Journal of Knowledge Management in Software Engineering
Software development is a collective, complex, and creative effort. Worldwide, there is an
increasing demand for IT projects and the demand for skilled and experienced software
developers is increasing as well. Shorter time-to-market, better quality and better productivity
present the increasing number of goals to be achieved. To meet these requirements, software
organisations have tried to better use one of their most important resources: the organisational
software engineering knowledge.
Historically, this knowledge has been stored on paper or in people’s minds. When a problem
arises, we look for experts across our work, relying on people we know, or we look for
documents. Unfortunately, paper has limited accessibility and it is difficult to update. On the
other hand, in a large organisation, it can be difficult to locate who knows what, and
knowledge in people’s minds is lost when individuals leave the company. Important
discussions are lost because they are not adequately recorded. Therefore, knowledge has to be
systematically collected, stored in the corporate memory, and shared across the organisation.
However, knowledge is more than simply a list of things we know or a collection of facts.
Therefore, knowledge management (KM) can play a vital role in encapsulating and spreading
software development knowledge and expertise.
In the context of software development, KM can be used to capture the knowledge and
experience generated during the software process. Reusing knowledge can prevent the
repetition of past failures and guide the solution of recurrent problems. Also, we must not
forget that collaboration is one of the most important knowledge sources for software
organisations. But, to be effective in the software development context, a KM system should
be integrated into the software development process.
Scope of Journal
The Journal cover all following major tracks but not limited to:
- Information processing and information management
- Information organization, taxonomies and ontology
- Knowledge creation, retention, sharing and transfer
- Knowledge discovery, data and text mining
- Knowledge management and innovations
- Knowledge management education
- Knowledge management tools and technologies
- Knowledge management measurements
- Knowledge professionals and leadership
- Learning organization and organizational learning
- Practical implementations of knowledge management
- Knowledge based intelligent systems in industry 4.0
- Ontology-based knowledge management for ambient intelligent systems.
- Knowledge based Ambient Intelligent Decision Support Systems
- Knowledge acquisition, representation, and reasoning for intelligent environments.
- Internet of Things (IoT) and knowledge management.
- Knowledge sharing among smart objects.
- Data Mining and Knowledge Discovery in smart environments.
- Secure and distributed knowledge management in pervasive environments.
- Knowledge Management in Self-Organizing Systems.
- Healthcare knowledge management.
- Artificial intelligence techniques for knowledge management.
- ambiguity in software development
- cleanroom software engineering
- formal methods of specification
- impact of CASE on software development life cycle
- object-oriented systems
- rapid prototyping
- Knowledge Engineering Methods and Practices
- distributed knowledge-based systems
- deductive database systems
- expert systems
- knowledge-based systems
- knowledge representations
- knowledge-based systems in language translation & processing
- logic programming
- reverse engineering in software design
- software and knowledge-ware maintenance
- Autonomic Computing and Agent-Based Systems
- Adaptive systems
- Agent architectures, ontologies, languages and protocols
- Agent-based learning and knowledge discovery
- Data Modelling, Mining and Data Analytics
- Data analytics modelling and algorithms
- Data mining methods, techniques and tools
- Data modelling, aggregation, integration and transformation
- Data visualization
- Web and text mining
- Agile methodology and practice
- Big data analytics application systems
- Big data application quality services
- Big data quality validation
- Cloud computing and Innovative cloud-based application systems
- Innovative sensing cloud and systems
- IOT and smart city application systems
- Large-scale cyber systems
- Mobile cloud computing
- Knowledge Systems and Engineering
- Knowledge acquisition
- Knowledge-based and expert system
- Knowledge engineering tools and techniques
- Knowledge modelling, integration, transformation, and management
- Knowledge representation and retrievals
- Knowledge visualization
- Time and knowledge management tools
- Uncertainty knowledge management
- Mobile Computing and Mobile System Engineering
- Innovative mobile applications
- Mobile app design and development
- Mobile system validation and test automation
- Pervasive computing
- SOA and Service-Oriented System
- Discovery and composition service level agreements
- Middleware for service based systems
- Runtime service management
- Semantic web
- Service-centric software engineering
- Service oriented architectures service
- Service oriented requirements engineering
- Software & System Quality of Service
- Quality assurance process, standards, and systems
- Soft computing
- Software and system testing methods
- Software dependability, reliability, scalabilitv
- Software safety systems
- Software test automation and tools
- Software & System Security
- Cloud, sensor cloud and mobile cloud security
- Encryption methods and tools
- Mobile app security and privacy
- Mobile system integrity, security and fault tolerance
- Security service systems
- Software and system security and privacy
- Enterprise software, middleware and tools
- Multimedia and hypermedia software engineering
- Process and workflow management
- Program understanding and system maintenance
- Reflection and metadata approaches
- Requirements engineering
- Software engineering techniques and production perspectives
- Software analysis, design and modelling
- Software domain modelling and analysis
- Software engineering case study and experience reports
- Software engineering decision support
- Software engineering tools and environments
- Software maintenance and evolution
- Agent-based software engineering
- Agile methodologies
- Artificial intelligence approaches to software engineering
- Aspect-based software engineering
- Automated software design and synthesis
- Automated software specification
- Component-based software engineering
- Computer-supported cooperative work
- Embedded and ubiquitous software engineering
- Empirical software engineering
- Reverse engineering
- Search-based software engineering
- Smart Learning and Innovative Education Systems
- Learning software design engineering
- Mobile enabled learning systems and tools
- Online learning systems
- Smart learning methods and environmentsv
The submitted paper must be formatted according to the Microsoft Word Template
Submitted technical papers must be maximum of 10 pages
including all figures, tables and references.
Authors are requested to submit their papers electronically using KnowMngSoftEng@gmail.com
Tentative Editorial Board
Dr. Radziah Mohamad, Associate Professor, Department of Software Engineering, Universiti Teknologi Malaysia (UTM ).
Dr. Imran Ghani, Associate Professor, Virginia Military Institute, USA.
Dr. Esma Aïmeur, Professor, Université de Montréal, Canada.
Dr. Mohammad Nazir Ahmad, Associate Professor, Universiti Kebangsaan Malaysia.
Dr. Malti Bansal, Assistant Professor, Delhi Technological University, India.
DR. Hamid, UVAS, Lahore, Pakistan.
DR. Muddasar Naseer, Lahore University, Pakistan.
Dr Rashid H Khokhar, School of Computing & Mathematics, Faculty of Business, Charles Sturt University (CSU), Australia.
Dr. Farrukh Zeshan, Assistant Professor, COMSATS University Islamabad (CUI), Lahore Campus, Pakistan.