Discover how our advanced machine-learning models can forecast software defects before they occur, ensuring your applications are robust and dependable.
[/et_pb_text][et_pb_button button_text=”Learn More” _builder_version=”4.23.1″ _module_preset=”1bffc0fc-42a0-49d1-bd9a-ae3ade2d7206″ hover_enabled=”0″ locked=”off” global_colors_info=”{}”][/et_pb_button][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ admin_label=”About” _builder_version=”4.25.1″ _module_preset=”default” hover_enabled=”0″ template_type=”section” collapsed=”on” global_colors_info=”{}”][et_pb_row _builder_version=”4.25.1″ _module_preset=”048d8e79-b07f-439b-bd57-f41c14f0a56b” hover_enabled=”0″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}”][et_pb_heading title=”Understanding Common Defect Enumeration (CDE)” _builder_version=”4.25.1″ _module_preset=”c33f07d9-41e0-421a-8799-5799df695cce” hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_text _builder_version=”4.25.1″ _module_preset=”2c55a9c4-feed-423b-9edb-ae0b5b365cac” hover_enabled=”0″ global_colors_info=”{}”]The Common Defect Enumeration (CDE) is pivotal in predicting software defects and plays a crucial role in software failure modes effects analysis (FMEA). By categorizing and identifying potential defects early in the development process, CDE helps in mitigating risks and improving software reliability. Our extensive research and data analysis over the past 30 years have enabled us to develop a comprehensive CDE system that is integral to our predictive models, ensuring that software defects are minimized and managed effectively.[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Features” _builder_version=”4.17.6″ _module_preset=”default” hover_enabled=”0″ template_type=”section” collapsed=”on” global_colors_info=”{}”][et_pb_row _builder_version=”4.18.0″ _module_preset=”5138c454-be54-4233-bd3b-f8e6a8747976″ custom_margin=”|auto|-10px|auto|false|false” hover_enabled=”0″ locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_heading title=”Key Features of Our Predictive Models” _builder_version=”4.24.3″ _module_preset=”c33f07d9-41e0-421a-8799-5799df695cce” title_text_align=”center” hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.24.3″ _module_preset=”c948bff6-554d-4de7-99f0-8c1387a293a6″ hover_enabled=”0″ border_radii=”off|6px|6px||” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”24385ca2-769f-4664-bda9-1443db945d08″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_blurb title=”Advanced Defect Prediction” use_icon=”on” font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”ca79a742-981f-479f-a8a2-3a0292efaff0″ hover_enabled=”0″ global_colors_info=”{}”]Utilizes historical data and machine learning to forecast software defects before code is written.
[/et_pb_blurb][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”24385ca2-769f-4664-bda9-1443db945d08″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_blurb title=”CDE Identification” use_icon=”on” font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”ca79a742-981f-479f-a8a2-3a0292efaff0″ hover_enabled=”0″ global_colors_info=”{%22gcid-f2943306-fa6c-45f0-b632-5fc00151366a%22:%91%22icon_color%22,%22icon_color%22%93}”]Intelligently identifies relevant Common Defect Enumerations specific to your application and system.
[/et_pb_blurb][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”24385ca2-769f-4664-bda9-1443db945d08″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_blurb title=”Comprehensive Analysis” use_icon=”on” font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”ca79a742-981f-479f-a8a2-3a0292efaff0″ hover_enabled=”0″ global_colors_info=”{%22gcid-f2943306-fa6c-45f0-b632-5fc00151366a%22:%91%22icon_color%22,%22icon_color%22%93}”]Provides a single analysis for both safe and reliable software by tagging local effects to system effects and safety hazards.
[/et_pb_blurb][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.24.3″ _module_preset=”c948bff6-554d-4de7-99f0-8c1387a293a6″ hover_enabled=”0″ border_radii=”off|||6px|6px” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”24385ca2-769f-4664-bda9-1443db945d08″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_blurb title=”User-Friendly Interface” use_icon=”on” font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”ca79a742-981f-479f-a8a2-3a0292efaff0″ hover_enabled=”0″ global_colors_info=”{}”]Offers an intuitive interface that simplifies the preparation of software FMEA, reducing preparation time significantly.
[/et_pb_blurb][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”24385ca2-769f-4664-bda9-1443db945d08″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_blurb title=”Effective Mitigations” use_icon=”on” font_icon=”||divi||400″ _builder_version=”4.24.3″ _module_preset=”ca79a742-981f-479f-a8a2-3a0292efaff0″ hover_enabled=”0″ global_colors_info=”{%22gcid-f2943306-fa6c-45f0-b632-5fc00151366a%22:%91%22icon_color%22,%22icon_color%22%93}”]Advises on the most effective mitigations, highlighting cost-effective and fast-to-integrate practices.
[/et_pb_blurb][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”24385ca2-769f-4664-bda9-1443db945d08″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_blurb title=”Early Reliability Predictions” use_icon=”on” font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”ca79a742-981f-479f-a8a2-3a0292efaff0″ hover_enabled=”0″ global_colors_info=”{%22gcid-f2943306-fa6c-45f0-b632-5fc00151366a%22:%91%22icon_color%22,%22icon_color%22%93}”]Predicts software failure rates, Mean Time Between Software Failures (MTBSF), availability, and reliability early in the development cycle.
[/et_pb_blurb][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”4.23.1″ _module_preset=”default” hover_enabled=”0″ locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.23.1″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}”][et_pb_button button_text=”Explore Features” button_alignment=”center” _builder_version=”4.24.3″ _module_preset=”8f56c411-db99-421d-8465-2b11f170e039″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_button][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ admin_label=”How It Works” _builder_version=”4.24.1″ _module_preset=”default” hover_enabled=”0″ locked=”off” template_type=”section” collapsed=”on” global_colors_info=”{}”][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” hover_enabled=”0″ locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}”][et_pb_heading title=”How Our Models Predict Software Defects” _builder_version=”4.25.1″ _module_preset=”c33f07d9-41e0-421a-8799-5799df695cce” hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.25.2″ _module_preset=”5138c454-be54-4233-bd3b-f8e6a8747976″ custom_margin=”0px||||false|false” hover_enabled=”0″ global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ border_color_all=”gcid-secondary-color” border_width_top=”2px” global_colors_info=”{%22gcid-secondary-color%22:%91%22border_color_all%22%93}”][et_pb_icon font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”cfd71ba2-5416-411d-a5b2-b2ea5be81af8″ background_color=”gcid-secondary-color” custom_margin=”-24px||||false|false” hover_enabled=”0″ global_colors_info=”{%22gcid-secondary-color%22:%91%22background_color%22%93}”][/et_pb_icon][et_pb_heading title=”Step 1″ module_class=”ai_ignore_all” _builder_version=”4.25.1″ _module_preset=”f0c675ea-2574-4d0e-b725-30f8550a8550″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_heading title=”Data Collection” _builder_version=”4.25.2″ _module_preset=”8c21dae4-c59d-4c2b-958c-0e045c7f06d6″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_text _builder_version=”4.25.1″ _module_preset=”2c55a9c4-feed-423b-9edb-ae0b5b365cac” hover_enabled=”0″ global_colors_info=”{}”]We start by gathering extensive datasets from various software projects, including historical defect data and code repositories.
[/et_pb_text][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ border_color_all=”gcid-secondary-color” border_width_top=”2px” global_colors_info=”{%22gcid-secondary-color%22:%91%22border_color_all%22%93}”][et_pb_icon font_icon=”||fa||900″ _builder_version=”4.24.2″ _module_preset=”cfd71ba2-5416-411d-a5b2-b2ea5be81af8″ background_color=”gcid-secondary-color” custom_margin=”-24px||||false|false” hover_enabled=”0″ global_colors_info=”{%22gcid-secondary-color%22:%91%22background_color%22%93}”][/et_pb_icon][et_pb_heading title=”Step 2″ module_class=”ai_ignore_all” _builder_version=”4.24.3″ _module_preset=”f0c675ea-2574-4d0e-b725-30f8550a8550″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_heading title=”Data Preprocessing” _builder_version=”4.25.1″ _module_preset=”8c21dae4-c59d-4c2b-958c-0e045c7f06d6″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_text _builder_version=”4.25.1″ _module_preset=”2c55a9c4-feed-423b-9edb-ae0b5b365cac” hover_enabled=”0″ locked=”off” global_colors_info=”{}”]The collected data is cleaned and normalized to ensure consistency and accuracy, preparing it for analysis by our machine-learning models.
[/et_pb_text][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ border_color_all=”gcid-secondary-color” border_width_top=”2px” global_colors_info=”{%22gcid-secondary-color%22:%91%22border_color_all%22%93}”][et_pb_icon font_icon=”||fa||900″ _builder_version=”4.24.3″ _module_preset=”cfd71ba2-5416-411d-a5b2-b2ea5be81af8″ background_color=”gcid-secondary-color” custom_margin=”-24px||||false|false” hover_enabled=”0″ global_colors_info=”{%22gcid-secondary-color%22:%91%22background_color%22%93}”][/et_pb_icon][et_pb_heading title=”Step 3″ module_class=”ai_ignore_all” _builder_version=”4.24.2″ _module_preset=”f0c675ea-2574-4d0e-b725-30f8550a8550″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_heading title=”Model Training” _builder_version=”4.25.1″ _module_preset=”8c21dae4-c59d-4c2b-958c-0e045c7f06d6″ hover_enabled=”0″ global_colors_info=”{}”][/et_pb_heading][et_pb_text _builder_version=”4.25.1″ _module_preset=”2c55a9c4-feed-423b-9edb-ae0b5b365cac” hover_enabled=”0″ locked=”off” global_colors_info=”{}”]Our models are trained using the preprocessed data, learning to identify patterns and correlations that indicate potential software defects.
[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Testimonials” _builder_version=”4.17.6″ _module_preset=”default” hover_enabled=”0″ locked=”off” template_type=”section” collapsed=”on” global_colors_info=”{}”][et_pb_row _builder_version=”4.17.6″ _module_preset=”5138c454-be54-4233-bd3b-f8e6a8747976″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_heading title=”What Our Users Say” _builder_version=”4.24.3″ _module_preset=”c33f07d9-41e0-421a-8799-5799df695cce” hover_enabled=”0″ locked=”off” global_colors_info=”{}”][/et_pb_heading][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ use_custom_gutter=”on” gutter_width=”2″ _builder_version=”4.24.2″ _module_preset=”5138c454-be54-4233-bd3b-f8e6a8747976″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.24.2″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_testimonial author=”Jane Doe, Senior Developer” portrait_url=”https://missionreadysoftware.com/wp-content/uploads/2024/09/new-portrait-10-800×800-1-800×800.jpg” module_class=”ai_ignore_font_icon” _builder_version=”4.24.3″ _module_preset=”0e35d7c8-43f7-4642-88fa-284809e5aebb” hover_enabled=”0″ locked=”off” global_colors_info=”{%22gcid-36fd78a7-34bc-404d-873c-dafa34efaae5%22:%91%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22%93}” text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone”]Using Mission Ready Software’s models, we significantly reduced our defect rates and improved our product’s reliability. The insights provided were invaluable.
[/et_pb_testimonial][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.16″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_testimonial author=”John Smith, QA Lead” portrait_url=”https://missionreadysoftware.com/wp-content/uploads/2024/09/new-portrait-9-800×800-1-800×800.jpg” module_class=”ai_ignore_font_icon” _builder_version=”4.24.3″ _module_preset=”0e35d7c8-43f7-4642-88fa-284809e5aebb” hover_enabled=”0″ locked=”off” global_colors_info=”{%22gcid-36fd78a7-34bc-404d-873c-dafa34efaae5%22:%91%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22%93}” text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone”]The predictive capabilities of these models are outstanding. We could identify and mitigate potential issues early in the development cycle, saving us time and resources.
[/et_pb_testimonial][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.16″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_testimonial author=”Emily Johnson, Project Manager” portrait_url=”https://missionreadysoftware.com/wp-content/uploads/2024/09/new-portrait-11-800×800-1-800×800.jpg” module_class=”ai_ignore_font_icon” _builder_version=”4.24.3″ _module_preset=”0e35d7c8-43f7-4642-88fa-284809e5aebb” hover_enabled=”0″ locked=”off” global_colors_info=”{%22gcid-36fd78a7-34bc-404d-873c-dafa34efaae5%22:%91%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22%93}” text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone”]The user-friendly interface and detailed analysis helped us streamline our defect management process. Our team is now more efficient and effective.
[/et_pb_testimonial][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_2,1_2″ use_custom_gutter=”on” gutter_width=”2″ _builder_version=”4.16″ _module_preset=”5138c454-be54-4233-bd3b-f8e6a8747976″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.16″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_testimonial author=”Michael Brown, CTO” module_class=”ai_ignore_font_icon” _builder_version=”4.24.3″ _module_preset=”0e35d7c8-43f7-4642-88fa-284809e5aebb” hover_enabled=”0″ locked=”off” global_colors_info=”{%22gcid-36fd78a7-34bc-404d-873c-dafa34efaae5%22:%91%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22%93}” text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone”]Mission Ready Software’s models have become an integral part of our development workflow. They provide accurate predictions and actionable insights.
[/et_pb_testimonial][/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.16″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_testimonial author=”Sarah Wilson, Software Engineer” module_class=”ai_ignore_font_icon” _builder_version=”4.24.3″ _module_preset=”0e35d7c8-43f7-4642-88fa-284809e5aebb” hover_enabled=”0″ locked=”off” global_colors_info=”{%22gcid-36fd78a7-34bc-404d-873c-dafa34efaae5%22:%91%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22,%22icon_color%22%93}” text_font_size_tablet=”16px” text_font_size_phone=”14px” text_font_size_last_edited=”on|phone”]Thanks to these models, we have a better understanding of defect patterns and can proactively address them, leading to higher quality software releases.
[/et_pb_testimonial][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Statistics” _builder_version=”4.17.3″ _module_preset=”default” hover_enabled=”0″ locked=”off” template_type=”section” collapsed=”on” global_colors_info=”{}”][et_pb_row custom_padding_last_edited=”on|desktop” _builder_version=”4.17.3″ _module_preset=”5138c454-be54-4233-bd3b-f8e6a8747976″ custom_padding=”30px|30px|30px|30px|true|true” custom_padding_tablet=”30px|30px|30px|30px|true|true” custom_padding_phone=”20px|20px|20px|20px|true|true” hover_enabled=”0″ global_colors_info=”{%22gcid-36fd78a7-34bc-404d-873c-dafa34efaae5%22:%91%22border_color_top%22,%22border_color_top%22,%22border_color_top%22%93,%22gcid-828accbb-1ed2-407d-95be-20ab4e191566%22:%91%22border_color_right%22,%22border_color_right%22,%22border_color_right%22%93}”][et_pb_column type=”4_4″ _builder_version=”4.17.3″ _module_preset=”73121f80-a3ef-4484-8763-c3f18e3c56d2″ hover_enabled=”0″ global_colors_info=”{}”][et_pb_heading title=”Our Impact in Numbers” _builder_version=”4.24.2″ _module_preset=”c33f07d9-41e0-421a-8799-5799df695cce” title_text_align=”center” hover_enabled=”0″ locked=”off” global_colors_info=”{}”][/et_pb_heading][et_pb_text _builder_version=”4.24.3″ _module_preset=”2c55a9c4-feed-423b-9edb-ae0b5b365cac” text_orientation=”center” max_width=”800px” module_alignment=”center” hover_enabled=”0″ global_colors_info=”{}”]Our machine-learning models have proven to be highly effective in enhancing software reliability and reducing defects.
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