Saif Ur Rehman Khan

Cost-aware challenges for workflow scheduling approaches in cloud computing environments

Workflow Scheduling (WFS) mainly focuses on task allocation to achieve the desired workload balancing by pursuing optimal utilization of available resources. At the same time, relevant performance criteria and system distribution structure must be considered to solve specific WFS problems in cloud computing by providing different services to cloud users on pay-as-you-go and on-demand basis. In the literature, various WFS challenges affecting WFS execution cost have been discussed. However, prior work did not consider such challenges collectively. The main objective of this paper is to facilitate researchers in selecting appropriate cost-aware WFS approaches from the available pool of alternatives. To achieve this objective, we conducted an extensive review to investigate and analyze the underlying concepts of the relevant approaches. The cost-aware relevant challenges of WFS in cloud computing are classified based on Quality of Service (QoS) performance, system functionality and system architecture, which ultimately result in a taxonomy set. Some research opportunities are also discussed that help in identifying future research directions in the area of cloud computing. The findings of this review provide a roadmap for developing cost-aware models, which will motivate researchers to propose better cost-aware approaches for service consumers and/or utility providers in cloud computing. Extensively reviews cost-aware workflow scheduling approaches in cloud computing.Presents a set of taxonomy for cost-aware workflow scheduling challenges.Critically analyzes reported cost-aware workflow scheduling challenges.Provides useful recommendations for service consumers and utility providers.

The impact of test case reduction and prioritization on software testing effectiveness

Software testing is critical but most expensive phase of Software Development Life Cycle (SDLC). Development organizations desire to thoroughly test the software. But this exhaustive testing is impractical due to resource constraints. A large number of test suites are generated using automated tools. But the real challenge is the selection of subset of test cases and/or high order test cases crucial to validate the System Under Test (SUT). Test case reduction and prioritization techniques help test manager to solve this problem at a little cost. In this paper, we investigate their impact on testing process effectiveness using previous empirical studies. The results indicate that these techniques improve the testing effectiveness significantly. At the end, a case study is presented that suggests different useful combinations of these techniques, which are helpful for different testing scenarios.

UML models consistency management

Providing a complete life cycle of UML consistency management process.Presenting a thematic taxonomy of existing state-of-the-art UML consistency management activities based on a set of parameters extracted from the literature.Analytically comparing current state-of-the-art UML consistency management approaches including their commonalities and differences.Outlining a number of potential research issues in this field of study. Unified Modeling Language (UML) has become the de-facto standard to design todays large-size object-oriented systems. However, focusing on multiple UML diagrams is a main cause of breaching the consistency problem, which ultimately reduces the overall software models quality. Consistency management techniques are widely used to ensure the model consistency by correct model-to-model and model-to-code transformation. Consistency management becomes a promising area of research especially for model-driven architecture. In this paper, we extensively review UML consistency management techniques. The proposed techniques have been classified based on the parameters identified from the research literature. Moreover, we performed a qualitative comparison of consistency management techniques in order to identify current research trends, challenges and research gaps in this field of study. Based on the results, we concluded that researchers have not provided more attention on exploring inter-model and semantic consistency problems. Furthermore, state-of-the-art consistency management techniques mostly focus only on three UML diagrams (i.e., class, sequence and state chart) and the remaining UML diagrams have been overlooked. Consequently, due to this incomplete body of knowledge, researchers are unable to take full advantage of overlooked UML diagrams, which may be otherwise useful to handle the consistency management challenge in an efficient manner.

A code coverage-based test suite reduction and prioritization framework

Software testing is extensively used to ensure the development of a quality software system. The test suite size tends to increase by including new test cases due to software evolution. Consequently, the entire test suite cannot be executed considering budget and time limitations. Researchers have examined test suite reduction and prioritization techniques to address the test suite size problem. However, combination of these techniques can be useful for various regression testing situations. In this paper, we present a new code coverage-based test suite reduction and prioritization framework called TestOptimizer. The framework performs a suitable combination of TestFilter and St-Total techniques to determine optimal test cases, keeping in view of time restrictions. The performance of the proposed framework has been assessed using a case study. Results show that TestOptimizer can be beneficial to solve the test suite size problem within time constraints and has a profound impact on the required cost and effort of regression testing.

RePizer: a framework for prioritization of software requirements *

The standard software development life cycle heavily depends on requirements elicited from stakeholders. Based on those requirements, software development is planned and managed from its inception phase to closure. Due to time and resource constraints, it is imperative to identify the high-priority requirements that need to be considered first during the software development process. Moreover, existing prioritization frameworks lack a store of historical data useful for selecting the most suitable prioritization technique of any similar project domain. In this paper, we propose a framework for prioritization of software requirements, called RePizer, to be used in conjunction with a selected prioritization technique to rank software requirements based on defined criteria such as implementation cost. RePizer assists requirements engineers in a decision-making process by retrieving historical data from a requirements repository. RePizer also provides a panoramic view of the entire project to ensure the judicious use of software development resources. We compared the performance of RePizer in terms of expected accuracy and ease of use while separately adopting two different prioritization techniques, planning game (PG) and analytical hierarchy process (AHP). The results showed that RePizer performed better when used in conjunction with the PG technique.

Corrigendum to “A Preliminary Investigation of User Perception and Behavioral Intention for Different Review Types: Customers and Designers Perspective”

The author name Mahwish Waheed should be replaced with Mehwish Waheed. In the body of the paper,   (from β = .50, P = .000, to β = .3, P = .000) should be replaced with the following values (from β = .75, P = .000 to β = .41, P = .001);   (from β = .25, P = .0, to β = .13, n.s.) should be replaced with the following values (from β = .19, P = .05 to β = .06, n.s.);   (from β = .60, P = .000, to β = .26, P = .000) should be replaced with the following values (from β = .24, P = .011 to β = .57, P = 000);   (from β = .20, P = .04, to β = .001, n.s.) should be replaced with the following values (from β = .70, P = .000 to β = .001, n.s.). Figure 1 is corrected as follows. Figure 1 The proposed model.

RAMBUTANS: automatic AOP-specific test generation tool

Aspect-oriented programming (AOP) is a programmatic methodology to handle better modularized code by separating crosscutting concerns from the traditional abstraction boundaries. Automated testing, as one of the most demanding needs of the software development to reduce both human effort and costs, is a delicate issue in testing aspect-oriented programs. Prior studies in the automated test generation for aspect-oriented programs have been very limited with respect to the need for both adequate tool support and capability concerning effectiveness and efficiency. This paper describes a new AOP-specific tool for testing aspect-oriented programs, called RAMBUTANS. The RAMBUTANS tool uses a directed random testing technique that is especially well suited for generating tests for aspectual features in AspectJ. The directed random aspect of the tool is parameterized by associating weights to aspects, advice, methods, and classes by controlling object and joint point creations during the test generation process. We present a comprehensive empirical evaluation of our tool against the current AOP test generation approaches on three industrial aspect-oriented projects. The results of the experimental and statistical tests showed that RAMBUTANS tool produces test suites that have higher fault-detection capability and efficiency for AspectJ-like programs.

A survey on Test Suite Reduction frameworks and tools

An extensive review on automated support for TSR.Presenting a thematic taxonomy to categorize the existing literature based on testing domains and corresponding parameters.Providing a detailed comparative analysis of TSR frameworks based on the devised taxonometric parameters.Synthesizing current state-of-the-art based on the underlying common philosophies.Highlighting several potential research issues in this field of study. Software testing is a widely accepted practice that ensures the quality of a System under Test (SUT). However, the gradual increase of the test suite size demands high portion of testing budget and time. Test Suite Reduction (TSR) is considered a potential approach to deal with the test suite size problem. Moreover, a complete automation support is highly recommended for software testing to adequately meet the challenges of a resource constrained testing environment. Several TSR frameworks and tools have been proposed to efficiently address the test-suite size problem. The main objective of the paper is to comprehensively review the state-of-the-art TSR frameworks to highlights their strengths and weaknesses. Furthermore, the paper focuses on devising a detailed thematic taxonomy to classify existing literature that helps in understanding the underlying issues and proof of concept. Moreover, the paper investigates critical aspects and related features of TSR frameworks and tools based on a set of defined parameters. We also rigorously elaborated various testing domains and approaches followed by the extant TSR frameworks. The results reveal that majority of TSR frameworks focused on randomized unit testing, and a considerable number of frameworks lacks in supporting multi-objective optimization problems. Moreover, there is no generalized framework, effective for testing applications developed in any programming domain. Conversely, Integer Linear Programming (ILP) based TSR frameworks provide an optimal solution for multi-objective optimization problems and improve execution time by running multiple ILP in parallel. The study concludes with new insights and provides an unbiased view of the state-of-the-art TSR frameworks. Finally, we present potential research issues for further investigation to anticipate efficient TSR frameworks.

An improved algorithm to maintain the Binary Search Tree dynamically

Binary Search Tree (BST) is an acyclic graph that is widely used to arrange the data for optimal search. In order to maintain the binary search tree in optimal shape several algorithms have been proposed. A recently proposed technique [1] applies single and double rotations to balance the binary search tree. However, due to double rotation it takes almost double time as compared to single rotation; ultimately increasing the demand for memory and processor. In this paper we propose a new technique which solves the double rotation problem in almost half of the steps of existing algorithm.

ISARE: An Integrated Software Architecture Reuse and Evaluation Framework

Quality is an important consideration in the development of today’s large complex software systems. Software architecture and quality play a vital role in the success or failure of any software system. Similarly to maintain the qualities of a software system during development and to adapt the quality attributes as the software requirements changes, software architecture is necessary. This paper discusses software quality attributes and the support provided by software architecture to achieve the desired quality. A novel Software Architecture Reuse and Evaluation framework is proposed on the basis of existing software architecture evaluation methods with respect to quality requirements. A case study is used for experimental validation of the ISARE. The results show that ISARE ensures the required level of quality requirements in the software architecture and automatable.