Variability and Reproducibility in Software Engineering: A Study of Four Companies that Developed the Same System

The scientific study of a phenomenon requires it to be reproducible. Mature engineering industries are recognized by projects and products that are, to some extent, reproducible. Yet, reproducibility in software engineering (SE) has not been investigated thoroughly, despite the fact that lack of reproducibility has both practical and scientific consequences. We report a longitudinal multiple-case study of variations and reproducibility in software development, from bidding to deployment, on the basis of the same requirement specification. In a call for tender to 81 companies, 35 responded. Four of them developed the system independently. The firm price, planned schedule, and planned development process, had, respectively, “low,” “low,” and “medium” reproducibilities. The contractor's costs, actual lead time, and schedule overrun of the projects had, respectively, “medium,” “high,” and “low” reproducibilities. The quality dimensions of the delivered products, reliability, usability, and maintainability had, respectively, “low,” "high,” and “low” reproducibilities. Moreover, variability for predictable reasons is also included in the notion of reproducibility. We found that the observed outcome of the four development projects matched our expectations, which were formulated partially on the basis of SE folklore. Nevertheless, achieving more reproducibility in SE remains a great challenge for SE research, education, and industry.     

Predicting Missing Items in Shopping Carts

Existing research in association mining has focused mainly on how to expedite the search for frequently co-occurring groups of items in “shopping cart” type of transactions; less attention has been paid to methods that exploit these “frequent itemsets” for prediction purposes. This paper contributes to the latter task by proposing a technique that uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy. Using the recently proposed data structure of itemset trees (IT-trees), we obtain, in a computationally efficient manner, all rules whose antecedents contain at least one item from the incomplete shopping cart. Then, we combine these rules by uncertainty processing techniques, including the classical Bayesian decision theory and a new algorithm based on the Dempster-Shafer (DS) theory of evidence combination.     

Human Action Recognition by Semilatent Topic Models

We propose two new models for human action recognition from video sequences using topic models. Video sequences are represented by a novel “bag-of-words” representation, where each frame corresponds to a “word.” Our models differ from previous latent topic models for visual recognition in two major aspects: first of all, the latent topics in our models directly correspond to class labels; second, some of the latent variables in previous topic models become observed in our case. Our models have several advantages over other latent topic models used in visual recognition. First of all, the training is much easier due to the decoupling of the model parameters. Second, it alleviates the issue of how to choose the appropriate number of latent topics. Third, it achieves much better performance by utilizing the information provided by the class labels in the training set. We present action classification results on five different data sets. Our results are either comparable to, or significantly better than previously published results on these data sets.     

基于云服务的计算化学社区

中国科学院超算环境是由中国科学院统筹规划建设的“院总中心-分中心-所级中心”三层结构的超级计算环境,环境的资源聚合使用网格中间件 SCE,并使用 API 接口对外提供服务。依托超算环境建设的科学计算学云服务社区采用软件即服务的模式,使用浏览器/服务器结构来提供专业交互式的计算化学科学计算服务,以“降低使用门槛、提高使用效率,助跑计算化学用户的科学研究工作”为目标,为广大科研用户提供“一站式”计算的 Web 服务模式和异构资源协同工作模式。本文同时介绍了社区的建设应用情况以及环境的运行、监控情况。     

ICCD: Interactive Continuous Collision Detection between Deformable Models Using Connectivity-Based Culling

We present an interactive algorithm for continuous collision detection between deformable models. We introduce multiple techniques to improve the culling efficiency and the overall performance of continuous collision detection. First, we present a novel formulation for continuous normal cones and use these normal cones to efficiently cull large regions of the mesh as part of self-collision tests. Second, we introduce the concept of “procedural representative triangles” to remove all redundant elementary tests between nonadjacent triangles. Finally, we exploit the mesh connectivity and introduce the concept of “orphan sets” to eliminate redundant elementary tests between adjacent triangle primitives. In practice, we can reduce the number of elementary tests by two orders of magnitude. These culling techniques have been combined with bounding volume hierarchies and can result in one order of magnitude performance improvement as compared to prior collision detection algorithms for deformable models. We highlight the performance of our algorithm on several benchmarks, including cloth simulations, N-body simulations, and breaking objects.     

Chasing the Weakest System Model for Implementing Ω and Consensus

Aguilera et al. and Malkhi et al. presented two system models, which are weaker than all previously proposed models where the eventual leader election oracle Ω can be implemented, and thus, consensus can also be solved. The former model assumes unicast steps and at least one correct process with f outgoing eventually timely links, whereas the latter assumes broadcast steps and at least one correct process with f bidirectional but moving eventually timely links. Consequently, those models are incomparable. In this paper, we show that Ω can also be implemented in a system with at least one process with f outgoing moving eventually timely links, assuming either unicast or broadcast steps. It seems to be the weakest system model that allows to solve consensus via Ω-based algorithms known so far. We also provide matching lower bounds for the communication complexity of Ω in this model, which are based on an interesting “stabilization property” of infinite runs. Those results reveal a fairly high price to be paid for this further relaxation of synchrony properties.     

Automating the Design and Construction of Query Forms

One of the simplest ways to query a database is through a form where a user can fill in relevant information and obtain desired results by submitting the form. Designing good forms is a nontrivial manual task, and the designer needs a sound understanding of both the data organization and the querying needs. Furthermore, form design usually has conflicting goals: each form should be simple and easy to understand, while collectively, the interface must support as many queries as possible. In this paper, we present a framework for generating forms in an automatic and principled way, given a database and a sample query workload. We design a tunable clustering algorithm for establishing form structure based on multiple “similar” queries, which includes a mechanism for extending forms to support future “similar” queries. The algorithm is adaptive and can incrementally adjust forms to reflect the most current querying trends. We have implemented our form generation system on a real database and evaluated it on a comprehensive set of query loads and database schemas. We observe that our system generates a modest number of forms for large and diverse query loads even after placing a strict bound on form complexity.     

一种基于用户访问行为的推荐系统设计与实现

本文基于“中国科普博览”网站 Web 日志数据,设计和实现了一种推荐系统的原型。该系统主要包括数据预处理模块,基于改进型 FP-growth 算法设计的频繁项集挖掘模块,以及基于滑动窗口设计的推荐模型模块。改进型 FP-growth 算法利用页面访问次数与页面停留时间组成的权值,产生更符合挖掘需求的频繁项集。     

Generating Event Sequence-Based Test Cases Using GUI Runtime State Feedback

This paper presents a fully automatic model-driven technique to generate test cases for Graphical user interfaces (GUIs)-based applications. The technique uses feedback from the execution of a “seed test suite,” which is generated automatically using an existing structural event interaction graph model of the GUI. During its execution, the runtime effect of each GUI event on all other events pinpoints event semantic interaction (ESI) relationships, which are used to automatically generate new test cases. Two studies on eight applications demonstrate that the feedback-based technique 1) is able to significantly improve existing techniques and helps identify serious problems in the software and 2) the ESI relationships captured via GUI state yield test suites that most often detect more faults than their code, event, and event-interaction-coverage equivalent counterparts.     

浅谈虚拟现实技术的发展现状

虚拟现实(Virtual Reality,VR)技术是一种可以创建和体验虚拟世界的计算机仿真技术,它是人工智能、计算机图形学、多媒体技术、网络技术等多种技术的集成。针对目前VR产品不景气的状况,本文首先阐述了VR技术基本科技创新支撑不足的原因,进一步分析了VR技术急待突破的难题及其技术障碍,最后概括并展望了目前VR技术的技术成果。     

Reducing Redundancy in Subspace Clustering

In this paper, we first study an important but unsolved dilemma in the literature of subspace clustering, which is referred to as “information overlapping-data coverage” challenge. Current solutions of subspace clustering usually invoke a grid-based Apriori-like procedure to identify dense regions and construct subspace clusters afterward. Due to the nature of monotonicity property in Apriori-like procedures, it is inherent that if a region is identified as dense, all its projected regions are also identified as dense, causing overlapping/redundant clustering information to be inevitably reported to users when generating clusters from such highly correlated regions. However, naive methods to filter redundant clusters will incur a challenging problem in the other side of the dilemma, called the “data coverage” issue. Note that two clusters may have highly correlated dense regions but their data members could be highly different to each other. Arbitrarily removing one of them may lose the coverage of data with clustering information, thus likely reporting an incomplete and biased clustering result. In this paper, therefore, we further propose an innovative algorithm, called "NOnRedundant Subspace Cluster mining” (NORSC), to efficiently discover a succinct collection of subspace clusters while also maintaining the required degree of data coverage. NORSC not only avoids generating the redundant clusters with most of the contained data covered by higher dimensional clusters to resolve the information overlapping problem but also limits the information loss to cope with the data coverage problem. As shown by our experimental results, NORSC is very effective in identifying a concise and small set of subspace clusters, while incurring time complexity in orders of magnitude better than that of previous works.     

Direct Estimation of Nonrigid Registrations with Image-Based Self-Occlusion Reasoning

The registration problem for images of a deforming surface has been well studied. External occlusions are usually well handled. In 2D image-based registration, self-occlusions are more challenging. Consequently, the surface is usually assumed to be only slightly self-occluding. This paper is about image-based nonrigid registration with self-occlusion reasoning. A specific framework explicitly modeling self-occlusions is proposed. It is combined with an intensity-based, “direct” data term for registration. Self-occlusions are detected as shrinkage areas in the 2D warp. Experimental results on several challenging data sets show that our approach successfully registers images with self-occlusions while effectively detecting the self-occluded regions.     

Protect Us from Ourselves

A few weeks ago, a new Google Labs feature for their Gmail system made some news. They called it "mail goggles" and the tag line was "Stop sending mail you later regret". The announcement said that one of their engineers wanted to keep from sending pleas to his ex-girlfriend when he wasn't thinking straight, so he came up with a simple test. I checked my calendar — no, it wasn't April 1st — but I still couldn't help thinking this was an odd joke. Nope! Sure enough, if I go to the Labs page from my Gmail account, I see that the feature exists, with examples of simple — but not too simple — math problems it might pose.     

Full-Information Lookups for Peer-to-Peer Overlays

Most peer-to-peer lookup schemes keep a small amount of routing state per node, typically logarithmic in the number of overlay nodes. This design assumes that routing information at each member node must be kept small so that the bookkeeping required to respond to system membership changes is also small, given that aggressive membership dynamics are expected. As a consequence, lookups have high latency as each lookup requires contacting several nodes in sequence. In this paper, we question these assumptions by presenting a peer-to-peer routing algorithm with small lookup paths. Our algorithm, called “OneHop,” maintains full information about the system membership at each node, routing in a single hop whenever that information is up to date and in a small number of hops otherwise. We show how to disseminate information about membership changes quickly enough so that nodes maintain accurate complete membership information. We also present analytic bandwidth requirements for our scheme that demonstrate that it could be deployed in systems with hundreds of thousands of nodes and high churn. We validate our analytic model using a simulated environment and a real implementation. Our results confirm that OneHop is able to achieve high efficiency, usually reaching the correct node directly 99 percent of the time.     

Image Transformations and Blurring

Since cameras blur the incoming light during measurement, different images of the same surface do not contain the same information about that surface. Thus, in general, corresponding points in multiple views of a scene have different image intensities. While multiple-view geometry constrains the locations of corresponding points, it does not give relationships between the signals at corresponding locations. This paper offers an elementary treatment of these relationships. We first develop the notion of "ideal” and "real” images, corresponding to, respectively, the raw incoming light and the measured signal. This framework separates the filtering and geometric aspects of imaging. We then consider how to synthesize one view of a surface from another; if the transformation between the two views is affine, it emerges that this is possible if and only if the singular values of the affine matrix are positive. Next, we consider how to combine the information in several views of a surface into a single output image. By developing a new tool called "frequency segmentation,” we show how this can be done despite not knowing the blurring kernel.     

植物标本资源共享平台与标本数字化能力建设

植物标本资源共享平台是在科技部“国家科技基础条件平台”项目资助下建立的,并通过中国数字植物标本馆 (Chinese Virtual Herbarium,简称 CVH,网址：www.cvh.ac.cn) 网站为门户网站,为用户提供一个方便快捷获取中国植物标本及相关植物学信息的电子网络平台。CVH 从 2006 年发展至今,不仅在网站访问量、网站页面、网站资源量等方面都有了整体的提升和发展,还从 2014 年开始,注重参建单位的标本数字化能力建设工作,设计参建单位标本馆标本数字化能力提升的解决方案,为标本数字化工作的延续和发展提供了有力的技术支撑。     

Comparing shared and distributed memory computers

There are two distinct types of MIMD (Multiple Instruction, Multiple Data) computers: the shared memory machine, e.g. Butterfly, and the distributed memory machine, e.g. Hypercubes, Transputer arrays. Typically these utilize different programming models: the shared memory machine has monitors, semaphores and fetch-and-add; whereas the distributed memory machine uses message passing. Moreover there are two popular types of operating systems: a multi-tasking, asynchronous operating system and a crystalline, loosely synchronous operating system.

In this paper I firstly describe the Butterfly, Hypercube and Transputer array MIMD computers, and review monitors, semaphores, fetch-and-add and message passing; then I explain the two types of operating systems and give examples of how they are implemented on these MIMD computers. Next I discuss the advantages and disadvantages of shared memory machines with monitors, semaphores and fetch-and-add, compared to distributed memory machines using message passing, answering questions such as “is one model ‘easier’ to program than the other?” and “which is ‘more efficient‘?”. One may think that a shared memory machine with monitors, semaphores and fetch-and-add is simpler to program and runs faster than a distributed memory machine using message passing but we shall see that this is not necessarily the case. Finally I briefly discuss which type of operating system to use and on which type of computer. This of course depends on the algorithm one wishes to compute.     

General Cost Models for Evaluating Dimensionality Reduction in High-Dimensional Spaces

Similarity search usually encounters a serious problem in the high-dimensional space, known as the “curse of dimensionality.” In order to speed up the retrieval efficiency, most previous approaches reduce the dimensionality of the entire data set to a fixed lower value before building indexes (referred to as global dimensionality reduction (GDR)). More recent works focus on locally reducing the dimensionality of data to different values (called the local dimensionality reduction (LDR)). In addition, random projection is proposed as an approximate dimensionality reduction (ADR) technique to answer the approximate similarity search instead of the exact one. However, so far little work has formally evaluated the effectiveness and efficiency of GDR, LDR, and ADR for the range query. Motivated by this, in this paper, we propose general cost models for evaluating the query performance over the reduced data sets by GDR, LDR, and ADR, in light of which we introduce a novel (A)LDR method, Partitioning based on RANdomized Search (PRANS). It can achieve high retrieval efficiency with the guarantee of optimality given by the formal models. Finally, a {rm B}^{+}-tree index is constructed over the reduced partitions for fast similarity search. Extensive experiments validate the correctness of our cost models on both real and synthetic data sets and demonstrate the efficiency and effectiveness of the proposed PRANS method.     

Scaled rotation regularization

A new regularization method - a scaled rotation - is proposed and compared with the standard linear regularized discriminant analysis. A sense of the method consists in the singular value decomposition S=TDT′ of a sample covariance matrix S and a use of the following representation of an inverse of the covariance matrix S⁻¹=T(D+λI)⁻¹T ′. For certain data structures the scaled rotation helps to reduce the generalization error in small learning-set and high dimensionality cases. Efficacy of the scaled rotation increases if one transforms the data by y=(D+λI)^−1/2T ′x and uses an optimally stopped single layer perceptron classifier afterwards.     

An approach towards the design of intelligent man-machine interfaces used in process control

This paper is related to improvements carried out n the field of human-machine communication in complex industrial processes, using the concept of the ‘intelligent’ interface. Following a review of literature on this subject, an ‘intelligent’ interface design based on ergonomical concepts is described. Finally, we present our approach to the design of an ‘intelligent’ interface. The Decisional Module of Imagery (D.M.I.) as it is called, is based on two models: a task model and a user model. The D.M.I.'s structure and its integration in an experimental platform are described in the last part of this paper.