Teaching Logic, from a Conceptual Viewpoint

This challenges and open problems paper discusses the role of software engineers when combining modeling with Search-Based Software Engineering (SBSE). With SBSE techniques increasingly providing insights into difficult software modeling problems, the role of the software engineer might be thought of as diminishing. However, given the crucial role of the model understanding in SBSE, we argue that the role of the software engineer will become more important through interactive SBSE, although exploiting this interaction remains a challenge for the field.

Logicians may want to consider the following statements: Engineers use mathematics in their Software Engineers do not use mathematics in their What should we conclude from these axioms? would conclude that Software Engineers are not Engineers. Others would conclude that the first statement must be incorrect and should read, All Engineers except Software Engineers use mathematics in their work. They would argue that mathematics is irrelevant in software development. Still others would conclude that, Some of the people who now call themselves Software Engineers are not qualified to do so. Although much of the mathematics developed by Computer Scientists is not very practical, this talk will argue that mathematics can and should play a central role in software engineering. It will show how classical engineering concepts can be applied in software development. 3rd IEEE International Conference on Formal Engineering Methods (ICFEM'00)

Empirical research is playing a significant role in software engineering (SE), and it has been applied to evaluate software artifacts and technologies. There have been a great number of empirical research articles published recently. There is also a large research community in empirical software engineering (ESE). In this paper, we identify both the overall landscape and detailed implementations of ESE, and investigate frequently applied empirical methods, targeted research purposes, used data sources, and applied data processing approaches and tools in ESE. The aim is to identify new trends and obtain interesting observations of empirical software engineering across different sub-fields of software engineering. We conduct a mapping study on 538 selected articles from January 2013 to November 2017, with four research questions. We observe that the trend of applying empirical methods in software engineering is continuously increasing and the most commonly applied methods are experiment, case study and survey. Moreover, open source projects are the most frequently used data sources. We also observe that most of researchers have paid attention to the validity and the possibility to replicate their studies. These observations are carefully analyzed and presented as carefully designed diagrams. We also reveal shortcomings and demanded knowledge/strategies in ESE and propose recommendations for researchers.

In response to the enormous annual dollar value spent on software, major emphasis is being placed within industry, Government and academia on the establishment of a rigorous discipline for the development of software—i. e., on the establishment of software engineering. This has significance in the realm of computer system simulation for two basic reasons: first, computer system simulation (any simulation for that matter) does itself involve the development of software; and second, computer system simulation is a technique/tool which can be applied to the discipline of software development. It will be the purpose of this workshop to discuss both the role of software engineering in computer system simulation and the role of computer system simulation in software engineering. Potential topics for discussion include, but are not limited to: a. Identification of software engineering b. Disciplines required for software engineering c. Software engineering in support of computer system simulation d. Computer system simulation as a tool in software engineering e. Recent progress in the direction of establishing the software engineering discipline.

Autistic individuals possess many unique skills that are beneficial to the workforce, especially the technology industry. However, research shows the unemployment rate is still considerably high among the autistic population compared to their neurotypical peers. It has been suggested that some autistic individuals may excel in software engineering roles. This paper presents a Multivocal Literature Review (MLR) to highlight the cognitive style and talents of individuals with Autism Spectrum Disorder (ASD). An analysis is carried out to fully understand the challenges faced by autistic individuals transitioning into the workplace while also highlighting the challenges faced in their day to day working life. These challenges include workplace environments as well as workplace ceremonies, including, for example, daily stand-up meetings. Many neurotypical software engineers, software engineering firms and academics can benefit from this information as they work towards a more inclusive and more effective software engineering community.

Software modules and components have always played a key role in software engineering, primarily as coarse-grained abstractions that embody the principle of information hiding. The fundamental contribution of component-based software engineering lies in making the black-box property a core requirement. In this paper we point out that this important notion tends to be neglected in component model analyses, and define the black-box property in terms of detailed characteristics which help to evaluate component models from this perspective. A survey of typical representatives of industrial and research component models shows that especially the former ones leave much to be desired, and the paper discusses the consequences of the weak aspects of their design.

An important role in software engineering is played by design notations. The Agent UML (AUML) notation for sequence diagrams has been widely used to capture the design of interactions between agents. However, AUML is not precisely defined, and there is very little in the way of tool support available. We argue that using a textual notation allows the notation to be precisely defined, and facilitates the development of tool support. We present a textual notation that we have developed, and describe a number of tools that support this notation. One of these tools is a 'renderer' which takes a textual AUML protocol and generates the standard graphical view. The layout of graphical elements in the generated graphical view is done automatically, using a layout algorithm which we present.

Conservative extensions of logical theories play an important role in software engineering. They provide a formal basis for program refinement and guarantee the integrity and transparency of modules and objects. This paper studies conservative extension ideas in the context of default logic. In particular, we define several alternative concepts, study their properties, and derive interconnections among the concepts. The main result provides an interesting distinctive feature of Reiter's default logic over some well-known variants.

The role of design pattern in the form of software metric and internal code architecture for object-oriented design plays a critical role in software en-gineering in terms of production cost efficiency. This paper discusses about code reusability that is a frequently exercised cost saving methodology in IT produc-tion. After reviewing existing literatures towards study on software metrics, we found that very few studies are witnessed to incline towards code reusability. Hence, we developed a simple analytical model that establishes relationship between the design components of standard software metric and code reusability using case studies of three software projects (Customer Relationship Management project, Supply Chain Management project, and Enterprise Relationship Management project). We also testify our proposal using stochastic based Markov model to find that proposed system can extract significant information of maximized values of code reusability with increasing level of uncertainties of software project methodologies.

Generative AI is revolutionizing software development by providing intelligent programming assistance, automating code generation, debugging, and refactoring. This paper evaluates the impact of AI-powered coding assistants, such as GitHub Copilot and OpenAI Codex, on developer productivity and code quality. We analyze AI’s effectiveness in improving coding efficiency, reducing errors, and maintaining best practices while addressing challenges such as bias, over-reliance, and security risks. Our study compares AI-assisted and human-written code using empirical data and controlled experiments across multiple programming languages. Key metrics, including defect rates, maintainability, and adherence to industry standards, are used to assess AI’s influence on code quality. Additionally, we explore its implications for software engineering workflows, education, and future advancements in AI-driven development. Findings reveal that AI-assisted coding enhances productivity but requires human oversight to mitigate risks like code vulnerabilities and inconsistencies. This research provides valuable insights into AI’s evolving role in software engineering, offering guidance for developers, researchers, and industry practitioners. DOI:https://doi.org/10.52783/pst.1668

Traditional waterfall or iterative waterfall methods are being used in software industries since its birth. In the last decade, time to market and flexibility in accommodating customer requirements became very important aspects in software project delivery. Keeping these two driving factors in mind, agile methodology became very popular, where continuous cycle of development and testing involving high customer interaction is promoted and this practice results in an early time to market. Hence, the quality aspects for these projects become very important in today’s context. Quality metrics play an important role in software engineering as they transform both the customer expectation and operational performance to metrics which can be measured, evaluated and compared. These metrics focus primarily on three aspects: the quality aspects of the product, the process which was followed during its development and some important project parameters. These metrics are influenced by different factors such as functionality, usability, reliability and portability. This research work focuses on literature survey on different quality metrics used in traditional software development, their applicability in agile method and finally searches for the right kind of quality metrics which can be used in agile projects.

Cloud-based technologies play an increasing role in software engineering because of their scalability, availability, and cost efficiency. However, due to privacy issues, developers and organizations still hesitate to host applications that handle sensitive data on servers of external cloud providers. Modern hardware extensions, such as Intel's Software Guard Extensions (SGX), are an attempt to provide confidentiality and integrity for applications running on external hardware. Still, enabling SGX in cloud systems poses new challenges considering scalability and flexibility. In this paper, we propose an approach to address these issues by employing concepts from the domain of Dynamic Software Product Lines (DSPLs). We aim to enable applications running on SGX-based cloud systems to be securely reconfigurable and extendable during runtime. In particular, we describe properties that such an approach should fulfill and discuss corresponding challenges.

The role of the design pattern in the form of software metric and internal code architecture for object-oriented design plays a critical role in software engineering regarding production cost efficiency. This paper discusses code reusability that is a frequently exercised cost saving methodology in IT production. After reviewing existing literature towards a study on software metrics, we found that very few studies are witnessed to incline towards code reusability. Hence, we developed a simple analytical model that establishes a relationship between the design components of standard software metric and code reusability using case studies of three software projects (Customer Relationship Management project, Supply Chain Management project, and Enterprise Relationship Management project). We also testify our proposal using stochastic based Markov model to find that proposed system can extract significant information of maximized values of code reusability with increasing level of uncertainties of software project methodologies.

It is well known that Zermelo-Fraenkel Set Theory (ZF), despite its usefulness as a foundational theory for mathematics, has two unwanted features: it cannot be written down explicitly due to its infinitely many axioms, and it has a countable model due to the Löwenheim–Skolem theorem. This paper presents the axioms one has to accept to get rid of these two features. For that matter, some twenty axioms are formulated in a non-classical first-order language with countably many constants: to this collection of axioms is associated a universe of discourse consisting of a class of objects, each of which is a set, and a class of arrows, each of which is a function. The axioms of ZF are derived from this finite axiom schema, and it is shown that it does not have a countable model—if it has a model at all, that is. Furthermore, the axioms of category theory are proven to hold: the present universe may therefore serve as an ontological basis for category theory. However, it has not been investigated whether any of the soundness and completeness properties hold for the present theory: the inevitable conclusion is therefore that only further research can establish whether the present results indeed constitute an advancement in the foundations of mathematics.

Mathematical logic and computer science have driven the design of a growing number of logics and related formalisms such as set theories and type theories. In response to this population explosion, logical frameworks have been developed as formal meta-languages in which to represent, structure, relate and reason about logics.Research on logical frameworks has diverged into separate communities, often with conflicting backgrounds and philosophies. In particular, two of the most important logical frameworks are the framework of institutions, from the area of model theory based on category theory, and the Edinburgh Logical Framework LF, from the area of proof theory based on dependent type theory. Even though their ultimate motivations overlap – for example in applications to software verification – they have fundamentally different perspectives on logic.In the current paper, we design a logical framework that integrates the frameworks of institutions and LF in a way that combines their complementary advantages while retaining the elegance of each of them. In particular, our framework takes a balanced approach between model theory and proof theory, and permits the representation of logics in a way that comprises all major ingredients of a logic: syntax, models, satisfaction, judgments and proofs. This provides a theoretical basis for the systematic study of logics in a comprehensive logical framework. Our framework has been applied to obtain a large library of structured and machine-verified encodings of logics and logic translations.