Modeling information in software languages

Ohjelmiston kehitystyökalut käyttävät infromaatiota kehittäjän tuottamasta lähdekoodista. Informaatiota hyödynnetään ohjelmistoprojektin eri vaiheissa ja eri tarkoituksissa. Moderneissa ohjelmistoprojekteissa käytetyn informaation määrä voi kasvaa erittäin suureksi. Ohjelmistotyökaluilla on omat informaatiomallinsa ja käyttömekanisminsa. Informaation määrä sekä erilliset työkaluinformaatiomallit tekevät erittäin hankalaksi rakentaa joustavaa työkaluympäristöä, erityisesti ongelma-aluekohtaiseen ohjelmiston kehitysprosessiin. Tässä työssä on analysoitu perusinformaatiometamalleja Unified Modeling language kielestä, Python ohjelmointikielestä ja C++ ohjelmointikielestä. Metainformaation taso on rajoitettu rakenteelliselle tasolle. Ajettavat rakenteet on jätetty pois. ModelBase metamalli on yhdistetty olemassa olevista analysoiduista metamalleista. Tätä metamallia voidaan käyttää tulevaisuudessa ohjelmistotyökalujen kehitykseen.

Python as a programming language for the introductory programming courses

Tämä kandidaatintyö tutkii tietotekniikan perusopetuksessa keskeisen aiheen,ohjelmoinnin, alkeisopetusta ja siihen liittyviä ongelmia. Työssä perehdytään ohjelmoinnin perusopetusmenetelmiin ja opetuksen lähestymistapoihin, sekä ratkaisuihin, joilla opetusta voidaan tehostaa. Näitä ratkaisuja työssä ovat mm. ohjelmointikielen valinta, käytettävän kehitysympäristön löytäminen sekä kurssia tukevien opetusapuvälineiden etsiminen. Lisäksi kurssin läpivientiin liittyvien toimintojen, kuten harjoitusten ja mahdollisten viikkotehtävien valinta kuuluu osaksitätä työtä. Työ itsessään lähestyy aihetta tutkimalla Pythonin soveltuvuutta ohjelmoinnin alkeisopetukseen mm. vertailemalla sitä muihin olemassa oleviin yleisiin opetuskieliin, kuten C, C++ tai Java. Se tarkastelee kielen hyviä ja huonoja puolia, sekä tutkii, voidaanko Pythonia hyödyntää luontevasti pääasiallisena opetuskielenä. Lisäksi työ perehtyy siihen, mitä kaikkea kurssilla tulisi opettaa, sekä siihen, kuinka kurssin läpivienti olisi tehokkainta toteuttaa ja minkälaiset tekniset puitteet kurssin toteuttamista varten olisi järkevää valita.

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.

Applications of graph transformation in tools for domain-specific modeling languages

The use of domain-specific languages (DSLs) has been proposed as an approach to cost-e ectively develop families of software systems in a restricted application domain. Domain-specific languages in combination with the accumulated knowledge and experience of previous implementations, can in turn be used to generate new applications with unique sets of requirements. For this reason, DSLs are considered to be an important approach for software reuse. However, the toolset supporting a particular domain-specific language is also domain-specific and is per definition not reusable. Therefore, creating and maintaining a DSL requires additional resources that could be even larger than the savings associated with using them. As a solution, di erent tool frameworks have been proposed to simplify and reduce the cost of developments of DSLs. Developers of tool support for DSLs need to instantiate, customize or configure the framework for a particular DSL. There are di erent approaches for this. An approach is to use an application programming interface (API) and to extend the basic framework using an imperative programming language. An example of a tools which is based on this approach is Eclipse GEF. Another approach is to configure the framework using declarative languages that are independent of the underlying framework implementation. We believe this second approach can bring important benefits as this brings focus to specifying what should the tool be like instead of writing a program specifying how the tool achieves this functionality. In this thesis we explore this second approach. We use graph transformation as the basic approach to customize a domain-specific modeling (DSM) tool framework. The contributions of this thesis includes a comparison of di erent approaches for defining, representing and interchanging software modeling languages and models and a tool architecture for an open domain-specific modeling framework that e ciently integrates several model transformation components and visual editors. We also present several specific algorithms and tool components for DSM framework. These include an approach for graph query based on region operators and the star operator and an approach for reconciling models and diagrams after executing model transformation programs. We exemplify our approach with two case studies MICAS and EFCO. In these studies we show how our experimental modeling tool framework has been used to define tool environments for domain-specific languages.

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM

Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.

A User-Centric Perspective on Parallel Programming with Focus on OpenMP

The process of developing software that takes advantage of multiple processors is commonly referred to as parallel programming. For various reasons, this process is much harder than the sequential case. For decades, parallel programming has been a problem for a small niche only: engineers working on parallelizing mostly numerical applications in High Performance Computing. This has changed with the advent of multi-core processors in mainstream computer architectures. Parallel programming in our days becomes a problem for a much larger group of developers. The main objective of this thesis was to find ways to make parallel programming easier for them. Different aims were identified in order to reach the objective: research the state of the art of parallel programming today, improve the education of software developers about the topic, and provide programmers with powerful abstractions to make their work easier. To reach these aims, several key steps were taken. To start with, a survey was conducted among parallel programmers to find out about the state of the art. More than 250 people participated, yielding results about the parallel programming systems and languages in use, as well as about common problems with these systems. Furthermore, a study was conducted in university classes on parallel programming. It resulted in a list of frequently made mistakes that were analyzed and used to create a programmers' checklist to avoid them in the future. For programmers' education, an online resource was setup to collect experiences and knowledge in the field of parallel programming - called the Parawiki. Another key step in this direction was the creation of the Thinking Parallel weblog, where more than 50.000 readers to date have read essays on the topic. For the third aim (powerful abstractions), it was decided to concentrate on one parallel programming system: OpenMP. Its ease of use and high level of abstraction were the most important reasons for this decision. Two different research directions were pursued. The first one resulted in a parallel library called AthenaMP. It contains so-called generic components, derived from design patterns for parallel programming. These include functionality to enhance the locks provided by OpenMP, to perform operations on large amounts of data (data-parallel programming), and to enable the implementation of irregular algorithms using task pools. AthenaMP itself serves a triple role: the components are well-documented and can be used directly in programs, it enables developers to study the source code and learn from it, and it is possible for compiler writers to use it as a testing ground for their OpenMP compilers. The second research direction was targeted at changing the OpenMP specification to make the system more powerful. The main contributions here were a proposal to enable thread-cancellation and a proposal to avoid busy waiting. Both were implemented in a research compiler, shown to be useful in example applications, and proposed to the OpenMP Language Committee.

AFL-1: A Programming Language for Massively Concurrent Computers

Computational models are arising is which programs are constructed by specifying large networks of very simple computational devices. Although such models can potentially make use of a massive amount of concurrency, their usefulness as a programming model for the design of complex systems will ultimately be decided by the ease in which such networks can be programmed (constructed). This thesis outlines a language for specifying computational networks. The language (AFL-1) consists of a set of primitives, ad a mechanism to group these elements into higher level structures. An implementation of this language runs on the Thinking Machines Corporation, Connection machine. Two significant examples were programmed in the language, an expert system (CIS), and a planning system (AFPLAN). These systems are explained and analyzed in terms of how they compare with similar systems written in conventional languages.

Programming & Software

An overview of programming and software development.

The European Declarative System, Database, and Languages

The EP2025 EDS project develops a highly parallel information server that supports established high-value interfaces. We describe the motivation for the project, the architecture of the system, and the design and application of its database and language subsystems. The Elipsys logic programming language, its advanced applications, EDS Lisp, and the Metal machine translation system are examined.

Formalizing languages for service oriented computing

Service Oriented Computing is a new programming paradigm for addressing distributed system design issues. Services are autonomous computational entities which can be dynamically discovered and composed in order to form more complex systems able to achieve different kinds of task. E-government, e-business and e-science are some examples of the IT areas where Service Oriented Computing will be exploited in the next years. At present, the most credited Service Oriented Computing technology is that of Web Services, whose specifications are enriched day by day by industrial consortia without following a precise and rigorous approach. This PhD thesis aims, on the one hand, at modelling Service Oriented Computing in a formal way in order to precisely define the main concepts it is based upon and, on the other hand, at defining a new approach, called bipolar approach, for addressing system design issues by synergically exploiting choreography and orchestration languages related by means of a mathematical relation called conformance. Choreography allows us to describe systems of services from a global view point whereas orchestration supplies a means for addressing such an issue from a local perspective. In this work we present SOCK, a process algebra based language inspired by the Web Service orchestration language WS-BPEL which catches the essentials of Service Oriented Computing. From the definition of SOCK we will able to define a general model for dealing with Service Oriented Computing where services and systems of services are related to the design of finite state automata and process algebra concurrent systems, respectively. Furthermore, we introduce a formal language for dealing with choreography. Such a language is equipped with a formal semantics and it forms, together with a subset of the SOCK calculus, the bipolar framework. Finally, we present JOLIE which is a Java implentation of a subset of the SOCK calculus and it is part of the bipolar framework we intend to promote.

Embedding Languages Without Breaking Tools

Domain-specific languages (DSLs) are increasingly used as embedded languages within general-purpose host languages. DSLs provide a compact, dedicated syntax for specifying parts of an application related to specialized domains. Unfortunately, such language extensions typically do not integrate well with the development tools of the host language. Editors, compilers and debuggers are either unaware of the extensions, or must be adapted at a non-trivial cost. We present a novel approach to embed DSLs into an existing host language by leveraging the underlying representation of the host language used by these tools. Helvetia is an extensible system that intercepts the compilation pipeline of the Smalltalk host language to seamlessly integrate language extensions. We validate our approach by case studies that demonstrate three fundamentally different ways to extend or adapt the host language syntax and semantics.

Mining the Ecosystem to Improve Type Inference For Dynamically Typed Languages

Dynamically typed languages lack information about the types of variables in the source code. Developers care about this information as it supports program comprehension. Ba- sic type inference techniques are helpful, but may yield many false positives or negatives. We propose to mine information from the software ecosys- tem on how frequently given types are inferred unambigu- ously to improve the quality of type inference for a single system. This paper presents an approach to augment existing type inference techniques by supplementing the informa- tion available in the source code of a project with data from other projects written in the same language. For all available projects, we track how often messages are sent to instance variables throughout the source code. Predictions for the type of a variable are made based on the messages sent to it. The evaluation of a proof-of-concept prototype shows that this approach works well for types that are sufficiently popular, like those from the standard librarie, and tends to create false positives for unpopular or domain specific types. The false positives are, in most cases, fairly easily identifiable. Also, the evaluation data shows a substantial increase in the number of correctly inferred types when compared to the non-augmented type inference.

Designing a high performance parallel logic programming system

Compilation techniques such as those portrayed by the Warren Abstract Machine(WAM) have greatly improved the speed of execution of logic programs. The research presented herein is geared towards providing additional performance to logic programs through the use of parallelism, while preserving the conventional semantics of logic languages. Two áreas to which special attention is given are the preservation of sequential performance and storage efficiency, and the use of low overhead mechanisms for controlling parallel execution. Accordingly, the techniques used for supporting parallelism are efficient extensions of those which have brought high inferencing speeds to sequential implementations. At a lower level, special attention is also given to design and simulation detail and to the architectural implications of the execution model behavior. This paper offers an overview of the basic concepts and techniques used in the parallel design, simulation tools used, and some of the results obtained to date.