Journal Information
Information and Software Technology (IST)
Impact Factor:
Call For Papers
Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal's scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include:

• Software management, quality and metrics,
• Software processes,
• Software architecture, modelling, specification, design and programming
• Functional and non-functional software requirements
• Software testing and verification & validation
• Empirical studies of all aspects of engineering and managing software development 
Last updated by Dou Sun in 2022-01-29
Special Issues
Special Issue on Application of causal modeling and inference methods in software engineering: Approaches, Challenges, State-of-the-Art and Prospects
Submission Date: 2023-09-30

This special issue provides an opportunity for researchers and practitioners to present theory, techniques, and applications related to the use of causal modelling and causal inference methods in software engineering. While much attention in the software engineering community has been given to the investigations based on correlation analysis techniques, advances in the field of causal modelling and inference remain to a large extent unexplored. The recent growth and development of data science practices and artificial intelligence has brought more attention to the issue of causality. The gold standard for estimating causal effects is to conduct controlled experiments with randomized controlled trials. However, when this is not possible (e.g., for practical or ethical reasons), causal effects must be estimated from observational data (i.e., data that were not generated in randomized controlled trials) or judged by subject matter experts. A major challenge with observational data, assuming all relevant variables have been captured, is that they may contain confounding correlations that can bias the estimation of causal effects. The field of causal inference has developed methods to reduce the impact of confounding factors and separate spurious correlations from causal effects. In the last decade, causal inference methods have begun to be applied in the field of software engineering. This is because (i) questions of causality are fundamental to obtaining actionable results, (ii) causal inference methods provide a way to evaluate the design of an empirical study in a principled way, such as deciding which elements to condition on and which would introduce bias, and (iii) these approaches also allow latent and unobserved variables to be handled in an elegant way. In addition, the use of causality within the software engineering process can be used to help the user locate defects, explain failures, enforce liability requirements, or even help resolve liability issues in software engineering. In this special issue, we intend to publish work studying causality and causal analysis methods in software engineering. We intend to keep the scope of the application use cases (i.e., software engineering) as broad as possible (for example, using the Software Engineering Body of Knowledge (SWEBOK) as a frame of reference). However, we will limit the type of analysis methods used to causal discovery and inference. We are particularly interested in methods that make explicit use of a graphical causal model. The types of work expected include (not limited to) proof of concept, benchmarks, empirical studies, lessons learned reports, literature reviews, etc. The special issue aims to collect primary and secondary studies on the adaptation, application and empirical evaluation of causal discovery and inference methods and techniques, including related methodologies, challenges and future prospects. Papers may focus on, but are not restricted to, the following themes: Causal analysis using observational software engineering data. Causal analysis based on judgment of software engineering human experts. Hybrid causal analysis methods, which combine the above-mentioned approaches. Causal structure discovery analysis. Counterfactual analysis. Causal debugging and explanations in software engineering.
Last updated by Dou Sun in 2023-06-11
Special Issue on Software Architecture for Quantum Computing Systems
Submission Date: 2023-10-30

Quantum computing systems have emerged as a technology to address computation-specific challenges. Several technology companies like IBM, Google, and Microsoft have invested in the research and development of quantum systems. Lately, the software engineering community has started focusing on developing techniques and tools for quantum software models, algorithmic specifications, and simulation evaluations to benefit from quantum hardware. The architecture of software-intensive systems aims to abstract complex and implementation-specific details in terms of architectural components and connectors to represent overall system design. Presently, Quantum software systems primarily focused on producing quantum source code while overlooking overall quantum software design and architecture. Such systems are often prone to bugs. The role of software architecture in quantum software engineering is pivotal to organize the overall requirements, which lead to software design, coding, validation, and deployment, all facilitated with architectural notations. Software architecture for quantum computing systems empower the role of software practitioners to model, implement and deploy the quantum software system. This special issue aims to provide a venue to discuss various aspects of quantum software architecture, existing challenges, and potential opportunities. This special issue will bring together researchers and practitioners from academia and industry to present empirical studies and discuss the issues related to software architecture design for quantum computing systems. This special issue will seek submissions reporting original, unpublished research on software architecture for quantum computing systems covering any aspect of experimental, empirical, and evidence-based software engineering, for example, quantitative and qualitative methods for empirical evaluation of quantum computing architecture techniques, processes, methods, tools, and best practices. This special issue welcomes the submission form industry experts and research community on software architecture for quantum computing systems. Suggested Topics Potential topics include but are not limited to the following: Topics of interest for the special issue include (but are not limited to) the themes as follows: State-of-the-art and state-of-the-practice in quantum software architecture Systematic literature reviews and mapping studies on quantum software architecture Controlled experiments and quasi-experiments on software architecture for quantum computing systems. Case studies, surveys, observational studies, Delphi studies, and field studies on software architecture for quantum computing systems. Evaluation and quality aspect of software architecture for quantum computing systems. Frameworks and architecture description languages for quantum computing systems. Best practices and lessons learned in software architecture for quantum computing systems. Software design and architecture. Design and architecture patterns. Validation and simulation. Industrial findings and experience reports of developing quantum software Architectural patterns and styles Prototypes and tool support for architecture Development environments, frameworks and tools Manuscript submission information: Important Dates Deadline for submission: 30 October 2023 Notification to authors: 90 days (3 months)
Last updated by Dou Sun in 2023-01-23
Special Issue on Reengineering Legacy Software Systems to Blockchain Platforms
Submission Date: 2023-11-30

Legacy software systems (or on-premises software) with billion lines of code, amongst others, are the critical assets of business enterprises. These systems provide a backbone to accomplish various 24/7 online digital services such as shopping, ordering products, shipping, transferring money, and lodging tax return. While our growing reliance on legacy systems is increased to keep business continuity, they become less sustainable, more complicated for maintenance, and venerable to security attacks. While many scientific and practical areas have shown increasing interest in reaping the benefits of blockchain technology to empower the security and reliability of software systems, legacy systems, however, may not be able to utilise the advantages of blockchain technologies at the first place. Such systems may not support blockchain design thinking such as decentralised architecture, data immutability, effective gas consumption, limited scalability, consensus-based transaction processing to name a few. As enabling legacy systems to utilise blockchain technologies may vary greatly between systems and organizations across different application domains, there is a need for advanced techniques, tools, processes, and design principles that tie high-level enterprise requirements and low level implementation (e.g., programming models, Bitcoin scripting languages) together in enabling legacy systems to leverage blockchain platforms. Otherwise, the resultant blockchain enabled system will be vulnerable to security issues, erroneous, and costly to maintain. Many research challenges and opportunities remain to be addressed and surmounted in the secured integration and transformation of legacy systems to run on blockchain platforms in a cost-effective way, while still being integrated with backend systems. This special issue aims at making a synergy between research and practice that are focused on migrating legacy software to blockchain platforms, highlighting the need for novel and high-quality research in migrating systems to blockchain platforms, and appraising the current and future impact of blockchain enabled systems. The issue is open to all manuscripts drawing results based on qualitative, quantitative, empirical, and design science research approaches that make significant contributions to tackling real-world challenges confronted by project managers, software practitioners, digital consulting firms, and researchers in reengineering systems to blockchain platforms. Suggested Topics The topics of interest include but are not limited to the following. Survey based studies and literature review on blockchain migration Data and legal security and privacy issues on the blockchain migration Industrial findings and experience reports of reengineering/migrating systems to smart contracts Empirical studies and metrics on legacy system migration to blockchain platforms Legacy data migration to blockchain Integrating legacy systems and on-premises infrastructure to multiple blockchains Architectural patterns and styles for blockchain enabled legacy systems Legacy code refactoring and architecture transformation to (Ethereum) smart contracts Value driven requirements engineering for system transformation to smart contracts Blockchain-based NFT casting models for legacy systems and data Reengineering processes and method tailoring for transformation to smart contracts Legacy system migration to open source blockchain platforms
Last updated by Dou Sun in 2023-06-11
Special Issue on Software Production
Submission Date: 2023-11-30

Topics for the Special Issue Software Platforms, Ecosystems, and App Stores – open digital platforms; open innovation; app store architectures; application programming interface (API) architectures; digital and data platforms; software ecosystems health; ecosystem orchestration and governance; app economy; actors and network analysis; incentives and ecosystem-based business models. Research Methods in Software Production - Case studies; surveys and questionnaires; experiments; structured literature surveys; empiricism; evaluation; validity; grounded theory; quantitative research; repository mining, app store mining. Responsible Software – responsible software for digital transformation; responsible enterprise; enterprise modeling; information and communication technology; sustainability; socio-environmental auditing; sustainability of software products; sustainable software development; responsible management in software development and operation; undesirable/unintended use of software business; societal issues of current and emerging software business developments. Software Business Development – developing and introducing new digital transformation business models; business modeling for software products and services; effective business model change and improvement; economics of software companies; mergers and acquisitions; internationalization, outsourcing and other strategies for realizing new business models. Legal Issues – legal software-related implications for digital transformation, licensing, intellectual property and patents aspects and other legal aspects associated with software business, cybersecurity, privacy, and security. Software Startups – environment success factors; entrepreneurial process in software development; novel software startup processes; disruptive innovation and adoption; establishing new competence; risk management; managing startup growth. Citizen Development – low-code/no-code (LCNC) platforms and initiatives for digital transformation; empowering non-technical users; role of citizen developers; new business models; governance; business processes; hyper-agile development; LCNC analytics; barriers, challenges, and enablers for citizen development. Engineering and Management – software product management; project portfolio management; life-cycle perspective; continuous delivery; agile development; technical debt; platform governance; digital platforms; value co-creation. Human Factors – education and training; human value morale, ethics and beliefs; human-centered design; ethical software engineering; artificial intelligence (AI) risks and ethics; transparency; user interaction with algorithms; algorithm aversion; algorithm appreciation. Emerging Industry Trends – emergence of new software business technologies (e.g., AI, big-data analytics, blockchain, cloud computing) and infrastructures (e.g., digital platforms and ecosystems); novel value-creation processes and work practices (e.g., IT consumerization, resource sharing); games and gamification; software business education; disruptive trends in software business; the future of software business. Computer Games - Game development methodologies and tools; game engines and middleware; Game economics and virtual economies; In-game monetization, pricing, and virtual goods markets; Game education and training; game development education, game-based learning, and use of games in training and simulation. Software Production Education - Project-based learning; working on real-world software development projects; Code reviews; critical thinking skills; Self-paced learning; Hands-on workshops, hackathons and coding challenges; Case studies. eHealth Software - Usability and user experience of eHealth software; Data security and privacy in eHealth software; Telemedicine and remote patient monitoring; Artificial intelligence and machine learning in eHealth software; Impact of eHealth software on healthcare outcomes; eHealth software for chronic disease management; Adoption and diffusion of eHealth software in healthcare organizations.
Last updated by Dou Sun in 2023-06-11
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