Testing probability distributions underlying aggregated data

In this paper, we analyze and study a hybrid model for testing and learning probability distributions. Here, in addition to samples, the testing algorithm is provided with one of two different types of oracles to the unknown distribution $D$ over $[n]$. More precisely, we define both the dual and cumulative dual access models, in which the algorithm $A$ can both sample from $D$ and respectively, for any $i\in[n]$, - query the probability mass $D(i)$ (query access); or - get the total mass of $\{1,\dots,i\}$, i.e. $\sum_{j=1}^i D(j)$ (cumulative access) These two models, by generalizing the previously studied sampling and query oracle models, allow us to bypass the strong lower bounds established for a number of problems in these settings, while capturing several interesting aspects of these problems -- and providing new insight on the limitations of the models. Finally, we show that while the testing algorithms can be in most cases strictly more efficient, some tasks remain hard even with this additional power

Can we avoid high coupling?

It is considered good software design practice to organize source code into modules and to favour within-module connections (cohesion) over between-module connections (coupling), leading to the oft-repeated maxim "low coupling/high cohesion". Prior research into network theory and its application to software systems has found evidence that many important properties in real software systems exhibit approximately scale-free structure, including coupling; researchers have claimed that such scale-free structures are ubiquitous. This implies that high coupling must be unavoidable, statistically speaking, apparently contradicting standard ideas about software structure. We present a model that leads to the simple predictions that approximately scale-free structures ought to arise both for between-module connectivity and overall connectivity, and not as the result of poor design or optimization shortcuts. These predictions are borne out by our large-scale empirical study. Hence we conclude that high coupling is not avoidable--and that this is in fact quite reasonable

A Hypergraph Dictatorship Test with Perfect Completeness

A hypergraph dictatorship test is first introduced by Samorodnitsky and Trevisan and serves as a key component in their unique games based \PCP construction. Such a test has oracle access to a collection of functions and determines whether all the functions are the same dictatorship, or all their low degree influences are $o(1).$ Their test makes $q\geq3$ queries and has amortized query complexity $1+O(\frac{\log q}{q})$ but has an inherent loss of perfect completeness. In this paper we give an adaptive hypergraph dictatorship test that achieves both perfect completeness and amortized query complexity $1+O(\frac{\log q}{q})$.Comment: Some minor correction

Assessing Code Authorship: The Case of the Linux Kernel

Code authorship is a key information in large-scale open source systems. Among others, it allows maintainers to assess division of work and identify key collaborators. Interestingly, open-source communities lack guidelines on how to manage authorship. This could be mitigated by setting to build an empirical body of knowledge on how authorship-related measures evolve in successful open-source communities. Towards that direction, we perform a case study on the Linux kernel. Our results show that: (a) only a small portion of developers (26 %) makes significant contributions to the code base; (b) the distribution of the number of files per author is highly skewed --- a small group of top authors (3 %) is responsible for hundreds of files, while most authors (75 %) are responsible for at most 11 files; (c) most authors (62 %) have a specialist profile; (d) authors with a high number of co-authorship connections tend to collaborate with others with less connections.Comment: Accepted at 13th International Conference on Open Source Systems (OSS). 12 page

A framework for the simulation of structural software evolution

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 ACM.As functionality is added to an aging piece of software, its original design and structure will tend to erode. This can lead to high coupling, low cohesion and other undesirable effects associated with spaghetti architectures. The underlying forces that cause such degradation have been the subject of much research. However, progress in this field is slow, as its complexity makes it difficult to isolate the causal flows leading to these effects. This is further complicated by the difficulty of generating enough empirical data, in sufficient quantity, and attributing such data to specific points in the causal chain. This article describes a framework for simulating the structural evolution of software. A complete simulation model is built by incrementally adding modules to the framework, each of which contributes an individual evolutionary effect. These effects are then combined to form a multifaceted simulation that evolves a fictitious code base in a manner approximating real-world behavior. We describe the underlying principles and structures of our framework from a theoretical and user perspective; a validation of a simple set of evolutionary parameters is then provided and three empirical software studies generated from open-source software (OSS) are used to support claims and generated results. The research illustrates how simulation can be used to investigate a complex and under-researched area of the development cycle. It also shows the value of incorporating certain human traits into a simulation—factors that, in real-world system development, can significantly influence evolutionary structures

Return of the Great Spaghetti Monster : Learnings from a Twelve-Year Adventure in Web Software Development

The widespread adoption of the World Wide Web has fundamentally changed the landscape of software development. Only ten years ago, very few developers would write software for the Web, let alone consider using JavaScript or other web technologies for writing any serious software applications. In this paper, we reflect upon a twelve-year adventure in web development that began with the development of the Lively Kernel system at Sun Microsystems Labs in 2006. Back then, we also published some papers that identified important challenges in web-based software development based on established software engineering principles. We will revisit our earlier findings and compare the state of the art in web development today to our earlier learnings, followed by some reflections and suggestions for the road forward.Peer reviewe

formal methods and agile development towards a happy marriage

Change makes software different from any other artifact created by humans. Although this is known since the 1970s, change is still often handled in an ad hoc manner. Agile development and, more recently, DevOps have been proposed as a solution, and success stories are reported from industry. Still, principled and rigorous foundations that can be taught, practiced, and systematically replicated are lacking. We argue that change has to become a first-class concept and that the development tools used by engineers and the run time environment supporting software execution should be structured in a way that naturally accommodates change. We distinguish between evolution and adaptation and discuss how software can be made self-adaptive, and how it can cooperate with humans in-the-loop, supporting continuous verification and assuring dependability. We discuss how several research approaches that were investigated in the past decade may be integrated and extended in a roadmap of future work leading to progress in tool support and automation to achieve dependable adaptation and evolution

Chatbot Theory: A naïve and elementary theory for dialogue management

Due to the increasing interested and use of chatbot, its properties and operation possibilities shall be proper realized matching both safety and security issues as well as present the several uses and compositions that this technology supports. This paper focus is on dialogue management since it is considered the core of a chatbot. The dialogue manager is responsible to, more than to transform an input sentence into an output one, hold the illusion of a human conversation. In this sense, it is presented an inceptive theoretical framework through a formal way for chatbots that can be used as a reference to explore, compose, build and discuss chatbots. The discussion is performed mostly on ELIZA since, due to its historical records, it can be considered an important reference chatbot, nevertheless, the proposed theory is compatible with the most recent technologies such those using machine and deep learning. The paper then presents some sketchy instances in order to explore the support provided by the theory.This paper has been supported by COMPETE: POCI-01-0145-FEDER-0070 43 and FCT – Fundação para a Ciência e Tecnologia - Project UID/CEC/ 00319/2013

THE ROLE OF INTERDEPENDENCE IN THE MICRO-FOUNDATIONS OF ORGANIZATION DESIGN: TASK, GOAL, AND KNOWLEDGE INTERDEPENDENCE

Interdependence is a core concept in organization design, yet one that has remained consistently understudied. Current notions of interdependence remain rooted in seminal works, produced at a time when managers’ near-perfect understanding of the task at hand drove the organization design process. In this context, task interdependence was rightly assumed to be exogenously determined by characteristics of the work and the technology. We no longer live in that world, yet our view of interdependence has remained exceedingly task-centric and our treatment of interdependence overly deterministic. As organizations face increasingly unpredictable workstreams and workers co-design the organization alongside managers, our field requires a more comprehensive toolbox that incorporates aspects of agent-based interdependence. In this paper, we synthesize research in organization design, organizational behavior, and other related literatures to examine three types of interdependence that characterize organizations’ workflows: task, goal, and knowledge interdependence. We offer clear definitions for each construct, analyze how each arises endogenously in the design process, explore their interrelations, and pose questions to guide future research