, configuration basis, deployment cycle, and invocation basis. The goal is to automatically provide the most appropriate guidance process based on the current development context.
QUALITY ASSESSMENT MODEL OF THE ADAPTIVE GUIDANCEijseajournal
The need for adaptive guidance systems is now recognized for all software development processes. The new needs generated by the mobility context for software development led these guidance systems to both quality and ability adaptation to the possible variations of the development context. This paper deals with the adaptive guidance quality to satisfy the developer’s guidance needs. We propose a quality model to the adaptive guidance. This model offers a more detailed description of the quality factors of guidance service adaptation. This description aims to assess the quality level of each guidance adaptation factor and therefore the evaluation of the adaptive quality guidance service.
ADAPTIVE CONFIGURATION META-MODEL OF A GUIDANCE PROCESSijcsit
The current technology tend leads us to recognize the need for adaptive guidance process for all process of
software development. The new needs generated by the mobility context for software development led these
guidance processes to be adapted. In order to improve the performance of the deployed software
development, it is useful to manage the configuration of its evolving aspects. This paper deals with the
configuration management of guidance process or its ability to be adapted to specific development
contexts. The proposed adaptive configuration Meta-model is worked out on the basis of a Y description
for adaptive guidance process. This description focuses on three dimensions defined by the
material/software platform, the adaptation form and provided guidance service. Each dimension considers
several factors to develop a coherent configuration strategy and provide automatically the appropriate
guidance process to a current development context.
IMPLEMENTATION OF DYNAMIC COUPLING MEASUREMENT OF DISTRIBUTED OBJECT ORIENTED...IJCSEA Journal
This document summarizes a research paper that proposes a method for dynamically measuring coupling in distributed object-oriented software systems. The method involves three steps: instrumentation of the Java Virtual Machine to trace method calls, post-processing of the trace files to merge information, and calculation of coupling metrics based on the dynamic traces. The implementation results show that the proposed approach can effectively measure coupling metrics dynamically by accounting for polymorphism and dynamic binding, overcoming limitations of traditional static coupling analysis.
IMPLEMENTATION OF DYNAMIC COUPLING MEASUREMENT OF DISTRIBUTED OBJECT ORIENTED...IJCSEA Journal
Software metrics are increasingly playing a central role in the planning and control of software development projects. Coupling measures have important applications in software development and maintenance. Existing literature on software metrics is mainly focused on centralized systems, while work in the area of distributed systems, particularly in service-oriented systems, is scarce. Distributed systems with service oriented components are even more heterogeneous networking and execution environment. Traditional coupling measures take into account only “static” couplings. They do not account for “dynamic” couplings due to polymorphism and may significantly underestimate the complexity of software and misjudge the need for code inspection, testing and debugging. This is expected to result in poor predictive accuracy of the quality models in distributed Object Oriented systems that utilize static coupling measurements. In order to overcome these issues, we propose a hybrid model in Distributed Object Oriented Software for measure the coupling dynamically. In the proposed method, there are three steps
such as Instrumentation process, Post processing and Coupling measurement. Initially the instrumentation process is done. In this process the instrumented JVM that has been modified to trace method calls. During this process, three trace files are created namely .prf, .clp, .svp. In the second step, the information in these file are merged. At the end of this step, the merged detailed trace of each JVM contains pointers to the merged trace files of the other JVM such that the path of every remote call from the client to the server can be uniquely identified. Finally, the coupling metrics are measured dynamically. The implementation results show that the proposed system will effectively measure the coupling metrics dynamically.
This document provides an overview of object oriented analysis and design using the Unified Modeling Language (UML). It discusses key concepts in object oriented programming like classes, objects, encapsulation, inheritance and polymorphism. It also outlines the software development lifecycle and phases like requirements analysis, design, coding, testing and maintenance. Finally, it introduces UML and explains how use case diagrams can be used to model the user view of a system by defining actors and use cases.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
FORMALIZATION & DATA ABSTRACTION DURING USE CASE MODELING IN OBJECT ORIENTED ...cscpconf
In object oriented analysis and design, use cases represent the things of value that the system performs for its actors in UML and unified process. Use cases are not functions or features.
They allow us to get behavioral abstraction of the system to be. The purpose of the behavioral abstraction is to get to the heart of what a system must do, we must first focus on who (or what)
will use it, or be used by it. After we do this, we look at what the system must do for those users in order to do something useful. That is what exactly we expect from the use cases as the
behavioral abstraction. Apart from this fact use cases are the poor candidates for the data abstraction. Rather the do not have data abstraction. The main reason is it shows or describes
the sequence of events or actions performed by the actor or use case, it does not take data in to account. As we know in earlier stages of the development we believe in ‘what’ rather than
‘how’. ‘What’ does not need to include data whereas ‘how’ depicts the data. As use case moves around ‘what’ only we are not able to extract the data. So in order to incorporate data in use cases one must feel the need of data at the initial stages of the development. We have developed the technique to integrate data in to the uses cases. This paper is regarding our investigations to take care of data during early stages of the software development. The collected abstraction of data helps in the analysis and then assist in forming the attributes of the candidate classes. This makes sure that we will not miss any attribute that is required in the abstracted behavior using use cases. Formalization adds to the accuracy of the data abstraction. We have investigated object constraint language to perform better data abstraction during analysis & design in unified paradigm. In this paper we have presented our research regarding early stage data abstraction and its formalization.
1-SDLC - Development Models – Waterfall, Rapid Application Development, Agile...JOHNLEAK1
This document provides information about different types of data models:
1. Conceptual data models define entities, attributes, and relationships at a high level without technical details.
2. Logical data models build on conceptual models by adding more detail like data types but remain independent of specific databases.
3. Physical data models describe how the database will be implemented for a specific database system, including keys, constraints and other features.
Automatic customer review summarization using deep learningbased hybrid senti...IJECEIAES
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In the process of software architecture design, different decisions are made that have systemwide
impact. An important decision of design stage is the selection of a suitable software
architecture style. Lack of investigation on the quantitative impact of architecture styles on
software quality attributes is the main problem in using such styles. So, the use of architecture
styles in designing is based on the intuition of software developers. The aim of this research is
to quantify the impacts of architecture styles on software maintainability. In this study,
architecture styles are evaluated based on coupling, complexity and cohesion metrics and
ranked by analytic hierarchy process from maintainability viewpoint. The main contribution of
this paper is quantification and ranking of software architecture styles from the perspective of
maintainability quality attribute at stage of architectural style selection.
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Proceedings of the 2015 Industrial and Systems Engineering Res.docxwkyra78
Proceedings of the 2015 Industrial and Systems Engineering Research Conference
S. Cetinkaya and J. K. Ryan, eds.
Use of Symbolic Regression for Lean Six Sigma Projects
Daniel Moreno-Sanchez, MSc.
Jacobo Tijerina-Aguilera, MSc.
Universidad de Monterrey
San Pedro Garza Garcia, NL 66238, Mexico
Arlethe Yari Aguilar-Villarreal, MEng.
Universidad Autonoma de Nuevo Leon
San Nicolas de los Garza, NL 66451, Mexico
Abstract
Lean Six Sigma projects and the quality engineering profession have to deal with an extensive selection of tools
most of them requiring specialized training. The increased availability of standard statistical software motivates the
use of advanced data science techniques to identify relationships between potential causes and project metrics. In
these circumstances, Symbolic Regression has received increased attention from researchers and practitioners to
uncover the intrinsic relationships hidden within complex data without requiring specialized training for its
implementation. The objective of this paper is to evaluate the advantages and drawbacks of using computer assisted
Symbolic Regression within the Analyze phase of a Lean Six Sigma project. An application of this approach in a
service industry project is also presented.
Keywords
Symbolic Regression, Data Science, Lean Six Sigma
1. Introduction
Lean Six Sigma (LSS) has become a well-known hybrid methodology for quality and productivity improvement in
organizations. Its wide adoption in several industries has shaped Process Innovation and Operational Excellence
initiatives, enabling LSS to become a main topic in quality practitioner sites of interest [1], recognized Six Sigma
(SS) certification body of knowledge contents [2], and professional society conferences [3].
However LSS projects and the quality engineering profession have to deal with an extensive selection of tools most
of them requiring specialized training. To assist LSS practitioners it is common to categorize tools based on the
traditional DMAIC model which stands for Define, Measure, Analyze, Improve, and Control phases. Table 1
presents an overview of the main tools that are commonly used in each phase of a LSS project, allowing team
members to progressively develop an understanding between realizing each phase’s intent and how the selected
tools can contribute to that purpose.
This paper focuses on the Analyze phase where tools for statistical model building are most likely to be selected.
The increased availability of standard statistical software motivates the use of advanced data science techniques to
identify relationships between potential causes and project metrics. In these circumstances Symbolic Regression
(SR) has received increased attention from researchers and practitioners even though SR is still in an early stage of
commercial availability.
The objective of this paper is to evaluate the advantages and drawbacks o ...
EVALUATION OF THE SOFTWARE ARCHITECTURE STYLES FROM MAINTAINABILITY VIEWPOINTcscpconf
In the process of software architecture design, different decisions are made that have systemwide
impact. An important decision of design stage is the selection of a suitable software
architecture style. Lack of investigation on the quantitative impact of architecture styles on
software quality attributes is the main problem in using such styles. So, the use of architecture
styles in designing is based on the intuition of software developers. The aim of this research is
to quantify the impacts of architecture styles on software maintainability. In this study,
architecture styles are evaluated based on coupling, complexity and cohesion metrics and
ranked by analytic hierarchy process from maintainability viewpoint. The main contribution of
this paper is quantification and ranking of software architecture styles from the perspective of
maintainability quality attribute at stage of architectural style selection.
The document discusses object-oriented databases (OODBs). It states that choosing the right OODB architecture is crucial for performance and scalability, more so than with relational databases. With OODBs, the application architecture has a greater impact on performance compared to relational databases, as OODBs provide more direct access to persistent data. Consequently, the application architecture affects performance and scalability more than the choice of OODB.
The Impact of Software Complexity on Cost and Quality - A Comparative Analysi...ijseajournal
Early prediction of software quality is important for better software planning and controlling. In early
development phases, design complexity metrics are considered as useful indicators of software testing
effort and some quality attributes. Although many studies investigate the relationship between design
complexity and cost and quality, it is unclear what we have learned beyond the scope of individual studies.
This paper presented a systematic review on the influence of software complexity metrics on quality
attributes. We aggregated Spearman correlation coefficients from 59 different data sets from 57 primary
studies by a tailored meta-analysis approach. We found that fault proneness and maintainability are most
frequently investigated attributes. Chidamber & Kemerer metric suite is most frequently used but not all of
them are good quality attribute indicators. Moreover, the impact of these metrics is not different in
proprietary and open source projects. The result provides some implications for building quality model
across project type.
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Computer Science & Information Technology (CS & IT)
The basic guidance is defined as a global orientation core whatever the profiles of both the
activity and the developer.
The selection of the appropriate type of guidance is often more intuitive and not suitable.
To respond to these limits, several studies [2, 3, 5, 6] try to offer more flexibility in the language
of software process modeling and a more adapted base of support and control. This tendency aims
to define interventions of direct and adaptive assistance during the software process progress [7].
The following PSEEs included in the M1 level are as:
ADELE/APEL is based on a reactive database. It proposes a global assistance of proscriptive
type and automates part of the development process using triggers [8, 9].
RHODES/PBOOL+ uses an explicit description of a development process. The software
processes are modeled in PBOOL language [10]. The activities are associated to a guidance
system with various scenarios of possible realization.
ADDD/ALADYN provides process automation and control the impact in a concrete system. The
task hierarchy is used to organize the process descriptions, called policies. Several aspects are
grouped and treated in a policy. A policy can be instantiated for several tasks. The instantiated
triggers are rules of the form event-condition-action (ECA) and used to implement a reactive
behavior [11].
On the M2 level of Meta model, SPEM [12] introduced the concept of "Guidance" in the
"Managed Content" package by defining the stereotype "Guidance". According to SPEM,” the
Guidance is a describable element which provides additional information to define the
describable elements of a modeling. It also offers, through the stereotype “Guidance_kind”
different types of guidance such as: Template, Guidelines, Checklists, etc. ..
However, the selection of guidance types remains defined in a manual and in an intuitive way. It
depends on the experience and on the informal personality of the project manager. In addition, the
proposed guidance is not adaptive to the actor’s profile (role, qualifications and behavior).
In considering the principal limitations of PSEEs and essential characteristics of our approach as
the context adaptation aspect and the abstraction levels, a comparative table of the studied Meta
models is as follows:
Table 1. A Comparative table of the studied Meta models
Meta model
Criteria
ADELE /APEL
RHODES /
PBOOL+
ADDD / ALADYN
SPEM
Global guidance
core
Global
Global
Customized for
each task
Global
Human performer
profile oriented
guidance
Not adapted
Not adapted
Not adapted
Context
development
Guidance
Not adapted
Adapted
Adapted
Not adapted
Guidance types
Not invoked
associated with a
specific guide
system
Not invoked
considered
strategy Model
Intuitive
selection
3. Computer Science & Information Technology (CS & IT)
201
Explicit activity
abstraction
Explicit
abstraction
Implicit
abstraction
Implicit abstraction
Explicit
abstraction
Explicit task
abstraction
Implicit
abstraction
Not invoked
Explicit abstraction
Explicit
abstraction
Process Modeling
Language(PML)
APEL
With predefined
primitives
PBOOL+
With explicit
primitives
ALADYN
Not explicitly
mentioned
UML Profile
With explicit
primitive
The current tendency is that developers would like to have integrated environments that are
suitable to specific needs according to the role and the characteristics of each developer and
closed to the context of the underway task. However, the provided efforts to develop such
environments remain an insufficient contribution.
In this context, our conceptual model is based on the conventional reasoning of software
processes enriched by the "Adaptive Guidance" element which supervises the running of the
activities. It also provides adaptive support to the actor. It is described by the following figure:
Performer
Has for role
Role
Performs
Activity
Consume
Providedguidance
Controls
Responsible
Adaptive Guidance
Products
Product
Figure 1. : Conceptual Model with Adaptive Guidance
This tendency of adaptive guidance environments is yet a subject of much research focusing on
defining the concepts and objectives of process modeling software-based adaptive guidance [2, 3,
6].
For the sake of productivity and development time, our goal is to establish an optimal relationship
between profile of guidance type and the adapted developer’s profile to the context of
development. The context is defined by the activity model, the developer and team development
[2, 3, 13]. It is interesting to have an operator to assess the similarities within the handled data;
this operator is the similarity function [13, 14, 15, 16]. The numerical similarity measures turn out
to be extremely flexible employment. They are able to work on a broad spectrum of data types
and it is fairly easy to introduce into the calculation, (statistical approximations if the underlying
information is complex). In addition, similarities quantification by a continuous value implies that
it is always possible and easy to compare pairs of objects. This is not the case for the symbolic
similarity; treatment of numerical values is often done in an unsatisfactory way by rewriting these
values in symbolic form [14, 16].
Our approach operates in the optimization of profiles classes in relation to the semantics of data
manipulation. It defines a system for processing the similarity index and classification of
guidance profiles. For this, we have to design a classifier in order to facilitate the analysis of our
4. 202
Computer Science & Information Technology (CS & IT)
population and the type of assistance offered to appropriate developers involved in a software
process.
The second section summarizes the technique of assessing similarity. Section three presents our
approach (to model similarity with the software process), in addition to the implementation and
practical evaluation of our approach by giving algorithms and related results. The last section
concludes and presents future works perspectives.
2. SIMILARITY MEASURE
A similarity measure is defined on the set N (developers, documents, websites ...). Each object is
described by m features. Each feature can be present or absent in every object. A measure of
similarity, denoted by s, (between the elements of N is a specific application of NxN in R and
satisfying some properties [14, 15]).
Examples of the use of similarity techniques are described in cases of heterogeneous binary data
[17]. To transform a direct measure of similarity s into a dissimilarity measure d, we can apply
the following formula:
d(x, y) = smax – s(x, y).
Thus, each element x is associated to a binary vector (x1, x2, …, xm) such that:
1
xi =
If the feature i is present in the object x
0
Else
For i ∈{1,2,…. m}.
The m characteristics are considered of equal importance and each object has at least one feature
present. Note by:
a: The number of common characteristics between x and y.
b: The number of features present in x but not y.
c: The number of features present in y but not x.
d: The number of missing features in x and y.
Thus, the similarity measure s is given by the following formula:
We can deduce the measure of dissimilarity from the following formula:
Besides this general form, there are also other forms of similarity measures such as binary data
[14, 15, 17] as those given in table 2.
5. Computer Science & Information Technology (CS & IT)
203
Table 2. Different forms of similarity measures
To review and evaluate the effect of binary similarity measures, we will illustrate all the
similarity measures in an example as follows: Consider a set of 16 objects (A1, A2, . . . , A16),
each object has thirteen (13) features present or absent (C1, C2, ..., C13), all these data are
illustrated in the following table:
Table 3. Different forms of similarity measures
A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
A11
A12
A13
A14
A15
A16
C1
1
1
1
1
1
1
0
0
0
0
1
0
0
0
0
0
C2
0
0
0
0
0
0
1
1
1
1
0
0
0
0
0
0
C3
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
C4
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
C5
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
C6
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
C7
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
C8
0
0
0
0
0
0
0
0
0
1
0
0
1
1
1
0
C9
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
C10
0
0
0
0
1
1
1
1
0
1
1
1
1
0
0
0
C11
0
0
0
0
0
0
0
0
1
1
0
1
1
1
1
0
C12
1
0
0
1
1
1
1
0
0
0
0
0
0
0
0
0
C13
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
In applying the measures of similarities between some pairs of objects, we obtain a rate of
similarity on the similarity function used:
Table 4. A rate of similarity on the similarity function used
S (A1, A2)
Russel, Rao
Kendall, SokalMichener
Rogers, Tanimoto
Hamann
Sokal, Sneath
S (A1, A12)
S (A12, A16)
S (A1, A16)
0.23
0.00
0.23
0.00
0.92
0.86
0.85
0.96
0.31
0.18
-0.38
0.47
0.77
0.63
0.54
0.87
0.38
0.24
-0.23
0.56
The previous results give relations that may exist between different data from a sample objects
and deduce statistical information for describing more condensed key information contained in
these data. We also seek to classify data into different subgroups that are similar. According to
6. 204
Computer Science & Information Technology (CS & IT)
the area, the nature of this knowledge is different in data analysis; information will be taken into
account instead of a statistical nature.
3. SIMILARITIES IN THE SOFTWARE PROCESS
The proposed guidance system [3] addresses multiple views providing assistance to stakeholders.
Our approach aims to optimize the profile classes. To be adaptive to both the context and
identified needs, our model of adaptive guidance covers two levels of abstraction. It is based on a
set of task and activity model, the model developer and development team, as well as the
selection criteria specified by the mode of access for responding the objects of support by the
defined assistance interventions (Figure 2.). The instantiation of this system is through rules of
assistance detailed with the requirements for initiating appropriate actions to support a particular
context [2, 3, 5].
Controls
AL: Activity
Level
1
Is based on
Is based on
1
1
Activity Model
Is linked to
1..*
1
1
TL: Task
Level
ProvidedGuidance
Adaptive Guidance
1
+OwnedTaskPerf
ormer
*
Developer Model
+OwnedTask
*
Task Model
Team Model
Is linked to
1..*
1
ProcessRole
Responsibility
Qualification
Figure 2. : Adaptive Guidance Model.
3.1. The Adaptive guidance model
This assistance system is based on the major models: the activity model, the developer model and
the team development model.
a) The activity model: models the workflow, it is defined by:
• A hierarchical list of tasks,
• A mode of progression in the activity ensuring that all tasks can be performed under control
in a preset order established by the designer,
• A temporal mode of progression specifying deadlines for completion.
The aspects of the activity model are useful for the assistance system to provide assistance on
contextual growth in activity.
7. Computer Science & Information Technology (CS & IT)
205
b) The developer model: defines the specific properties of each user. It allows our model to
make adaptation according to these properties while maintaining the activity model. These
properties can be either static or dynamic.
• The static aspect refers to the user characteristics:
o his expertise in the field,
o his familiarity with the software process model or with the software process,
o his role in the activity.
• The dynamic aspect refers to the behavior of using the assistance system, the assistance
system must be interpreted during the use of the process or system software support, for
example :
o the fact to execute, to define or to complete resource of software process,
o the workload of an activity,
o his reaction to a message of support.
c) The development team model: development environments allow exchanges and collaborative
work. The assistance system can then construct a development team model that represents
elements of the team. Example: trace of the various activities of the team as well as different
interactions allow the developer to have a script about his own progress in the activity and the
progression of the team. The properties of this model can be static or dynamic order.
• The static dimension references skills and team performance in the field of collaboration
and distribution of task.
• The dynamic dimension deals with the behavior of the development team. It describes the
actions taken by the team during the course of software process.
These data constitute indications that can be interpreted on the use of the assistance by the
developer.
3.2. The assistance intervention
During the construction or interpretation of a software process model, the proposed model for
assistance allows the developer to choose various support functions, namely:
3.2.1. Controlling and taking corrective initiative: protect the user of his own initiatives when
they are inappropriate, inadequate initiative under progress.
3.2.2. Controlling and taking constructive initiative: the ability to take positive initiatives,
executing and combining the performance of operations without user intervention.
3.2.3. Specific assistance: analyze the impact projection to avoid deadlocks or delays.
3.3. The profiles categorization
For the sake of productivity and optimal lead time, we were led to define an effective process for
allocating appropriate guidance’s. This efficiency is based on the process of maximizing the
number of profiles classes to be considered in a development system. We will present our
analysis of similarity and classification of our population.
The conception of the processing system will be done through various algorithms. They process
both similarity index and hierarchical classification threshold for different profiles. To avoid an
important dissemination of similarity, this classification will be ordered by level of similarity
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index. This classification will serve as the basis for the selection and assignment of appropriate
types of assistance.
To reach an objective comparison between the profiles, an operator should be used for calculating
similarity based on the instantaneous evaluation of selected features and associated weights.
Despite the fact that this evaluation is not formal, it remains a crucial step for the classification.
For this, we use the notion of symbolic learning for instant evaluation of some attributes of the
profile as the behavior of the developer or development team.
3.3.1. Algorithm for computing Similarity Index
The evaluation of characteristics is based on the evolution of developer productivity. The weight
value of each feature indicates the degree of its importance. The approach used for the evaluation
of characteristics is based on ''COCOMO II” work [19, 20]. The table of weights could be refined
as soon as we have more data.
Consider two people profiles symbolized by:
X = (x1, x2, x3, ……………., xn)
Y = (y1, y2, y3, …………….., yn)
Each characteristic is related to a weight representing its impact in the degree of similarity and
symbolized by: Wi = (wi1, wi2, wi3, …………….., win)
Example: a family of two profiles is semantically described in table 4 and table 5. The semantics
evaluation and the weighting are determined by the project manager on an ongoing project [3, 19,
20].
Table 5. the profiles evaluation.
Features
Evaluation of profile 1
Evaluation of profile 2
High
Medium
Complexity level
Medium
Low
Activity Type
Tolerance zero
Margin Free
Role
Competence
Critical
High
Classic
Medium
Familiarity with Process
Software
Medium
Low
Model of
development
team
Model of developer
Model of
activity
Density of tasks in the activity
Behavior for assistance
Adequate
Skill Area Collaboration
High
Behavior for assistance
Acceptable
Acceptable
Medium
Adequate
To scan the semantics evaluation, we associate the weight corresponding to the consideration
according to each attribute.
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Table 6. Table of weights
W [1]
W [2]
W [3]
W [4]
W [5]
W [6]
W [7]
W [8]
W [9]
P2
P2
P3
P2
P2
P2
P2
P2
P4
With [i] ∈ [1, 5]. Where Pi represents the computing value
The algorithm processing is as follows: For any feature, whether it is identical to the profiles, we
increment the similarity index by the weight of this feature, otherwise, if the difference between
the two characteristics is < 1/2, we add half the weight of it, otherwise, we move to the next
feature.
The value 1/2 represents the average distance between two successive levels of an attribute
evaluation.
After all iterations, the similarity function obtained is formalized as follows:
S ( x , y ) =
A ( x , y )
∑ W [i ]
With:
X and Y represent the characteristics of the two profiles.
W [ ] represents the weighting of each feature.
• A (x, y) represents the sum of the weights between the two profiles, it is included between 0 and
ΣW[i].
•
•
The similarity function developed verifies the properties of a similarity measure.
∀x, y two profiles∈ N
If the profiles (x, y) are identical
Then A(x, y) = A(x, x) = ∑ W[i] with i= 1..9 ⇒ S(x, y) = A(x, y) / ∑ W[i] = 1
If the profiles (x, y) are totally different (the values are all above features > 1/2). Then for
any characteristic A (x, y) = 0 ⇒ S(x, y) = A(x, y) / ∑ W[i] = 0.
If any profiles are neither identical nor different then " It is appropriate to consider three
subsets possible through the following 03 cases":
This allowed us to affirm that:
∀ x, y two profiles ∈ N, The similarity function S(x, y) ∈[0, 1].
∀ x, y two profiles ∈ N, then S(x, x) = S(y, y) ≥ S(x, y).
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(1)
for features with a difference > 1/2
A (x, y) = 0
(2)
A (x, y) = Σ 1/2W [i] for the characteristics with a difference < 1/2
(3)
A (x, y) = Σ W [i]
for completely identical characteristics.
Finally for all characteristics:
A(x, y) = A(x, y) (1) + A(x, y) (2)
=
0 (1)
+ A(x, y) (3)
+ 1/2 ∑ W[i] (2) + ∑ W[i] (3)
Then
S(x, y) = A(x, y) / ∑ W[i] = (0(1) + 1/2∑ W[i] (2) + ∑ W[i] (3) ) / ( ∑ W[i] (1) +
Figure 3. : Algorithm for calculating similarity index.
Example: based on the assessing approach of the COCOMO model, the quantification of each
characteristic of a profile P is on the data range] 0, 2 [. It is usually done through three steps,
described by high, medium or low levels contribution, applying the following rules:
1: impact of middle order.
<1: positive impact.
>1: negative impact.
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209
Table 7. The profiles evaluation
Model of developer
Model of
development
profile 1
profile 2
profile 3
profile 4
Density of tasks in the
activity
1.65
1.20
1.10
1.65
Complexity level
1.00
0.60
1.00
1.00
Activity Type
Model of
activity
Features
1.70
1.20
1.20
1.70
Role
1.15
0.70
1.15
Competence
055
1.00
1.00
0.55
Familiarity with
Process Software
0.40
0.80
0.35
0.40
Behavior for assistance
0.40
0.60
0.40
0.40
Skill Area
Collaboration
0.70
0.70
0.70
0.70
Behavior for
assistance
0.95
0.10
0.95
0.95
1.60
The weight value of each feature indicates the degree of its importance. The project manager
associates the value correspondence table of weights, for example.
Table 8. Table of weights
W [1]
W [2]
W [3]
W [4]
W [5]
W [6]
W [7]
W [8]
W [9]
1
1
2
1
1
1
1
1
2
Based on our approach, the calculation of the similarity value between profiles is given by:
Table 9. The similarity values
S (P1, P2)
S (P1, P3)
S (P1, P4)
S (P2, P3)
S (P2, P4)
S (P3, P4)
Similarity
value
0.36
063
0.95
0.59
0.31
0.59
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3.3.2. Ascending Hierarchical Classification Algorithm for (addressing) and
similarity threshold
Classifying is grouping objects together according to similar criteria. There are two main families
of classification techniques:
The non-hierarchical classification or partitioning leads to the decomposition of the set of all
individuals in m disjoint sets or equivalence classes, the number of classes is fixed for m.
The hierarchical classification for a given accuracy, two individuals may be confused in the
same group, whereas in a higher level of accuracy, they will be separated and belong to two
different subgroups.
We opted for the hierarchical classification in increments of similarity that led to construct a
classification tree showing the transition profiles to the group through a series of consolidation.
The obtained classification is related to the variables selected to describe individuals, in our case
the developers. They are called the active variables, which will be based on the classification of
individuals. For this, and to avoid dispersion of profiles similarity, the user must set the level of
similarity describing each time the similarity values to consider and the level of precision
represents the similarity threshold to be applied on the profiles of guidance to classify.
Figure 4. : Ascending Hierarchical Classification Algorithm
3.3.3. Processing of the algorithm on a sample guidance profiles
We have the similarity threshold set and profiles guidance X1, X2, ………, Xn as input.
Our algorithm will create a square matrix of size (NXN) considering the number of profiles to
classify and index of similarity between profiles. See the following graph of similarity:
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211
Figure 5. : The graph of similarity
For a level of 0.2 and a minimum similarity threshold of 0.50, set initially by the user, which fixes
K to 0.80, the application of this algorithm is illustrated as follows:
Figure 6. : Illustration of the algorithm
The maximum value of similarity in this table is 0.9, it is the index of similarity between two
profiles P1 and P4, and these profiles will be aggregated to the first group C1.
Figure 7. : Classification (first set)
At this level, we find that the similarity indices are all below the minimum level of similarity of
the first set.
•
Since Kmin is less than K, we fix the next level, for this example, the new K will be set at
0.50. It repeats the previous steps until all the indices similarities are below the new
threshold of similarity.
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The maximum value of similarity in the new similarity matrix is 0.59, it is the index of
similarity between two profiles P2 and P3, and the two profiles will be aggregated to the first
group C2.
Figure 8. : The major classification
The application of our approach to similarity index and hierarchical clustering allowed us to
deduce of the initial profiles number, two major classes C1, C2. This will provide the basis for
optimal allocation of the appropriate guidance.
The guidance profile (GP) associated to each profile (Px) class is based on the following formula:
GP (Px) = ∑ Ai Wi / 2*∑ Wi avec i=1 to 9
With: Ai : the characteristic value and Wi : the associated weight. In our case, the guidance
profile of each class based on the smallest similarity value is given by:
Table 10. The associate guidance value
GP
C1
0.50
C2
0.37
It should be noted that the value of GP is ranged from 0 to 1. The range associated with each type
of guidance is defined by the project manager. For instance, if the range of the corrective
guidance is bounded between 0 and 0.40 and the range of the constructive guidance is between
0.41 and 0.70, we automatically associate a corrective guidance to the class C2 and a constructive
guidance to the class C1.
4. CONCLUSION
The system presented in this paper is an approach based on similarity to process guidance model in the
software process. It allows the profiles optimization, ie: classes presented through the semantics
description of handled data, the definition of a system for processing the similarity index and
classification of guidance profiles. The aim of this work is to facilitate the analysis of our
population using the adaptive development context involved in the execution of a software
process.
The system has been designed and implemented and its practical assessment seems to be
promising with a significant impact on the productivity of software process development.
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[19] Barry W. Boehm, Chris Abts, A. Winsor Brown, Sunita Chulani, Bradford K. Clark, Ellis Horowitz,
Ray Madachy, Donald J. Reifer, Bert Steece. 2009 Software Cost Estimation With COCOMO II.
Prentice Hall Edition, ISBN: 0137025769, 978013702576.
[20] Kirk, D., & MacDonell, S. 2009. A simulation framework to support software project (re)planning, in
Proceedings of the 35th Euromicro Software Engineering and Advanced Applications (SEAA)
Conference. Patras, Greece, IEEE Computer Society Press, pp.285-292.