One possibility to automate more of software testing is to have developers write more general test cases. Given a general (parameterized test case), that holds in many situations, software can generate many different test instances and execute them automatically. Thus, even though the developers write fewer and smaller tests they can test more. However, it is not clear what other effects the use of generalized test cases has. One hypothesis is that “More general test cases are harder to understand than concrete ones and thus would lead to overall tests that are harder to understand”. Software understandability can be defined as the system that is written by one person is easy to read and understand by another person easily without any resistance. However, software understandability is hard to measure because understandability depends on the cognitive behavior of human. Software understandability assists in software reusability and software maintainability.

This report presents an extension to the domain definition language for Threaded Forward-chaining Partial Order Planner (TFPOP) that can be used to increase the understandability of domain models. The extension consists of composite actions which is a method for expressing abstract actions as procedures of primitive actions. TFPOP can then uses these abstract actions when searching for a plan. An experiment, with students as participants, was used to show that using composite action can increase the understandability for non-expert users. Moreover, it was also proved the planner can utilize the composite action to significantly decrease the search time. Furthermore, indications was found that using composite actions is equally fast in terms of search time as using existing equivalent methods to decrease the search time.

This thesis deals with text simplification in Czech, in particular with lexical simplification. Several strategies of complex word identification, substitution generation and substitution ranking are implemented and evaluated. Substitution generation is attempted both in a dictionary-based manner and in an embedding- based manner. Some experiments involving people are also presented, the experiments aim at gaining an in- sight into perceived simplicity/complexity and its factors. The experiments conducted and evaluated include sentence pair comparison and manual text simplification. Both the evaluation results of various strategies and the outcomes of experiments involving humans are described and some future work is suggested. 1

Syftet med denna studie var att förstå de strategier som användes av socialsekreterarna i hanteringen av en stor arbetsbelastning och undersöka deras nivå av känsla av sammanhang i hanteringen av nätverksfamiljehemsplaceringar av ensamkommande barn under 2015 och 2016. Studien varkvalitativ, och vårt empiriska material bestod av semistrukturerade intervjuer.Åtta socialsekreterare från sju mindre kommuner och två socialsekreterare från störrekommuner i södra Sverige, alla med erfarenhet av att arbeta med ensamkommande barn, deltog i vår studie. Vår ambition var att förstå hur, trots den stora arbetsbelastningen, socialsekreterarna hanterade sin arbetssituation. Vi försökte förstå de strategierna som bidrog till att göra det möjligt för socialsekreterarna att stanna kvar på sitt arbete trots omständigheterna. Vi fann att alla socialsekreterarna som intervjuades i vår studie hade en hög känsla av sammanhang som hjälpte dem att göra deras arbete meningsfullt och hanterbart. Den vanligaste coping strategi som socialsekreterarna använde sig av för att hantera deras arbetssituation var genom att sänka sina ambitioner och acceptera att deras arbete nådde en "good enough" standard. Socialsekreterare med stor arbetslivserfarenhet tenderade också att hantera den högre arbetsbelastningen mer framgångsrikt genom att acceptera, att trots att de inte alltid kunde följa rutiner och riktlinjer var avsikten fortfarande att göra gott i en svår situation. / The aim of this study was to create an understanding of the strategies used by the social workersin order to handle a large workload and to examine their level of sense of coherence intheir handling of kinship foster care placements of unaccompanied children in the years 2015and 2016. The study was qualitative, and our empirical material consists of semi-structuredinterviews. Eight social workers from seven smaller municipalities and two social workersfrom larger municipalities in southern Sweden, all with experience of working with unaccompaniedchildren, have participated in our study. Our ambition was to understand how, despitethe large workload, the social workers handled their situation. We have tried to create an understandingof the strategies that contributed to make it possible for the social workers to remainat work despite the circumstances. We have found that all the social workers interviewedin our study had a high sense of coherence that helped them make their work understandableand manageable. The most common coping strategy the social workers used was tolower their ambitions and accept that their administration reached “good enough” to handletheir workload. Social workers with a lot of work experience also tend to be able to handle ahigh workload more successfully by accepting that, in spite of not always being able to abideby routines and procedures, the intention is still to do good in a bad situation.

Alors que Twitter évolue vers un outil omniprésent de diffusion de l'information, la compréhension des tweets en langues étrangères devient un problème important et difficile. En raison de la nature intrinsèquement à commutation de code, discrète et bruitée des tweets, la traduction automatique (MT) à l'état de l'art n'est pas une option viable (Farzindar & Inkpen, 2015). En effet, au moins pour le hindi et le japonais, nous observons que le pourcentage de tweets « compréhensibles » passe de 80% pour les locuteurs natifs à moins de 30% pour les lecteurs monolingues cible (anglais ou français) utilisant Google Translate. Notre hypothèse de départ est qu'il devrait être possible de créer des outils génériques, permettant aux étrangers de comprendre au moins 70% des « tweets locaux », en utilisant une interface polyvalente de « lecture active » (LA, AR en anglais) tout en déterminant simultanément le pourcentage de tweets compréhensibles en-dessous duquel un tel système serait jugé inutile par les utilisateurs prévus.Nous avons donc spécifié un « SUFT » (système d'aide à la compréhension des tweets étrangers) générique, et mis en œuvre SUFT-1, un système interactif à mise en page multiple basé sur la LA, et facilement configurable en ajoutant des dictionnaires, des modules morphologiques et des plugins de TA. Il est capable d'accéder à plusieurs dictionnaires pour chaque langue source et fournit une interface d'évaluation. Pour les évaluations, nous introduisons une mesure liée à la tâche induisant un coût négligeable, et une méthodologie visant à permettre une « évaluation continue sur des données ouvertes », par opposition aux mesures classiques basées sur des jeux de test liés à des ensembles d'apprentissage fermés. Nous proposons de combiner le taux de compréhensibilité et le temps de décision de compréhensibilité comme une mesure de qualité à deux volets, subjectif et objectif, et de vérifier expérimentalement qu'une présentation de type lecture active, basée sur un dictionnaire, peut effectivement aider à comprendre les tweets mieux que les systèmes de TA disponibles.En plus de rassembler diverses ressources lexicales, nous avons construit une grande ressource de "formes de mots" apparaissant dans les tweets indiens, avec leurs analyses morphologiques (à savoir 163221 formes de mots hindi dérivées de 68788 lemmes et 72312 formes de mots marathi dérivées de 6026 lemmes) pour créer un analyseur morphologique multilingue spécialisé pour les tweets, capable de gérer des tweets à commutation de code, de calculer des traits unifiés, et de présenter un tweet en lui attachant un graphe de LA à partir duquel des lecteurs étrangers peuvent extraire intuitivement une signification plausible, s'il y en a une. / As Twitter evolves into a ubiquitous information dissemination tool, understanding tweets in foreign languages becomes an important and difficult problem. Because of the inherent code-mixed, disfluent and noisy nature of tweets, state-of-the-art Machine Translation (MT) is not a viable option (Farzindar & Inkpen, 2015). Indeed, at least for Hindi and Japanese, we observe that the percentage of "understandable" tweets falls from 80% for natives to below 30% for target (English or French) monolingual readers using Google Translate. Our starting hypothesis is that it should be possible to build generic tools, which would enable foreigners to make sense of at least 70% of “native tweets”, using a versatile “active reading” (AR) interface, while simultaneously determining the percentage of understandable tweets under which such a system would be deemed useless by intended users.We have thus specified a generic "SUFT" (System for Helping Understand Tweets), and implemented SUFT-1, an interactive multi-layout system based on AR, and easily configurable by adding dictionaries, morphological modules, and MT plugins. It is capable of accessing multiple dictionaries for each source language and provides an evaluation interface. For evaluations, we introduce a task-related measure inducing a negligible cost, and a methodology aimed at enabling a « continuous evaluation on open data », as opposed to classical measures based on test sets related to closed learning sets. We propose to combine understandability ratio and understandability decision time as a two-pronged quality measure, one subjective and the other objective, and experimentally ascertain that a dictionary-based active reading presentation can indeed help understand tweets better than available MT systems.In addition to gathering various lexical resources, we constructed a large resource of "word-forms" appearing in Indian tweets with their morphological analyses (viz. 163221 Hindi word-forms from 68788 lemmas and 72312 Marathi word-forms from 6026 lemmas) for creating a multilingual morphological analyzer specialized to tweets, which can handle code-mixed tweets, compute unified features, and present a tweet with an attached AR graph from which foreign readers can intuitively extract a plausible meaning, if any.

As the technology develops and robots are integrating into more and more facets of our lives, the futureof human-robot interaction may take form in all kinds of arrangements and configurations. In this study, we examined the understandability of di erent conversational strategies in robot-robot communication from a human-bystander standpoint. Specifically, we examined the understandability of verbal explanations constructed under Grice's maxims of informativeness. A prediction task was employed to test the understandability of the proposed strategy among other strategies. Furthermore, participants' perception of the robots' interaction was assessed with a range of ratings and rankings. The results suggest that those robots using the proposed strategy and those using the other tested strategies were understood and perceived similarly. / I takt med att teknologin utvecklas integreras robotar mer och mer i olika delar av våra liv. Framtidens människo-robot interaktioner kan ta många olika former och konfigurationer. I den här studien undersökte vi förståelsen för olika konversationsstrategier mellan robotar ur det mänskliga perspektivet. Specifikt undersökte vi förståelsen av muntliga förklaringar konstruerade enligt Grices princip för informativitet. En uppgift för deltagarna i testet var att försöka förutsäga robotarnas agerande. Dessutom utvärderades robotarnas interaktion genom att låta deltagarna rangordna och betygsätta dem. Resultatet tyder på att de robotar som använder Grices princip och de som använder de andra testade strategierna förstås och uppfattas på ett liknande sätt.

This document represents efforts to design and evaluate a new sign design for emergency route trailblazing in a two-part series. Study 1 was an off-road field experiment conducted to determine the best color combination and letter design for the emergency sign. Based upon Study 1 results, black on coral, black on light blue, and yellow on purple signs were chosen for further testing against a baseline black on orange sign, all with 125-mm, D series letters. Study 2 was an on-road field study of conspicuity, conducted using an instrumented vehicle through a construction zone-related detour, and a survey questionnaire. The findings indicated that use of a color combination other than traditional black on orange will improve driver performance and safety when used for trailblazing during critical incidents. Based on the conclusions and other anecdotal evidence, the following recommendations were made: 1) Do not use black on orange signs for trailblazing around a critical incident if an existing detour/construction zone is in place; 2) Do not use a black on coral sign for trailblazing around a critical incident; 3) A light blue on black sign is recommended due to generally favorable subjective ratings and for minimization of turn errors in an overlapping detour; however, the black on light blue sign may resemble regulatory signs when headlights reflect onto it; and 4) If reject black on light blue signs based on (3), consider using yellow on purple signs, which resulted in fewer turn errors than black on orange and received generally favorable ratings. / Master of Science

The field of explainable artificial intelligence (XAI) has gained momentum in recent years following the increased use of AI systems across industries leading to bias, discrimination, and data security concerns. Several conceptual frameworks for how to reach AI systems that are fair, transparent, and understandable have been proposed, as well as a number of technical solutions improving some of these aspects in a research context. However, there is still a lack of studies examining the implementation of these concepts and techniques in practice. This research aims to bridge the gap between prominent theory within the area and practical implementation, exploring the implementation and evaluation of XAI models in the Swedish credit scoring industry, and proposes a three-step framework for the implementation of local explanations in practice. The research methods used consisted of a case study with the model development at UC AB as a subject and an experiment evaluating the consumers' levels of trust and system understanding as well as the usefulness, persuasive power, and usability of the explanation for three different explanation prototypes developed. The framework proposed was validated by the case study and highlighted a number of key challenges and trade-offs present when implementing XAI in practice. Moreover, the evaluation of the XAI prototypes showed that the majority of consumers prefers rulebased explanations, but that preferences for explanations is still dependent on the individual consumer. Recommended future research endeavors include studying a longterm XAI project in which the models can be evaluated by the open market and the combination of different XAI methods in reaching a more personalized explanation for the consumer. / Under senare år har antalet AI implementationer stadigt ökat i flera industrier. Dessa implementationer har visat flera utmaningar kring nuvarande AI system, specifikt gällande diskriminering, otydlighet och datasäkerhet vilket lett till ett intresse för förklarbar artificiell intelligens (XAI). XAI syftar till att utveckla AI system som är rättvisa, transparenta och begripliga. Flera konceptuella ramverk har introducerats för XAI som presenterar etiska såväl som politiska perspektiv och målbilder. Dessutom har tekniska metoder utvecklats som gjort framsteg mot förklarbarhet i forskningskontext. Däremot saknas det fortfarande studier som undersöker implementationer av dessa koncept och tekniker i praktiken. Denna studie syftar till att överbrygga klyftan mellan den senaste teorin inom området och praktiken genom en fallstudie av ett företag i den svenska kreditupplysningsindustrin. Detta genom att föreslå ett ramverk för implementation av lokala förklaringar i praktiken och genom att utveckla tre förklaringsprototyper. Rapporten utvärderar även prototyperna med konsumenter på följande dimensioner: tillit, systemförståelse, användbarhet och övertalningsstyrka. Det föreslagna ramverket validerades genom fallstudien och belyste ett antal utmaningar och avvägningar som förekommer när XAI system utvecklas för användning i praktiken. Utöver detta visar utvärderingen av prototyperna att majoriteten av konsumenter föredrar regelbaserade förklaringar men indikerar även att preferenser mellan konsumenter varierar. Rekommendationer för framtida forskning är dels en längre studie, vari en XAI modell introduceras på och utvärderas av den fria marknaden, dels forskning som kombinerar olika XAI metoder för att generera mer personliga förklaringar för konsumenter.

The broad aim of this research was to assess the decision-usefulness of environmental reports produced by South African companies that are listed on the Johanessburg Securities Exchange (JSE) to users of the reports. The study was motivated by a lack of research on the decision-usefulness of environmental reports in South Africa. The study was conducted in two phases. The first phase in form of a content analysis evaluated the decision-usefulness of the environmental reports of top 100 JSE-listed South African companies using a control list and a judgement scale. The second phase in form of a questionnaire survey was aimed at determining, the information needs of users of environmental reports produced by South African companies (that are listed on the JSE), the extent to which they read and employ the reports for making decisions. In addition, this phase was meant to ascertain the degree of users' satisfaction with the decision-usefulness of the environmental reports as well as elicit their suggestions on ways of improving the reports. Furthermore, the second phase was aimed at determining the users’ perception of the relative importance of environmental reports as well as ascertaining whether there was an expectation gap between the users and the preparers of the reports with regard to their decision-usefulness. The results of the content analysis phase of the study indicate that the environmental reports of the sampled companies were decision-useful, however their decision-usefulness varied widely. Although decision-useful, the environmental reports of the sampled companies were not comparable. In addition, the environmental reports of companies from sectors with a significant impact on the environment, and those of large companies were more decision-useful than the reports of companies from sectors with an insignificant impact on the environment and those of smaller companies. The results of the questionnaire survey phase of the study indicate that users prefer balanced environmental reports that disclose both negative and positive aspects that identify and describe key relevant issues, that are specific and contain accurate information, and that provide future oriented information. In addition, users prefer environmental reports that identify and address key stakeholders and their concerns, demonstrate the integration of environmental issues into core business processes, and that compare quantitative impacts against best practice. Furthermore, the results also indicate that users do read environmental reports, mostly from companies’ websites Portable Document Format (PDF) annual reports and that they mostly use the environmental reports for research, their own knowledge, and to hold companies accountable. However, users are not fully satisfied with the decision-usefulness of the environmental reports as they feel that there is a need to improve the reports in order to make them more decision-useful. The results also indicate that users perceive environmental reports to be more important than any other type of reports, most notably the financial reports. Comparing the responses of the users to those of preparers on various issues pertaining to the decision-usefulness of environmental reports, significant differences were found between the views of the two groups. These differences provide ample evidence that is consistent with the existence of an environmental reporting expectation gap in South Africa. This study makes several original contributions to environmental reporting literature, most notable of which is that, it is the first study in the South African context to empirically evaluate the quality (decision-usefulness) of environmental reports in line with the accounting conceptual frameworks and the GRI guidelines combined. By so doing, the study introduces to the academic literature an extensive five dimensional qualitative characteristic framework for evaluating the quality (decision-usefulness) of environmental reports. In addition, the study uniquely employs the decision-usefulness theory to provide insights into the environmental reporting practices of South African companies that are listed on the JSE. In so doing, it re-contextualises the theory that is typically employed in explaining financial reporting, and demonstrates its applicability in explaining the decision-usefulness of the environmental reporting practices of South African companies that are listed on the JSE. / Accounting / D. Com. (Accounting)

The broad aim of this research was to assess the decision-usefulness of environmental reports produced by South African companies that are listed on the Johanessburg Securities Exchange (JSE) to users of the reports. The study was motivated by a lack of research on the decision-usefulness of environmental reports in South Africa. The study was conducted in two phases. The first phase in form of a content analysis evaluated the decision-usefulness of the environmental reports of top 100 JSE-listed South African companies using a control list and a judgement scale. The second phase in form of a questionnaire survey was aimed at determining, the information needs of users of environmental reports produced by South African companies (that are listed on the JSE), the extent to which they read and employ the reports for making decisions. In addition, this phase was meant to ascertain the degree of users' satisfaction with the decision-usefulness of the environmental reports as well as elicit their suggestions on ways of improving the reports. Furthermore, the second phase was aimed at determining the users’ perception of the relative importance of environmental reports as well as ascertaining whether there was an expectation gap between the users and the preparers of the reports with regard to their decision-usefulness. The results of the content analysis phase of the study indicate that the environmental reports of the sampled companies were decision-useful, however their decision-usefulness varied widely. Although decision-useful, the environmental reports of the sampled companies were not comparable. In addition, the environmental reports of companies from sectors with a significant impact on the environment, and those of large companies were more decision-useful than the reports of companies from sectors with an insignificant impact on the environment and those of smaller companies. The results of the questionnaire survey phase of the study indicate that users prefer balanced environmental reports that disclose both negative and positive aspects that identify and describe key relevant issues, that are specific and contain accurate information, and that provide future oriented information. In addition, users prefer environmental reports that identify and address key stakeholders and their concerns, demonstrate the integration of environmental issues into core business processes, and that compare quantitative impacts against best practice. Furthermore, the results also indicate that users do read environmental reports, mostly from companies’ websites Portable Document Format (PDF) annual reports and that they mostly use the environmental reports for research, their own knowledge, and to hold companies accountable. However, users are not fully satisfied with the decision-usefulness of the environmental reports as they feel that there is a need to improve the reports in order to make them more decision-useful. The results also indicate that users perceive environmental reports to be more important than any other type of reports, most notably the financial reports. Comparing the responses of the users to those of preparers on various issues pertaining to the decision-usefulness of environmental reports, significant differences were found between the views of the two groups. These differences provide ample evidence that is consistent with the existence of an environmental reporting expectation gap in South Africa. This study makes several original contributions to environmental reporting literature, most notable of which is that, it is the first study in the South African context to empirically evaluate the quality (decision-usefulness) of environmental reports in line with the accounting conceptual frameworks and the GRI guidelines combined. By so doing, the study introduces to the academic literature an extensive five dimensional qualitative characteristic framework for evaluating the quality (decision-usefulness) of environmental reports. In addition, the study uniquely employs the decision-usefulness theory to provide insights into the environmental reporting practices of South African companies that are listed on the JSE. In so doing, it re-contextualises the theory that is typically employed in explaining financial reporting, and demonstrates its applicability in explaining the decision-usefulness of the environmental reporting practices of South African companies that are listed on the JSE. / Accounting / D. Com. (Accounting)