Meta-programming with names and necessity

The notion of program transformation is ubiquitous in programming language studies on interpreters, compilers, partial evaluators, etc. In order to implement a program transformation, we need to choose a representation in the meta language, that is, the programming language in which we construct programs, for representing object programs, that is, the programs in the object language on which the program transformation is to be performed. In practice, most representations chosen for typed object programs are typeless in the sense that the type of an object program cannot be reflected in the type of its representation. This is unsatisfactory as such typeless representations make it impossible to capture in the type system of the meta language various invariants in a program transformation that are related to the types of object programs. In this paper, we propose an approach to implementing program transformations that makes use of a first-order typeful program representation formed in Dependent ML (DML), where the type of an object program as well as the types of the free variables in the object program can be reflected in the type of the representation of the object program. We introduce some programming techniques needed to handle this typeful program representation, and then present an implementation of a CPS transform function where the relation between the type of an object program and that of its CPS transform is captured in the type system of DML. In a broader context, we claim to have taken a solid step along the line of research on constructing certifying compilers.

The notion of program transformation is ubiquitous in programming language studies on interpreters, compilers, partial evaluators, etc. In order to implement a program transformation, we need to choose a representation in the meta language, that is, the programming language in which we construct programs, for representing object programs, that is, the programs in the object language on which the program transformation is to be performed. In practice, most representations chosen for typed object programs are typeless in the sense that the type of an object program cannot be reflected in the type of its representation. This is unsatisfactory as such typeless representations make it impossible to capture in the type system of the meta language various invariants in a program transformation that are related to the types of object programs. In this paper, we propose an approach to implementing program transformations that makes use of a first-order typeful program representation formed in Dependent ML (DML), where the type of an object program as well as the types of the free variables in the object program can be reflected in the type of the representation of the object program. We introduce some programming techniques needed to handle this typeful program representation, and then present an implementation of a CPS transform function where the relation between the type of an object program and that of its CPS transform is captured in the type system of DML. In a broader context, we claim to have taken a solid step along the line of research on constructing certifying compilers.

Physical Literacy (PL) is a synthesis construct that ties together movement competencies with affective, motivational, and knowledge-based elements. It is considered foundational to the development of physical activity-related outcomes. Many diverse organizations and programs have embraced the concept and are implementing programs targeting each of those core elements. However, research has lagged behind its interest and adoption. Among the more prominent gaps is the design and evaluation of programs that aim to increase PL within special populations such as new immigrants or refugee youth. The Immigrant-focused Physical Literacy for Youth (IPLAY) program is a co-developed evidence-informed 8-week PL program designed for new immigrant and refugee youths who have recently settled in Calgary, Alberta, Canada. This study aims to use a convergent parallel mixed-methods approach to collect, analyse, and interpret quantitative and qualitative data in the evaluation and iteration of the IPLAY program. PL programs can be used as a tool to build confidence and physical competencies among newcomer youth. Furthermore, academic-community collaborations in the design and delivery of PL programs can help improve the access and interest for PL programs among newcomer youth. These partnerships are critical and timely considering the recent and upcoming waves of immigration to "arrival cities" across Canada.

In INTERLISP we find a number of embedded languages such as the iterative statement and the pattern match facility in the CLISP package, the editor and makefile languages and so forth. We will in this paper concentrate on the problem of extending the LISP language and discuss a method to compile such extensions. We propose the language to be implemented through an interpreter (written in LISP) and that compilation of statements in such an embedded language is done through partial evaluation. The interpreter is partially evaluated with respect to the actual statements, and an object program in LISP is obtained. This LISP code can further be compiled to machine code by the standard LISP compiler.We have implemented the iterative statement and a CLISP-like pattern matcher and used a program manipulation system to generate object programs in LISP. Comparisons will be made with the corresponding INTERLISP implementations, which use special purpose compilers in order to generate the LISP code.

To avoid compilation errors it is desirable to verify that a compiler is type correct —i.e., given well-typed source code, it always outputs well-typed target code. This can be done intrinsically by implementing it as a function in a dependently typed programming language, such as Agda. This function manipulates data types of well-typed source and target programs, and is therefore type correct by construction. A key challenge in implementing an intrinsically typed compiler is the representation of labels in bytecode. Because label names are global, bytecode typing appears to be inherently a non-compositional, whole-program property. The individual operations of the compiler do not preserve this property, which requires the programmer to reason about labels, which spoils the compiler definition with proof terms. In this paper, we address this problem using a new nameless and co-contextual representation of typed global label binding, which is compositional. Our key idea is to use linearity to ensure that all labels are defined exactly once. To write concise compilers that manipulate programs in our representation, we develop a linear, dependently typed, shallowly embedded language in Agda, based on separation logic. We show that this language enables the concise specification and implementation of intrinsically typed operations on bytecode, culminating in an intrinsically typed compiler for a language with structured control-flow.

Pattern search of programs is a fundamental function for supporting programming. In this paper, we propose a search method for unpreprocessed programs, which are difficult to parse. Our parser directly parses them by rewriting token sequences, and allows minor errors in syntax trees. The search tool takes queries that are the same as the format of program fragments. By using the same parser for both queries and target programs, programmers have no need to describe the detail structures of syntax trees in queries. To support accurate search, we also show an alignment tool for branch directives, which converts undisciplined directives to discipline ones, and a reverse macro expansion tool, which integrates the use of macro calls. Finally, we present some experiments in which we have applied the tools to an open source application, and discuss how to improve our tools.

BackgroundThis study conducted an empirical evaluation of an intervention derived from the theory of planned behavior (TPB) aimed at implementing a health campaign among medical students at Shahid Beheshti University of Medical Sciences.MethodsIn this interventional study, a valid and reliable TPB-based questionnaire was administered before launching a health campaign titled “Organ Donation=Life Donation” among 260 medical students. The campaign was structured around nine steps situation analysis, goal identification, target audience identification, strategy development, tactics establishment, media selection, timetable creation, budget planning, and program evaluation. Two months after the campaign, participants completed a posttest and were offered an organ donation card. Data analysis was conducted using SPSS ver. 16, employing descriptive statistics (frequency and percentage) and tests such as the Kolmogorov-Smirnov test and the paired-samples t-test.ResultsAll participants adopted more prodonation stances across all constructs measured, both immediately and 2 months after exposure to the health campaign, compared to their pretest scores. These results indicate that the health campaign had a significant impact on psychological variables such as attitudes (P<0.001), subjective norms (P<0.001), and perceived behavioral control (P<0.038), as well as on the actual acceptance of an organ donor card.ConclusionsEffective health education and promotion interventions, including health campaigns, are essential to encourage the use of organ donation cards. Additionally, current experiences indicate that the TPB serves as a suitable theoretical framework for designing organ donation interventions.

Feature Oriented Programming (FOP) is a design methodology and tools for program synthesis. The goal is to specify a target program in terms of the features that it offers, and to synthesize an efficient program that meets these specifications. FOP has been used to develop product-lines in disparate domains, including compilers for extensible Java dialects [3], fire support simulators for the U.S. Army [5], high-performance network protocols [1], and program verification tools [14].

As modern programs grow in size and complexity, the importance of program behavior modeling is emerging in various areas. Because of the large amount of data generated by a target program and the difficulty of runtime analysis, previous works in these areas employ deep learning. However, they did not sufficiently consider the input of a target program, since, in our view, program behavior is a history of computational steps consisting of a function and its input arguments. A naive, intuitive way to embed the value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$x$</tex-math></inline-formula> as it is in a vector representation creates a tremendously large vector size. Instead, we found that all the values inducing the same runtime behavior can be represented as one identical <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">characteristic value</i> (CV). In this paper, we show that not only can a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">characteristic value</i> sequence replace the argument input, but it is also efficient to use it as an input vector for a neural network. This efficiency comes from modeling the whole program with multiple LSTM-RNN models and reducing the input space of the neural network. To demonstrate the effectiveness of this replacement, we performed experiments on the problem of program behavior anomaly detection. Our results show that our model achieves better detection performance compared to previous models and similar detection performance even with smaller model sizes. We also provide a visualization of the embedded vectors extracted from the embedding layer in the neural network model to prove that the CV sequence well represents the arguments.

In this tutorial the specialisation of declarative logic programs is presented. The main correctness results are given, and the outline of a basic algorithm for partial evaluation of a logic program with respect to a goal. The practical considerations of gaining efficiency (and not losing any) are discussed. A renaming scheme for performing structure specialisation is then described, and illustrated on a well-known string matching example. The basic algorithm is enhanced by incorporating abstract interpretation. A two-phase specialisation is then described and illustrated, in which partial evaluation is followed by the detection and removal of useless clauses. This is shown for the specialisation of a proof procedure for first order logic. The specialisation of meta programs is very important in logic programming, and the ground representation for object programs has to be handled. Some techniques for doing this are described. Comparisons are made in the tutorial to similar work in other programming languages, and the similarities and differences between them and logic program specialisation is discussed.

Background/Context: As dual language bilingual education (DLBE) programs expand nationwide, parental feedback becomes crucial in evaluating their effectiveness and ensuring equitable access. Understanding the perspectives of diverse parental groups, including marginalized and privileged communities, is essential for developing inclusive and equitable language programs that serve all students. Furthermore, the changing demographics of students and their families with transnational experiences, along with the growing diversity in non-Spanish DLBE languages, highlight the need for research that documents diverse DLBE programs and contexts. Considering this context, acknowledging parental views on Korean programs is meaningful in valuing the opinions of parents with rich transnational experiences in one of the less-commonly taught language programs in the country. Korean dual language programs are also under-researched in the DLBE literature, despite their unique spaces where different power dynamics emerge compared to Spanish or Chinese DLBE programs. Objective and Research Question: This study aims to investigate parents’ evaluations of DLBE programs, their plans to enroll their child until the secondary level, and potential reasons for leaving DLBE programs. First, the researcher explores parents’ evaluations of Korean dual language programs (KDLPs) and examines how parental evaluation is associated with other aspects of parents’ views and characteristics, such as their demographic features, parental satisfaction with their child’s language development, integration experiences among both children and parents, and parental involvement in the program. Next, the researcher investigates whether parents plan to enroll their child in KDLPs until the secondary level (grade 8 or 12) and examines the relationship between their plan and program evaluation. The study also probes the association between parental commitment plans and other variables related to parents’ views and characteristics. Finally, the study explores potential reasons that could spur parents to leave KDLPs. Research Design: This quantitative study used survey data collected from a sample of over 450 parents of students in seven KDLPs at the elementary level in Southern California. This study employed multilevel modeling, accounting for the nested data structure of respondents within schools. The parental evaluation variable was explored by multilevel ordinary least squares (OLS) regression with a cubed form of program evaluation value as the dependent variable to explore parents’ evaluation. For examining parents’ program commitment plans, multilevel logistic regression analysis was employed. To examine the difference between Korean and non-Korean parents in potential reasons for leaving the program, this study used the Wilcoxon-Mann-Whitney test. Conclusions/Recommendations: The results show that parental evaluation of KDLPs is positively linked with satisfaction in bilingualism, biliteracy, academic rigor, and sociocultural competence variables, with satisfaction in the target language (Korean) and academic rigor having the most significant impact. The study also reveals that parents’ likelihood of enrolling their child in a secondary KDLP is influenced by the length of their child’s enrollment, satisfaction with academic rigor, and integration among children. Interestingly, program evaluation does not significantly affect enrollment decisions. The integration issue that children did not get along with students of different races and cultures was the most influential reason for leaving the KDLPs for both Korean and non-Korean parents. Non-Korean parents also cited challenges with target language instruction as a potential reason for leaving the program. In summary, the results reveal the complex nature of parental perceptions and highlight the values that parents prioritize when assessing the programs. These insights have important implications for future research on KDLPs and DLBE programs more broadly, in terms of both advancing theoretical discussions and informing empirical investigations. By shedding light on the complexities of parental evaluations, this study also proposes the need for a distinct ideological framework in Asian language programs to better understand individual experiences and promote equity and justice in those programs.

Neuropeptide identification in mass spectrometry experiments using database search programs developed for proteins is challenging. Unlike proteins, the detection of the complete sequence using a single spectrum is required to identify neuropeptides or prohormone peptides. This study compared the performance of three open-source programs used to identify proteins, OMSSA, X!Tandem and Crux, to identify prohormone peptides. From a target database of 7850 prohormone peptides, 23550 query spectra were simulated across different scenarios. Crux was the only program that correctly matched all peptides regardless of p-value and at p-value < 1 × 10–2, 33%, 64%, and >75%, of the 5, 6, and ≥7 amino acid-peptides were detected. Crux also had the best performance in the identification of peptides from chimera spectra and in a variety of missing ion scenarios. OMSSA, X!Tandem and Crux correctly detected 98.9% (99.9%), 93.9% (97.4%) and 88.7% (98.3%) of the peptides at E- or p-value < 1 × 10–6 (< 1 × 10–2), respectively. OMSSA and X!Tandem outperformed the other programs in significance level and computational speed, respectively. A consensus approach is not recommended because some prohormone peptides were only identified by one program.

Career guidance professionals and employability teachers aim to develop graduate employability characteristics in response to employer and CBI demands for ‘future fit’ graduate entrants to the labour market (CBI 2009). Part of this ‘future fitness’ relies on a global outlook and ‘cultural agility’ (AGR, CIHE, CFR 2011). The ‘Start your International Career’ programme at the University of Central Lancashire (UCLan) aims to promote and develop global career awareness and graduate capacities. A case study approach was used to examine the experience from the first cohort to seek out indications of potential effective practice to benefit teachers and careers professionals working in this subject area. Positive outcomes suggest that an incentivised and diverse programme can build international career awareness and global work competencies.

Middle school co-teachers and administrators offered information during focus groups, interviews, and surveys pertaining to co-teaching. Co-teaching in this study is defined as a special education teacher and a regular education teacher collaboratively providing instruction to a group of student with diverse learning needs. This qualitative program evaluation, conducted in a Midwestern suburban area, provides an analysis of middle school co-teaching with a focus on collaboration and professional development. The purpose of this study was to discover perceptions of middle school co-teaching from those at the front lines, including special education co-teachers, regular education co-teachers, and building administrators. The conceptual framework for this study was collaboration as defined by Friend and Cook (2013). Open and axial coding were used in the data analysis process. Findings indicated a lack of consistent and ongoing professional development, concerns with collaboration between co-teachers, and confusion with roles in co-teaching.

The need for modules in the development of large programs is well known while meta-programming is widely regarded as a simple yet powerful methodology for knowledge representation and reasoning. Thus if we wish to reason about large knowledge bases, it is desirable that meta-programs should be designed to reason about modular programs. This paper describes a module system which allows the modules to be parametrised over the language symbols exported by the module and shows that this provides a natural environment for meta-programming where both the meta and object programs enjoy the same parametrised module system.