JWalk: a tool for lazy, systematic testing of java classes by design introspection and user interaction

Popular software testing tools, such as JUnit, allow frequent retesting of modified code; yet the manually created test scripts are often seriously incomplete. A unit-testing tool called JWalk has therefore been developed to address the need for systematic unit testing within the context of agile methods. The tool operates directly on the compiled code for Java classes and uses a new lazy method for inducing the changing design of a class on the fly. This is achieved partly through introspection, using Java’s reflection capability, and partly through interaction with the user, constructing and saving test oracles on the fly. Predictive rules reduce the number of oracle values that must be confirmed by the tester. Without human intervention, JWalk performs bounded exhaustive exploration of the class’s method protocols and may be directed to explore the space of algebraic constructions, or the intended design state-space of the tested class. With some human interaction, JWalk performs up to the equivalent of fully automated state-based testing, from a specification that was acquired incrementally

Hikester - the event management application

Today social networks and services are one of the most important part of our everyday life. Most of the daily activities, such as communicating with friends, reading news or dating is usually done using social networks. However, there are activities for which social networks do not yet provide adequate support. This paper focuses on event management and introduces "Hikester". The main objective of this service is to provide users with the possibility to create any event they desire and to invite other users. "Hikester" supports the creation and management of events like attendance of football matches, quest rooms, shared train rides or visit of museums in foreign countries. Here we discuss the project architecture as well as the detailed implementation of the system components: the recommender system, the spam recognition service and the parameters optimizer

gCSP: A Graphical Tool for Designing CSP systems

For broad acceptance of an engineering paradigm, a graphical notation and a supporting design tool seem necessary. This paper discusses certain issues of developing a design environment for building systems based on CSP. Some of the issues discussed depend specifically on the underlying theory of CSP, while a number of them are common for any graphical notation and supporting tools, such as provisions for complexity management and design overview

Dynamically detecting and tolerating IF-Condition Data Races

An IF-Condition Invariance Violation (ICIV) occurs when, after a thread has computed the control expression of an IF statement and while it is executing the THEN or ELSE clauses, another thread updates variables in the IF’s control expression. An ICIV can be easily detected, and is likely to be a sign of a concurrency bug in the code. Typically, the ICIV is caused by a data race, which we call IF-Condition Data Race (ICR). In this paper, we analyze the data races reported in the bug databases of popular software systems and show that ICRs occur relatively often. Then, we present two techniques to handle ICRs dynamically. They rely on simple code transformations and, in one case, additional hardware help. One of them (SW-IF) detects the races, while the other (HW-IF) detects and prevents them. We evaluate SW-IF and HW-IF using a variety of applica-tions. We show that these new techniques are effective at finding new data race bugs and run with low overhead. Specifically, HW-IF finds 5 new (unreported) race bugs and SW-IF finds 3 of them. In addition, 8-threaded executions of SPLASH-2 codes show that, on average, SW-IF adds 2 % execution overhead, while HW-IF adds less than 1%. 1

Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort, and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that influence-based graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201

Programming Robots With Events

International audienceWe introduce how to use event-based style to program robots through the INI programming language. INI features both built-in and user-defined events, a mechanism to handle various kinds of changes happening in the environment. Event handlers run in parallel either synchronously or asynchronously, and events can be reconfigured at runtime to modify their behavior when needed. We apply INI to the humanoid robot called Nao, for which we develop an object tracking program

A novel defense mechanism against web crawler intrusion

Web robots also known as crawlers or spiders are used by search engines, hackers and spammers to gather information about web pages. Timely detection and prevention of unwanted crawlers increases privacy and security of websites. In this research, a novel method to identify web crawlers is proposed to prevent unwanted crawler to access websites. The proposed method suggests a five-factor identification process to detect unwanted crawlers. This study provides the pretest and posttest results along with a systematic evaluation of web pages with the proposed identification technique versus web pages without the proposed identification process. An experiment was performed with repeated measures for two groups with each group containing ninety web pages. The outputs of the logistic regression analysis of treatment and control groups confirm the novel five-factor identification process as an effective mechanism to prevent unwanted web crawlers. This study concluded that the proposed five distinct identifier process is a very effective technique as demonstrated by a successful outcome