An experimental investigation of personality types impact on pair effectiveness in pair programming

In this paper, pair programming is empirically investigated from the perspective of developer personalities and temperaments and how they affect pair effectiveness. A controlled experiment was conducted to investigate the impact of developer personalities and temperaments on communication, pair performance and pair viability-collaboration. The experiment involved 70 undergraduate students and the objective was to compare pairs of heterogeneous developer personalities and temperaments with pairs of homogeneous personalities and temperaments, in terms of pair effectiveness. Pair effectiveness is expressed in terms of pair performance, measured by communication, velocity, design correctness and passed acceptance tests, and pair collaboration-viability measured by developers’ satisfaction, knowledge acquisition and participation. The results have shown that there is important difference between the two groups, indicating better communication, pair performance and pair collaboration-viability for the pairs with heterogeneous personalities and temperaments. In order to provide an objective assessment of the differences between the two groups of pairs, a number of statistical tests and stepwise Discriminant Analysis were used.

The impact of social factors on pair programming in a primary school

Pair programming (PP) is a usefulness approach to fostering computational thinking (CT) for young students. However, there are many factors to impact the effectiveness of PP. Among all factors, the social factors are often ignored by researchers. Therefore, this study aimed to explore the impact of two social factors (gender and partnership) on PP in a primary school setting. To that end, we conducted PP experiments in four classes from the sixth grade in a Chinese primary school. The research results indicated: (a) there was no significant difference on compatibility among the gender pairs, but a significant difference among partnership pairs; (b) there was no significant difference on programming achievement and confidence among different pairs, and girls became more productive and confidence in PP; and (c) PP tightened up the partnership within pairs. These findings suggest that teachers should take partnership into account as an important factor in PP or other collaborative learning, and adopt PP as an effective approach to decrease the gender gap in programming courses, and make students socialize.     

Knowledge transfer in pair programming: An in-depth analysis

Whilst knowledge transfer is one of the most widely-claimed benefits of pair programming, little is known about how knowledge transfer is achieved in this setting. This is particularly pertinent for novice−expert constellations, but knowledge transfer takes place to some degree in all constellations. We ask “what does it take to be a good “expert” and how can a “novice” best learn from a more experienced developer?”. An in-depth investigation of video and audio excerpts of professional pair programming sessions using Interaction Analysis reveals: six teaching strategies, ranging from “giving direct instructions” to “subtle hints”; and challenges and benefits for both partners. These strategies are instantiations of some but not all teaching methods promoted in cognitive apprenticeship; novice articulation, reflection and exploration are not seen in the data. The context of pair programming influences the strategies, challenges and benefits, in particular the roles of driver and navigator and agile prioritisation which considers business value rather than educational progression. Utilising these strategies more widely and recognizing the challenges and benefits for both partners will help developers to maximise the benefits from pairing sessions.     

A comparative analysis of different gender pair combinations in pair programming

Over the last decade, there has been a steady stream of pair programming studies. However, one significant area of pair programming that has not received its due attention is gender. Considering the fact that pair programming is one of the major human-centric software development paradigms, this is a gap that needs to be addressed. This empirical study conducted quantitative and qualitative analyses of different gender pair combinations within pair programming context. Using a pool of university programming course students as the experiment participants, the study examined three gender pair types: female–female, female–male, and male–male. The result revealed that there was no significant gender difference in the pair programming coding output. But there were significant differences in the levels of pair compatibility and communication between the same gender pair type: female–female and male–male, and the mixed gender pair type, female–male. The post-experiment comments provide additional insights and details about gender in pair interactions.     

利用结对编程技术改进程序设计实践教学

介绍了结对编程的概念,阐述了其作为学习编程技能的一种过程改进策略在国外计算机专业教学中的实验效果,并论述了相关影响因素。     

Java语言实验教学改革探讨

针对Java语言实验课程的教学现状,本文探讨了该课程实验教学方面的改革。通过在课程中引入敏捷方法和自动单元测试,来激发学生的学习兴趣,提高学生的编程能力、沟通能力和团队合作能力,改善学     

The implementation of linear programming algorithms based on homotopies

A fundamental homotopy-based linear programming algorithm, which utilizes Euler-predictor and Newton-corrector steps with restarts, is formulated and investigated numerically on problems representative of linear programs that arise in practice. A rich array of refinements of this basic algorithm are possible within the homotopy framework. Such refinements are needed in any practical implementation and are discussed in detail. Implications for the design of integrated large-scale mathematical programming software are also briefly considered.This research was supported by NSF Grant DMS-8815513, and first appeared, under the same title, as Technical Report 91-6 (October, 1991) issued by the department below.     

Adaptive value function approximation for continuous-state stochastic dynamic programming

Approximate dynamic programming (ADP) commonly employs value function approximation to numerically solve complex dynamic programming problems. A statistical perspective of value function approximation employs a design and analysis of computer experiments (DACE) approach, where the “computer experiment” yields points on the value function curve. The DACE approach has been used to numerically solve high-dimensional, continuous-state stochastic dynamic programming, and performs two tasks primarily: (1) design of experiments and (2) statistical modeling. The use of design of experiments enables more efficient discretization. However, identifying the appropriate sample size is not straightforward. Furthermore, identifying the appropriate model structure is a well-known problem in the field of statistics. In this paper, we present a sequential method that can adaptively determine both sample size and model structure. Number-theoretic methods (NTM) are used to sequentially grow the experimental design because of their ability to fill the design space. Feed-forward neural networks (NNs) are used for statistical modeling because of their adjustability in structure-complexity . This adaptive value function approximation (AVFA) method must be automated to enable efficient implementation within ADP. An AVFA algorithm is introduced, that increments the size of the state space training data in each sequential step, and for each sample size a successive model search process is performed to find an optimal NN model. The new algorithm is tested on a nine-dimensional inventory forecasting problem.     

Controlled experiments on the web: survey and practical guide

The web provides an unprecedented opportunity to evaluate ideas quickly using controlled experiments, also called randomized experiments, A/B tests (and their generalizations), split tests, Control/Treatment tests, MultiVariable Tests (MVT) and parallel flights. Controlled experiments embody the best scientific design for establishing a causal relationship between changes and their influence on user-observable behavior. We provide a practical guide to conducting online experiments, where end-users can help guide the development of features. Our experience indicates that significant learning and return-on-investment (ROI) are seen when development teams listen to their customers, not to the Highest Paid Person’s Opinion (HiPPO). We provide several examples of controlled experiments with surprising results. We review the important ingredients of running controlled experiments, and discuss their limitations (both technical and organizational). We focus on several areas that are critical to experimentation, including statistical power, sample size, and techniques for variance reduction. We describe common architectures for experimentation systems and analyze their advantages and disadvantages. We evaluate randomization and hashing techniques, which we show are not as simple in practice as is often assumed. Controlled experiments typically generate large amounts of data, which can be analyzed using data mining techniques to gain deeper understanding of the factors influencing the outcome of interest, leading to new hypotheses and creating a virtuous cycle of improvements. Organizations that embrace controlled experiments with clear evaluation criteria can evolve their systems with automated optimizations and real-time analyses. Based on our extensive practical experience with multiple systems and organizations, we share key lessons that will help practitioners in running trustworthy controlled experiments.     

Control applications of nonlinear convex programming

Since 1984 there has been a concentrated effort to develop efficient interior-point methods for linear programming (LP). In the last few years researchers have begun to appreciate a very important property of these interior-point methods (beyond their efficiency for LP): they extend gracefully to nonlinear convex optimization problems. New interior-point algorithms for problem classes such as semidefinite programming (SDP) or second-order cone programming (SOCP) are now approaching the extreme efficiency of modern linear programming codes. In this paper we discuss three examples of areas of control where our ability to efficiently solve nonlinear convex optimization problems opens up new applications. In the first example we show how SOCP can be used to solve robust open-loop optimal control problems. In the second example, we show how SOCP can be used to simultaneously design the set-point and feedback gains for a controller, and compare this method with the more standard approach. Our final application concerns analysis and synthesis via linear matrix inequalities and SDP.     

Reduced gradient decomposition in multistage linear programming

It is shown that multistage linear programming problems without final constraints allow an ultimate decomposition based on reduced gradient computation. The decomposition results in one-stage linear programming problems of small dimensionality without the necessity of coordination involving master problems and subproblems.     

不同施肥方法对缓释尿素的肥效及氮素利用率的影响

以水稻和玉米为供试作物进行盆栽试验和田间试验。结果表明,水稻和玉米的增产效应均表现为;缓释尿素基追施结合处理>普通尿素基追施结合处理>缓释尿素一次性基施处理>普通尿素一次性基施处理。处理间差异达显著或极显著水准。相比之下,一次性基施改为基追施结合的增产幅度要优于尿素缓效化的肥效。两种作物对尿素的氮素利用率范围值分别为54.8%~70.1%(水稻)和53.6%~59.1%(玉米),其规律与上述肥效相吻合,也是各处理增产的内在原因。在水稻和玉米生产中应推荐在施用PK肥基础上,缓释尿素85%作基肥、15%作追肥这一施肥方法。     

Testing robot controllers using constraint programming and continuous integration

ContextTesting complex industrial robots (CIRs) requires testing several interacting control systems. This is challenging, especially for robots performing process-intensive tasks such as painting or gluing, since their dedicated process control systems can be loosely coupled with the robot’s motion control.ObjectiveCurrent practices for validating CIRs involve manual test case design and execution. To reduce testing costs and improve quality assurance, a trend is to automate the generation of test cases. Our work aims to define a cost-effective automated testing technique to validate CIR control systems in an industrial context.MethodThis paper reports on a methodology, developed at ABB Robotics in collaboration with SIMULA, for the fully automated testing of CIRs control systems. Our approach draws on continuous integration principles and well-established constraint-based testing techniques. It is based on a novel constraint-based model for automatically generating test sequences where test sequences are both generated and executed as part of a continuous integration process.ResultsBy performing a detailed analysis of experimental results over a simplified version of our constraint model, we determine the most appropriate parameterization of the operational version of the constraint model. This version is now being deployed at ABB Robotics’s CIR testing facilities and used on a permanent basis. This paper presents the empirical results obtained when automatically generating test sequences for CIRs at ABB Robotics. In a real industrial setting, the results show that our methodology is not only able to detect reintroduced known faults, but also to spot completely new faults.ConclusionOur empirical evaluation shows that constraint-based testing is appropriate for automatically generating test sequences for CIRs and can be faithfully deployed in an industrial context.     

受控蠕虫框架结构研究

最近几年,随着网络系统应用及复杂性的增加,网络蠕虫成为网络系统安全的重要威胁。因此研究网络蠕虫的相关技术十分重要。给出蠕虫的基本定义,介绍了蠕虫工作流程图,并在此基础上提出了一种受控蠕虫的分布式结构框架;最后从受控蠕虫功能着手描述了受控蠕虫的工作流程图。     

A preliminary study on the impact of a pair design phase on pair programming and solo programming

The drawback of pair programming is the nearly doubled personnel cost. The extra cost of pair programming originates from the strict rule of extreme programming where every line of code should be developed by a pair of developers. Is this rule not a waste of resources? Is it not possible to gain a large portion of the benefits of pair programming by only a small fraction of the meeting time of a pair programming session? We conducted a preliminary study to answer this question by splitting the pair programming process into a pair design and a pair implementation phase. The pair implementation phase is compared to a solo implementation phase, which in turn was preceeded by a pair design phase, as well. The study is preliminary as its major goal was to identify an appropriate sample size for subsequent experiments. The data from this study suggest that there is no difference in terms of development cost between a pair and a solo implementation phase if the cost for developing programs of similar level of correctness is concerned.     

Homotopy techniques in linear programming

In this note, we consider the solution of a linear program, using suitably adapted homotopy techniques of nonlinear programming and equation solving that move through the interior of the polytope of feasible solutions. The homotopy is defined by means of a quadratic regularizing term in an appropriate metric. We also briefly discuss algorithmic implications and connections with the affine variant of Karmarkar's method.This is a revised version of a paper previously entitled Karmarkar's Method and Homotopies with Restarts.     

Object-oriented programming of distributed iterative equation solvers

An object-oriented approach is used to develop classes and frameworks for the implementation of distributed iterative equation solution. The software is implemented using the .NET framework, and builds upon previous work by the author. Development of the framework for iterative solution makes good use of interfaces to isolate sources of complexity. The framework is used for three different solution scenarios (i) conjugate gradient iteration on a single matrix; (ii) conjugate gradient iteration when domain decomposition is used; and (iii) using the Schur complement approach. Moreover, the framework is used for both local and remote objects. The .NET framework makes it very straightforward to program distributed applications, and the object-oriented approach greatly facilitates the software development. The framework was used in a finite element program and the speed-up results are shown.     

A modification of karmarkar's linear programming algorithm

We present a modification of Karmarkar's linear programming algorithm. Our algorithm uses a recentered projected gradient approach thereby obviatinga priori knowledge of the optimal objective function value. Assuming primal and dual nondegeneracy, we prove that our algorithm converges. We present computational comparisons between our algorithm and the revised simplex method. For small, dense constraint matrices we saw little difference between the two methods.     

A flexible algorithm for calculating pair interactions on SIMD architectures

Calculating interactions or correlations between pairs of particles is typically the most time-consuming task in particle simulation or correlation analysis. Straightforward implementations using a double loop over particle pairs have traditionally worked well, especially since compilers usually do a good job of unrolling the inner loop. In order to reach high performance on modern CPU and accelerator architectures, single-instruction multiple-data (SIMD) parallelization has become essential. Avoiding memory bottlenecks is also increasingly important and requires reducing the ratio of memory to arithmetic operations. Moreover, when pairs only interact within a certain cut-off distance, good SIMD utilization can only be achieved by reordering input and output data, which quickly becomes a limiting factor. Here we present an algorithm for SIMD parallelization based on grouping a fixed number of particles, e.g. 2, 4, or 8, into spatial clusters. Calculating all interactions between particles in a pair of such clusters improves data reuse compared to the traditional scheme and results in a more efficient SIMD parallelization. Adjusting the cluster size allows the algorithm to map to SIMD units of various widths. This flexibility not only enables fast and efficient implementation on current CPUs and accelerator architectures like GPUs or Intel MIC, but it also makes the algorithm future-proof. We present the algorithm with an application to molecular dynamics simulations, where we can also make use of the effective buffering the method introduces.