Swedish Institute of Computer Science Publications Database
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Test Case Prioritization Using Multi Criteria Decision Making Methods
No full textThe lack of a systematic approach to decision making might leads to a non-optimal usage of resources. Nowadays, the real world decision making problems are multiple criteria, complex, large scale and generally consist of uncertainty and vagueness. Multiple-criteria decision making (MCDM) is a subset of operations research and is divided into Multi-Objective Decision Making (MODM) and Multi-Attribute Decision Making (MADM). The principal objective of the present article is proposing a systematic multi-criteria design making approach in the area of software testing that will be exemplified by an industrial example
Practitioners' Perspectives on Change Impact Analysis for Safety-Critical Software - A Preliminary Analysis
No full textSafety standards prescribe change impact analysis (CIA) during evolution of safety-critical software systems. Although CIA is a fundamental activity, there is a lack of empirical studies about how it is performed in practice. We present a case study on CIA in the context of an evolving automation system, based on 14 interviews in Sweden and India. Our analysis suggests that engineers on average spend 50-100 hours on CIA per year, but the effort varies considerably with the phases of projects. Also, the respondents presented different connotations to CIA and perceived the importance of CIA differently. We report the most pressing CIA challenges, and several ideas on how to support future CIA. However, we show that measuring the effect of such improvement solutions is non-trivial, as CIA is intertwined with other development activities. While this paper only reports preliminary results, our work contributes empirical insights into practical CIA
Jogging at CHI
No full textHCI is increasingly paying attention to sports, and more and more CHI attendees are aiming to maintain being physically active while attending CHI. In response, we offer a SIG on the topic of sports-HCI and conduct it in a sportive way: we will go out of the conference venue and jog around San Jose while discussing the role of HCI in relation to sports. The goal is to actively shape the future of the field of sports-HCI
Prediction of user app usage behavior from geo-spatial data
No full textIn the era of mobile Internet, a vast amount of geo-spatial data allows us to gain further insights into human activities, which is critical for Internet Services Providers (ISP) to provide better personalized services. With the pervasiveness of mobile Internet, much evidence show that human mobility has heavy
impact on app usage behavior. In this paper, we propose a method based on machine learning to predict users' app usage behavior using several features of human mobility extracted from geo-spatial data in mobile Internet traces. The core idea of our method is selecting a set of mobility attributes (e.g. location, travel pattern, and mobility indicators) that have large impact on app usage behavior and inputting them into a classification model. We evaluate our method using real-world network traffic collected by our self-developed high-speed Traffic Monitoring System (TMS). Our prediction method achieves 90.3% accuracy in our experiment, which verifies the strong correlation between human mobility and app usage behavior. Our experimental results uncover a big potential of geo-spatial data extracted from mobile Internet
Automated Regression Testing Using Constraint Programming
No full textIn software validation, regression testing aims to check the absence of regression faults in new releases of a software system. Typically, test cases used in regression testing are executed during a limited amount of time and are selected to check a given set of user requirements. When testing large systems,the number of regression tests grows quickly over the years,and yet the available time slot stays limited. In order to overcome this problem, an approach known as test suite reduction (TSR), has been developed in software engineering to select a smallest subset of test cases, so that each requirement remains covered at least once. However solving the TSR problem is difficult as the underlying optimization problem is NP-hard,but it is also crucial for vendors interested in reducing the time to market of new software releases. In this paper, we address regression testing and TSR with Constraint Programming (CP). More specifically, we propose new CP models to solve TSR that exploit global constraints, namely NValue and GCC. We reuse a set of preprocessing rules to reduce a priori each instance,and we introduce a structure-aware search heuristic. We evaluated our CP models and proposed improvements against existing approaches, including a simple greedy approach and MINTS,the state-of-the-art tool of the software engineering community. Our experiments show that CP outperforms both the greedy approach and MINTS when it is interfaced with MiniSAT, in terms of percentage of reduction and execution time. When MINTS is interfaced with CPLEX, we show that our CP model performs better only on percentage of reduction. Finally, by working closely with validation engineers from Cisco Systems, Norway, we integrated our CP model into an industrial regression testing process
Move to be moved
No full textMovement-based design is reaching critical mass in HCI, and we can start to identify strategies, similarities and differences in how it is approached. Similarities may include, for example, a strong first person perspective on design, emphasising movement, somatics and aesthetic sensibilities of the designer, as well as starting from the premise that our bodily ways of being in the world are shaped by the ecologies of people, cultural practices and the artefacts we create and use. Different classes of systems are starting to emerge, such as spurring somaesthetic appreciation processes using biofeedback loops or carefully nudging us to interact with our own movements; engaging us in affective loops where the technology takes on a stronger agency, attempting to pull participants into particular experiences; extending on our senses and perception – even creating new senses through technology; social interactions, engaging us to jointly explore movement or touch; even endowing machines with their own ‘somatics’, exploring our relationship to technology; as well as engaging in larger political issues around the body, such as gender perspectives, or challenging the mind-body divide
GREP: a Group REkeying Protocol Based on Member Join History
No full textThis paper presents GREP, a highly scalable and efficient group rekeying protocol with the following merits. First, it rekeys the group with only two messages, introducing an overhead which is small, constant, and independent of the group size. Second, GREP considers collusion as a first-class attack. Third, GREP efficiently recovers the group from a collusion attack without recourse to a total member reinitialization. The recovery cost smoothly grows with the group size, and gradually increases with the attack severity. GREP achieves these results by organizing nodes into logical subgroups and exploiting the history of node joining events. This allows GREP to establish a total ordering among subgroups and among nodes in each subgroup, so making collusion recovery highly scalable and efficient. We evaluate performance from several standpoints, and show that GREP is deployable in large-scale networks of customary, even resource constrained, platforms
Kapacitetsanalys av Sävenäs rangerbangård: Spårbehov på riktningsgruppen undersökt i projektet PRAGGE
No full textI denna rapport analyseras kapaciteten på riktningsgruppen vid Sävenäs rangerbangård. Analysmetoden bygger på att schemalägga rangeringsrörelserna som krävs för att skapa de avgående tågen givet en viss bangårdskonfiguration. Schemaläggningen görs med matematisk optimering varvid antalet extra rörelser minimeras och används som ett mått för att bedöma belastningen på bangården. Resultatet är att minst 29 spår krävs på riktningsgruppen för att genomföra 2014 års trafik på ett rimligt sätt. En viktig iakttagelse är att antalet hanterade vagnar per tidsenhet inte ensamt är ett bra mått på belastningen på bangården, utan vagnarnas ståtid, antal destinationer och antalet ankommande respektive avgående tåg är exempel på andra parametrar som spelar stor roll för belastningen
Automatic Derivation of Platform Noninterference Properties
No full textFor the verification of system software, information flow properties of the instruction set architecture (ISA) are essential. They show how information propagates through the processor, including sometimes opaque control registers. Thus, they can be used to guarantee that user processes cannot infer the state of privileged system components, such as secure partitions.
Formal ISA models - for example for the HOL4 theorem prover - have been available for a number of years. However, little work has been published on the formal analysis of these models.
In this paper, we present a general framework for proving information flow properties of a number of ISAs automatically, for example for ARM.
The analysis is represented in HOL4 using a direct semantical embedding of noninterference, and does not use an explicit type system, in order to (i) minimize the trusted computing base, and to (ii) support a large degree of context-sensitivity, which is needed for the analysis.
The framework determines automatically which system components are accessible at a given privilege level, guaranteeing both soundness and accuracy