Asanka Wasala

Building Multilingual Language Resources in Web Localisation: A Crowdsourcing Approach

Before User Generated Content (UGC) became widespread, the majority of web content was generated for a specific target audience and in the language of that target audience. When information was to be published in multiple languages, it was done using well-established localisation methods. With the growth in UGC there are a number of issues, which seem incompatible with the traditional model of software localisation. First and foremost, the number of content contributors has increased hugely. As a by-product of this development, we are also witnessing a large expansion in the scale and variety of the content. Consequently, the demand for traditional forms of localisation (based on existing language resources, a professional pool of translators, and localisation experts) has become unsustainable. Additionally, the requirements and nature of the type of translation are shifting as well: The more web-based communities multiply in scale, type and geographical distribution, the more varied and global their requirements are. However, the growth in UGC also presents a number of localisation opportunities. In this chapter, we investigate web-enabled collaborative construction of language resources (translation memories) using micro-crowdsourcing approaches, as a means of addressing the diversity and scale issues that arise in UGC contexts and in software systems generally. As the proposed approaches are based on the expertise of human translators, they also address many of the quality issues related to MT-based solutions. The first example we provide describes a client-server architecture (UpLoD) where individual users translate elements of an application and its documentation as they use them, in return for free access to these applications. Periodically, the elements of the system and documentation translated by the individual translators are gathered centrally and are aggregated into an integral translation of all, or parts of, the system that can then be re-distributed to the system’s users. This architecture is shown to feed into the design of a browser extension-based client-server architecture (BE-COLA) that allows for the capturing and aligning of source and target content produced by the ‘power of the crowd’. The architectural approach chosen enables collaborative, in-context, and real-time localisation of web content supported by the crowd and generation of high-quality language resources.

Decision spaces in product lines, decision analysis, and design exploration: an interdisciplinary exploratory study

Context. From recent works on product properties resulting from configurations and the optimisation of these properties, one comes quickly to more complex challenges such as multi-objective optimisation, conflicting objectives, multiple stakeholders, and conflict resolution. The intuition is that Software Product Line Engineering (SPLE) can draw from other disciplines that deal with decision spaces and complex decision scenarios. Objectives. We aim to (1) explore links to such disciplines, (2) systematise and compare concepts, and (3) identify opportunities, where SPLE approaches can be enriched. Method. We undertake an exploratory study: Starting from common SPLE activities and artefacts, we identify aspects where we expect to find corresponding counterparts in other disciplines. We focus on Multiple Criteria Decision Analysis (MCDA), Multi-Objective Optimisation (MOO), and Design Space Exploration (DSE), and perform a comparison of the key concepts. Results. The resulting comparison relates SPLE activities and artefacts to concepts from MCDA, MOO, and DSE and identifies areas where SPLE approaches can be enriched. We also provide examples of existing work at the intersections of SPLE with the other fields. These findings are aimed to foster the conversation on research opportunities where SPLE can draw techniques from other disciplines dealing with complex decision scenarios.

FLINTS: a tool for architectural-level modeling of features in software systems

A functional perspective of software systems, at the architectural level allows developers to maintain a consistent understanding of the relationships between different functionalities of their system as it evolves, and allows them to analyze the system at a functional-chunk level rather than at the traditional, structural levels more typically presented by IDEs. This paper describes the derivation, implementation and evaluation of a prototype tool built to obtain this functional perspective from existing systems. The tool supports developers as they first attempt to locate specific functionalities in the source code. This support is based on preliminary design principles identified by observing experienced software developers in-vivo, as they performed this task manually. After the code associated with several such functionalities is located in the code, a graphical view allows the developer to assess the source code dependencies between the identified features and with the rest of the system. This helps developers understand the inter-functional interfaces and can be reviewed over time, as features are added and removed, to ensure on-going consistency between the architects perspective of the features in the system and the code-base.

Identification of potential classes in procedural code using a genetic algorithm

We present a novel approach for discovering and suggesting classes/objects in legacy/procedural code, based on a genetic algorithm. Initially, a (procedures-accessing-variables) matrix is extracted from the code and converted into a square matrix. This matrix highlights the variable-relationships between procedures and is used as input to a genetic algorithm. The output of the genetic algorithm is then visually encoded using a heat-map. The developers can then (1) either manually identify objects in the presented heat-map or (2) use an automated detection algorithm that suggests objects. We compare our results with previous work.