Selection is one of the key operations of genetic algorithm (GA). This paper presents a comparative analysis of GA performance in solving multi-objective network design problem (MONDP) using different parent selection methods. Three problem instances were tested and results show that on the average tournament selection is the most effective and most efficient for 10-node network design problem, while Ranking & Scaling is the least effective and least efficient. For 21-node and 36-node network problems, Roulette Wheel is the least effective but most efficient while Ranking & Scaling equals and outperformed tournament in effectiveness and efficiency respectively.

Inspection is a proven approach that is commonly used to manage software quality. To this end many inspection techniques such as Checklist-Based Reading (CBR), Perspective-Based Reading (PBR), Usage-Based Reading (UBR), and Defect-Based Reading (DBR) have been proposed in the literature. Unfortunately, plethora of empirical studies carried out to evaluate these reading techniques have produced inconsistent and conflicting results. Consequently, ad hoc reading and CBR still remain the standard reading techniques in software organizations. This paper investigates the performance of ad hoc and CBR techniques in a traditional paper-based environment. Seventeen undergraduate students of computer science majority of whom are in their final year were used as subjects in a controlled experiment. Results of the experiment indicate that CBR is significantly superior to ad hoc reading in terms of effectiveness, efficiency, effort, and number of false positives. On the average, 4 faults were detected in 69 minutes using ad hoc reading while 11 faults were detected in 42.5 minutes using Checklist-based reading. Also the average number of false positive is about 3.13 in checklist-based approach as against about 6.44 in ad hoc approach.

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A simple semi-conditional (SSC) grammar is a form of regulated rewriting system where the derivations are controlled either by a permitting string alone or by a forbidden string alone and this condition is specified in the rule. The maximum length i (j, resp.) of the permitting (forbidden, resp.) strings serves as a measure of descriptional complexity known as the degree of such grammars. In addition to the degree, the numbers of nonterminals and of conditional rules are also counted into the descriptional complexity measures of these grammars. We improve on some previously obtained results on the computational completeness of SSC grammars by minimizing the number of nonterminals and / or the number of conditional rules for a given degree (i, j). More specifically we prove, using a refined analysis of a normal form for type-0 grammars due to Geffert, that every recursively enumerable language is generated by an SSC grammar of (i) degree (2, 1) with eight conditional rules and nine nonterminals, (ii) degree (3, 1) with seven conditional rules and seven nonterminals (iii) degree (4, 1) with six conditional rules and seven nonterminals and (iv) degree (4, 1) with eight conditional rules and six nonterminals.