In many actor-based programming models, asynchronous method calls communicate their results using futures, where the fulfilment occurs under-the-hood. Promises play a similar role to futures, except that they must be explicitly created and explicitly fulfilled; this makes promises more flexible than futures, though promises lack fulfilment guarantees: they can be fulfilled once, multiple times or not at all. Unfortunately, futures are too rigid to exploit many available concurrent and parallel patterns. For instance, many computations block on a future to get its result only to return that result immediately (to fulfil their own future). To make futures more flexible, we explore a construct, forward, that delegates the responsibility for fulfilling the current implicit future to another computation. Forward reduces synchronisation and gives futures promise-like capabilities. This paper presents a formalisation of the forward construct, defined in a high-level source language, and a compilation strategy from the high-level language to a low-level, promised-based target language. The translation is shown to preserve semantics. Based on this foundation, we describe the implementation of forward in the parallel, actor-based language Encore, which compiles to C.

Model reformulation plays an important role in improving models and reducing search space so that solutions can be found faster. In solving Constraint Satisfaction Problems (CSPs), a model of a CSP may be solved rapidly, while a different model may take excessively long to solve. The efficient solution of CSP is significant in real-world applications, such as air traffic management, resource allocation, production scheduling, and bioinformatics. Many technologies such as constraint programming (CP), hybrid technologies, mixed integer programming (MIP), constraint-based local search (CBLS), boolean satisfiability (SAT) could have different solvers and backends to solve the real-time problems. Model reformulation can have a significant impact on solving time. Techniques from formal methods will be used to provide machine assistance for MiniZinc, which is the high-level modelling language to model CSPs. The verification tool, Isabelle, will be used to verify the correctness of reformulations. We plan to apply recent results in formal methods such as program analysis and synthesis to provide semi-automated frameworks for model analysis. In this paper, we identify the challenges, implement frameworks, and evaluate our experimental results in reformulations for future research.

Model reformulation plays an important role in improving models, reducing search space so that solutions can be found faster. Hence we categorise model reformulation into three types: a model is reformulated to another model with the same modelling language, a model with non constraint programming standard types is compiled to another model with constraint programming (CP) standard types, and a model is converted to Boolean satisfiability problem (SAT), Mixed-integer programming (MIP), Satisfiability modulo theories (SMT), and Mixed integer linear programming (MILP). Based on these categories, reformulation and compilation could be used in different ways to improve a model such as automatic reformulations, semi-automatic reformulations, MIP to constraint programming, implied constraints, set Constraint Satisfaction Problems (CSPs) to CSPs, string variables to CSP without string variables, symmetry breaking, pre-computation, non-binary to binary translations, and reformulations into SAT, MILP, and SMT. CP is a pervasive and highly successful technology for solving a wide variety of constraint satisfaction problems such as air traffic management, resource allocation, transportation, scheduling, and so on. Model reformulation can have a significant impact on solving time. Techniques from formal methods will be used to provide machine assistance for MiniZinc, which is the high-level modelling language to model CSPs. In this survey, we present an overview of reformulation focusing on the contributions made in the area of reformulation of CSPs where significant performance improvements have been achieved. Our contributions are as follows: propose criteria and types that categorise model reformulations; we systematically unify and organise the vast literature; contrast and compare different categories of the reformulation for solving CSPs; propose a compiler for counter automata reformulation; ultimately, we propose a plan for future work, we identify the challenges, implement frameworks, and evaluate our experimental results of model reformulations.

 Constraint programming (CP) is pervasive and widely used to solve real-time problems which input data could be scaled up to the huge sizes, and the results are required to be given efficiently and dynamically. Many technologies such as CP, hybrid technologies, mixed integer programming (MIP), constraint-based local search (CBLS), boolean satisfiability (SAT) could have different solvers and backends to solve the real-time problems. Streaming videos problem is the problem that requires to decide which videos to put in which cache servers in order to minimise the waiting time for all requests with a description of cache servers, network endpoints and videos are given. In this paper, we model the streaming videos problem in two different ways. The first model is implemented using heuristics, and the global constraints are used in the second model. The experiments are benchmarked using MiniZinc, which is an open-source constraint modelling language that can be used to model constraint satisfaction and optimisation problems in the high-level, solver-independent way. The aim of the paper is to benchmark these technologies to evaluate the execution time and final scores of the two models using large instances of input data from Google Hash Code.

Soft skills are significant to the engineering labour market, especially in Information Technology where demands are high on for instance communication skill, teamwork skill, presentation skill, etc. Despite their importance, educating students in using those skills is not fully included in the bachelor education programmes, especially in developing countries. This project aims to gain insights in how soft skills are taught in Vietnamese universities, and which skills are missing in their bachelor education programmes. The findings are intended to support education in order to develop the teaching of soft skills for Vietnamese students, and decrease the unemployment rate of Vietnamese graduates. In this project, semi-structured interviews, by e-mail, have been used to collect the data. There are eight Vietnamese interviewees who have experiences from various education programmes. The interview transcripts were then analysed and categorised into themes. The results of our work are a preliminary identification of missing skills in the undergraduate programmes, and a set of proposed skills that could be considered to improve the education programmes.