Abrar A. Qureshi

A Quality-Based Requirement Prioritization Framework Using Binary Inputs

Despite the clear need to prioritize requirements in software projects, finding a practical method for requirements prioritization has proven difficult. Existing requirements prioritization methods that provide the most consistent results are also the most complex, and therefore the most difficult to implement. More informal methods save time and are easier to apply, but may not be suitable for practical scenarios because they lack the structure and consistency required to properly analyze requirements. This paper proposes a novel and practical approach for prioritizing requirements in software projects. The proposed approach attempts to quantify the quality of requirements to provide a measurement that is representative of all quality criteria identified for a specific software project. The derived quality measurement can be easily computed to serve as the main metric for requirements prioritization.

Software requirement prioritization using fuzzy multi-attribute decision making

Although many approaches have been proposed to prioritize requirements in software projects, almost none has been widely adopted. This is mostly due to their complexity, time commitment, lack of consistency, or implementation difficulties. This paper proposes a novel approach to do so that is practical, easy to implement and can show a reasonable level of consistency. In addition, it takes in consideration the imprecise nature of requirements and quality attributes by modeling the latter as fuzzy variables. The problem of prioritizing requirements is formulated as a fuzzy multi-attribute decision problem in which the expected value operator is used to rank the alternatives listed in the problem formulation. This approach can be easily extended to include other quality attributes as well as customized to fit the needs of most software projects.

A Multi-criteria Decision Making Approach for Resource Allocation in Software Engineering

The completion of reliable software products within the expected time frame represents a major problem for companies that develop software applications. As the field grows, the software industry continues to struggle with delivering products in a timely manner. A major cause for increased cost and low quality in software products can be attributed to inadequate resource allocation. Therefore, it is important to develop systematic personnel assignment processes that consider the complete candidate skill set and provide the best fit to increase quality, reduce cost, and reduce training time. This paper presents a novel methodology that considers multiple project-specific skills to assign resources to software tasks. The methodology takes into account the existing capabilities of candidates to determine the best fit based on the required skills for the task. A sample case study is used to show the methodology’s capabilities.

Analysis of Inconsistencies in Object Oriented Metrics

Software Metrics have been proposed for procedural and object oriented paradigms to measure various attributes like complexity, cohesion, software quality, and productivity. Among all of these, “Complexity” and “Cohesion” are considered to be the most important attributes. As object oriented analysis and design appears to be at the forefront of software engineering technologies, many different object-oriented complexity and cohesion metrics have been developed. The aim of the paper is to compare some of the complexity and cohesion metrics and to analyze these metrics and expose their inconsistencies. The paper provides a brief introduction of CK and Morris’s metrics for calculating the complexity and cohesion of a software. The inconsistencies in these methods are exposed by providing various examples. The paper concludes by proving inconsistencies in CK’s cohesion matrices and Morris’s complexity matrices.

Delivering software engineering education through LEGO robotics

The number of software engineering jobs is expected to grow faster than all other jobs over the next decade. STEM education is an important initiative to encourage young students to develop the skills they require to succeed in these positions. The First Lego League sponsors annual tournaments in which students must build and program a robot to accomplish various tasks in order to score points. Previously, the students had not used any process or documentation when developing the programs to run on the robot. This competition provides an opportunity to instruct the students in the benefits of using a formalized process that is essential in many software engineering projects commonly encountered in industry.

Formal semantics of interactions in sequence diagrams for embedded software

Recently, sequence diagrams have been extended with the introduction of a set of operators in the latest specification of the Unified Modeling Language 2 (UML 2). Embedded in combined fragments, these operators are intended to simplify the diagrams structure or alter the order of its events. However, the latest specification introduces a non-trivial degree of ambiguity in the interpretation and understanding of sequence diagrams. As these diagrams are increasingly adopted as modeling tools in embedded software, their ambiguity can exacerbate the challenges encountered in embedded system design. To address this ambiguity, this paper presents a formal model in operational semantics based on Abstract State Machines (ASM) to define the semantics of the loop, break and strict operators in sequence diagrams. Specifically, update rules are devised for ASMs to handle important behaviors present in most embedded software operating in distributed or parallel environments. This formal model can be readily extended to define the semantics of the remaining operators including information about time intervals and their related constraints.

Automatic detection of radio signal obstruction in wireless sensor networks' on-demand deployment

This paper presents an application of machine learning approach for automatic terrain classification suitable for optimal wireless sensor network performance in on-demand deployment. The work entails practical terrain image processing using supervised SVM kernel algorithm moving from gray scale level to color and covering every aspect of a typical terrain image. This paper showcases the integral part of proposed intelligent decision making framework that will be used in wireless sensor network deployment process. The proposed system will automatically identify the areas with potential obstructions to radio frequency signal in a pre-deployment procedure or simulation. This research work presents the performance of the approach which is consistence with practical deployment behavior.

Engineering graphic user interfaces with protected content

Information technology organizations are increasingly having difficulty completing software projects with protected content due to a lack of qualified engineers with proper security credentials. These organizations are turning toward technology to look for advanced software tools that allow them to develop software systems while protecting proprietary or classified content. Many of these software systems require that a graphic user interface (GUI) be developed without accessing protected content. Properly credentialed engineers can later embed the protected content in this GUI. This paper presents a software tool, called GUI Miner, which allows users to edit the contents of GUIs without accessing the source code of the target application. This tool extracts the entire set of GUI widgets in an existing Java application to make them available for editing. Edit changes made on these widgets are automatically reflected on the screen and saved to appropriate class files by modifying their bytecode. Testing of this tool on a set of small Java applications shows that it works as expected without consuming too many memory or processor resources.

Formalizing the design of embedded software using sequence diagrams and abstract state machines

The latest specification of the Unified Modeling Language (UML) 2.x revised completely the structure and elements of sequence diagrams by expanding their modularity via interaction fragments. These fragments are based on a set of operators that can simplify the diagrams structure or alter the order of events in the diagram. Unfortunately, the new revision introduced a significant degree of ambiguity in the interpretation of these diagrams. This ambiguity is exacerbated by the fact that different styles of sequence diagrams can be used for different purposes of modeling and analysis. To address this ambiguity, this paper presents a formal model in operational semantics based on Abstract State Machines (ASM) to define the semantics of sequence diagrams. Specifically, update rules are devised for ASMs to handle important behaviors present in most embedded software operating in distributed or parallel environments. The approach in this paper assumes that lifeline processes in a sequence diagram act as autonomous agents that communicate by exchanging messages among each other in asynchronous and distributed manner. This formal model can be readily extended to define the semantics of the remaining operators including information about time intervals and constraints.